Namespace(amp=False, batch_size=64, dali=True, data_shape=300, dataset='coco', dataset_root='~/.mxnet/datasets/', epochs=240, gpus='0,1,2,3', horovod=True, log_interval=100, lr=0.001, lr_decay=0.1, lr_decay_epoch='160,200', momentum=0.9, network='resnet34_v1b', num_workers=32, resume='', save_interval=10, save_prefix='ssd_300_resnet34_v1b_coco', seed=233, start_epoch=0, syncbn=False, val_interval=1, wd=0.0005) Start training from [Epoch 0] Namespace(amp=False, batch_size=64, dali=True, data_shape=300, dataset='coco', dataset_root='~/.mxnet/datasets/', epochs=240, gpus='0,1,2,3', horovod=True, log_interval=100, lr=0.001, lr_decay=0.1, lr_decay_epoch='160,200', momentum=0.9, network='resnet34_v1b', num_workers=32, resume='', save_interval=10, save_prefix='ssd_300_resnet34_v1b_coco', seed=233, start_epoch=0, syncbn=False, val_interval=1, wd=0.0005) Start training from [Epoch 0] Namespace(amp=False, batch_size=64, dali=True, data_shape=300, dataset='coco', dataset_root='~/.mxnet/datasets/', epochs=240, gpus='0,1,2,3', horovod=True, log_interval=100, lr=0.001, lr_decay=0.1, lr_decay_epoch='160,200', momentum=0.9, network='resnet34_v1b', num_workers=32, resume='', save_interval=10, save_prefix='ssd_300_resnet34_v1b_coco', seed=233, start_epoch=0, syncbn=False, val_interval=1, wd=0.0005) Start training from [Epoch 0] Namespace(amp=False, batch_size=64, dali=True, data_shape=300, dataset='coco', dataset_root='~/.mxnet/datasets/', epochs=240, gpus='0,1,2,3', horovod=True, log_interval=100, lr=0.001, lr_decay=0.1, lr_decay_epoch='160,200', momentum=0.9, network='resnet34_v1b', num_workers=32, resume='', save_interval=10, save_prefix='ssd_300_resnet34_v1b_coco', seed=233, start_epoch=0, syncbn=False, val_interval=1, wd=0.0005) Start training from [Epoch 0] [Epoch 0][Batch 99], Speed: 356.554 samples/sec, CrossEntropy=9.720, SmoothL1=3.369 [Epoch 0][Batch 199], Speed: 356.534 samples/sec, CrossEntropy=7.978, SmoothL1=3.144 [Epoch 0][Batch 299], Speed: 358.902 samples/sec, CrossEntropy=7.319, SmoothL1=3.008 [Epoch 0][Batch 399], Speed: 346.698 samples/sec, CrossEntropy=6.949, SmoothL1=2.917 [Epoch 0][Batch 499], Speed: 360.628 samples/sec, CrossEntropy=6.709, SmoothL1=2.849 [Epoch 0][Batch 599], Speed: 362.100 samples/sec, CrossEntropy=6.523, SmoothL1=2.789 [Epoch 0][Batch 699], Speed: 343.357 samples/sec, CrossEntropy=6.388, SmoothL1=2.739 [Epoch 0][Batch 799], Speed: 350.629 samples/sec, CrossEntropy=6.281, SmoothL1=2.691 [Epoch 0][Batch 899], Speed: 340.980 samples/sec, CrossEntropy=6.196, SmoothL1=2.644 [Epoch 0][Batch 999], Speed: 351.778 samples/sec, CrossEntropy=6.116, SmoothL1=2.606 [Epoch 0][Batch 1099], Speed: 348.694 samples/sec, CrossEntropy=6.054, SmoothL1=2.570 [Epoch 0][Batch 1199], Speed: 352.788 samples/sec, CrossEntropy=5.995, SmoothL1=2.538 [Epoch 0][Batch 1299], Speed: 348.591 samples/sec, CrossEntropy=5.942, SmoothL1=2.509 [Epoch 0][Batch 1399], Speed: 352.012 samples/sec, CrossEntropy=5.893, SmoothL1=2.484 [Epoch 0][Batch 1499], Speed: 361.744 samples/sec, CrossEntropy=5.847, SmoothL1=2.459 [Epoch 0][Batch 1599], Speed: 351.147 samples/sec, CrossEntropy=5.803, SmoothL1=2.433 [Epoch 0][Batch 1699], Speed: 352.398 samples/sec, CrossEntropy=5.764, SmoothL1=2.412 [Epoch 0][Batch 1799], Speed: 357.793 samples/sec, CrossEntropy=5.727, SmoothL1=2.391 [Epoch 0] Training cost: 339.827, CrossEntropy=5.710, SmoothL1=2.382 [Epoch 0] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.012 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.031 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.007 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.001 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.018 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.020 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.020 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.030 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.032 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.002 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.036 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.053 person=12.9 bicycle=0.5 car=3.1 motorcycle=0.6 airplane=1.4 bus=1.0 train=0.2 truck=0.2 boat=0.1 traffic light=0.0 fire hydrant=0.0 stop sign=0.0 parking meter=0.0 bench=0.0 bird=0.5 cat=0.7 dog=0.2 horse=2.8 sheep=1.7 cow=3.1 elephant=1.0 bear=0.0 zebra=10.7 giraffe=4.0 backpack=0.0 umbrella=1.5 handbag=0.0 tie=0.0 suitcase=0.0 frisbee=0.0 skis=0.0 snowboard=0.0 sports ball=0.0 kite=0.0 baseball bat=0.0 baseball glove=0.0 skateboard=0.2 surfboard=0.0 tennis racket=0.0 bottle=0.8 wine glass=0.0 cup=2.2 fork=0.0 knife=0.0 spoon=0.0 bowl=2.8 banana=0.0 apple=0.1 sandwich=0.3 orange=4.7 broccoli=0.9 carrot=0.1 hot dog=0.0 pizza=1.3 donut=4.2 cake=0.4 chair=1.4 couch=0.0 potted plant=0.2 bed=0.6 dining table=5.4 toilet=2.8 tv=7.1 laptop=2.0 mouse=0.0 remote=0.0 keyboard=0.1 cell phone=0.0 microwave=0.0 oven=0.0 toaster=0.0 sink=1.6 refrigerator=0.0 book=0.1 clock=8.4 vase=0.0 scissors=0.0 teddy bear=0.0 hair drier=0.0 toothbrush=0.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =1.2 [Epoch 1][Batch 99], Speed: 354.902 samples/sec, CrossEntropy=5.016, SmoothL1=2.029 [Epoch 1][Batch 199], Speed: 359.115 samples/sec, CrossEntropy=5.022, SmoothL1=2.021 [Epoch 1][Batch 299], Speed: 340.333 samples/sec, CrossEntropy=5.001, SmoothL1=2.020 [Epoch 1][Batch 399], Speed: 355.954 samples/sec, CrossEntropy=4.986, SmoothL1=2.015 [Epoch 1][Batch 499], Speed: 353.284 samples/sec, CrossEntropy=4.960, SmoothL1=2.005 [Epoch 1][Batch 599], Speed: 358.260 samples/sec, CrossEntropy=4.942, SmoothL1=1.999 [Epoch 1][Batch 699], Speed: 341.513 samples/sec, CrossEntropy=4.928, SmoothL1=1.990 [Epoch 1][Batch 799], Speed: 356.510 samples/sec, CrossEntropy=4.915, SmoothL1=1.988 [Epoch 1][Batch 899], Speed: 340.864 samples/sec, CrossEntropy=4.899, SmoothL1=1.984 [Epoch 1][Batch 999], Speed: 335.787 samples/sec, CrossEntropy=4.885, SmoothL1=1.977 [Epoch 1][Batch 1099], Speed: 358.851 samples/sec, CrossEntropy=4.871, SmoothL1=1.976 [Epoch 1][Batch 1199], Speed: 353.159 samples/sec, CrossEntropy=4.858, SmoothL1=1.970 [Epoch 1][Batch 1299], Speed: 356.440 samples/sec, CrossEntropy=4.849, SmoothL1=1.971 [Epoch 1][Batch 1399], Speed: 361.418 samples/sec, CrossEntropy=4.839, SmoothL1=1.966 [Epoch 1][Batch 1499], Speed: 346.407 samples/sec, CrossEntropy=4.825, SmoothL1=1.962 [Epoch 1][Batch 1599], Speed: 355.671 samples/sec, CrossEntropy=4.813, SmoothL1=1.959 [Epoch 1][Batch 1699], Speed: 357.391 samples/sec, CrossEntropy=4.799, SmoothL1=1.956 [Epoch 1][Batch 1799], Speed: 355.719 samples/sec, CrossEntropy=4.788, SmoothL1=1.950 [Epoch 1] Training cost: 334.571, CrossEntropy=4.781, SmoothL1=1.949 [Epoch 1] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.038 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.093 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.023 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.002 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.046 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.062 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.063 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.096 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.101 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.003 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.088 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.174 person=16.1 bicycle=1.9 car=5.2 motorcycle=3.8 airplane=5.8 bus=13.7 train=8.4 truck=3.0 boat=0.6 traffic light=0.6 fire hydrant=0.0 stop sign=12.5 parking meter=0.0 bench=0.5 bird=2.4 cat=10.0 dog=8.8 horse=10.4 sheep=3.8 cow=5.6 elephant=6.9 bear=1.6 zebra=17.0 giraffe=12.9 backpack=0.0 umbrella=3.1 handbag=0.0 tie=0.2 suitcase=0.4 frisbee=1.1 skis=0.8 snowboard=0.0 sports ball=0.6 kite=0.6 baseball bat=0.0 baseball glove=0.0 skateboard=2.6 surfboard=0.6 tennis racket=4.1 bottle=2.0 wine glass=0.9 cup=4.4 fork=0.0 knife=0.0 spoon=0.0 bowl=6.1 banana=1.3 apple=0.8 sandwich=3.2 orange=6.0 broccoli=3.9 carrot=0.7 hot dog=0.2 pizza=8.2 donut=6.6 cake=1.6 chair=2.5 couch=5.6 potted plant=1.4 bed=4.7 dining table=9.8 toilet=12.1 tv=13.9 laptop=6.8 mouse=0.0 remote=0.0 keyboard=3.7 cell phone=1.2 microwave=8.0 oven=0.8 toaster=0.0 sink=3.2 refrigerator=1.1 book=0.5 clock=10.2 vase=0.8 scissors=0.0 teddy bear=4.0 hair drier=0.0 toothbrush=0.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =3.8 [Epoch 2][Batch 99], Speed: 360.487 samples/sec, CrossEntropy=4.525, SmoothL1=1.887 [Epoch 2][Batch 199], Speed: 352.465 samples/sec, CrossEntropy=4.518, SmoothL1=1.894 [Epoch 2][Batch 299], Speed: 349.287 samples/sec, CrossEntropy=4.507, SmoothL1=1.882 [Epoch 2][Batch 399], Speed: 359.172 samples/sec, CrossEntropy=4.507, SmoothL1=1.877 [Epoch 2][Batch 499], Speed: 347.872 samples/sec, CrossEntropy=4.500, SmoothL1=1.874 [Epoch 2][Batch 599], Speed: 352.618 samples/sec, CrossEntropy=4.489, SmoothL1=1.867 [Epoch 2][Batch 699], Speed: 346.174 samples/sec, CrossEntropy=4.489, SmoothL1=1.867 [Epoch 2][Batch 799], Speed: 356.442 samples/sec, CrossEntropy=4.486, SmoothL1=1.863 [Epoch 2][Batch 899], Speed: 357.088 samples/sec, CrossEntropy=4.477, SmoothL1=1.863 [Epoch 2][Batch 999], Speed: 361.801 samples/sec, CrossEntropy=4.464, SmoothL1=1.861 [Epoch 2][Batch 1099], Speed: 361.256 samples/sec, CrossEntropy=4.461, SmoothL1=1.860 [Epoch 2][Batch 1199], Speed: 362.419 samples/sec, CrossEntropy=4.454, SmoothL1=1.860 [Epoch 2][Batch 1299], Speed: 351.708 samples/sec, CrossEntropy=4.448, SmoothL1=1.855 [Epoch 2][Batch 1399], Speed: 348.275 samples/sec, CrossEntropy=4.440, SmoothL1=1.853 [Epoch 2][Batch 1499], Speed: 347.791 samples/sec, CrossEntropy=4.433, SmoothL1=1.850 [Epoch 2][Batch 1599], Speed: 350.062 samples/sec, CrossEntropy=4.426, SmoothL1=1.848 [Epoch 2][Batch 1699], Speed: 348.565 samples/sec, CrossEntropy=4.416, SmoothL1=1.847 [Epoch 2][Batch 1799], Speed: 350.459 samples/sec, CrossEntropy=4.413, SmoothL1=1.848 [Epoch 2] Training cost: 334.480, CrossEntropy=4.410, SmoothL1=1.846 [Epoch 2] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.061 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.140 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.043 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.004 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.067 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.100 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.087 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.128 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.133 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.005 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.120 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.236 person=18.1 bicycle=2.3 car=6.8 motorcycle=6.4 airplane=15.0 bus=18.7 train=18.7 truck=4.1 boat=1.4 traffic light=0.9 fire hydrant=1.4 stop sign=20.9 parking meter=0.0 bench=1.6 bird=4.3 cat=19.7 dog=15.3 horse=14.6 sheep=7.9 cow=8.6 elephant=13.3 bear=5.1 zebra=21.6 giraffe=21.8 backpack=0.6 umbrella=4.9 handbag=0.0 tie=1.2 suitcase=0.4 frisbee=2.9 skis=1.1 snowboard=0.0 sports ball=3.4 kite=1.6 baseball bat=1.4 baseball glove=0.0 skateboard=3.7 surfboard=2.5 tennis racket=7.2 bottle=2.9 wine glass=2.3 cup=5.1 fork=0.3 knife=0.2 spoon=0.3 bowl=7.8 banana=2.3 apple=0.9 sandwich=6.8 orange=5.9 broccoli=3.5 carrot=0.9 hot dog=0.4 pizza=17.1 donut=8.9 cake=3.9 chair=2.9 couch=7.8 potted plant=1.8 bed=10.5 dining table=10.9 toilet=17.0 tv=19.5 laptop=11.5 mouse=0.0 remote=0.0 keyboard=8.2 cell phone=3.2 microwave=9.0 oven=3.0 toaster=0.0 sink=4.3 refrigerator=1.9 book=0.8 clock=13.6 vase=2.7 scissors=0.0 teddy bear=7.0 hair drier=0.0 toothbrush=0.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =6.1 [Epoch 3][Batch 99], Speed: 350.880 samples/sec, CrossEntropy=4.263, SmoothL1=1.813 [Epoch 3][Batch 199], Speed: 356.317 samples/sec, CrossEntropy=4.267, SmoothL1=1.814 [Epoch 3][Batch 299], Speed: 358.636 samples/sec, CrossEntropy=4.250, SmoothL1=1.796 [Epoch 3][Batch 399], Speed: 352.200 samples/sec, CrossEntropy=4.239, SmoothL1=1.789 [Epoch 3][Batch 499], Speed: 347.391 samples/sec, CrossEntropy=4.222, SmoothL1=1.791 [Epoch 3][Batch 599], Speed: 357.692 samples/sec, CrossEntropy=4.223, SmoothL1=1.794 [Epoch 3][Batch 699], Speed: 358.264 samples/sec, CrossEntropy=4.220, SmoothL1=1.793 [Epoch 3][Batch 799], Speed: 357.904 samples/sec, CrossEntropy=4.216, SmoothL1=1.789 [Epoch 3][Batch 899], Speed: 347.725 samples/sec, CrossEntropy=4.214, SmoothL1=1.787 [Epoch 3][Batch 999], Speed: 359.209 samples/sec, CrossEntropy=4.206, SmoothL1=1.787 [Epoch 3][Batch 1099], Speed: 352.288 samples/sec, CrossEntropy=4.202, SmoothL1=1.784 [Epoch 3][Batch 1199], Speed: 352.341 samples/sec, CrossEntropy=4.197, SmoothL1=1.786 [Epoch 3][Batch 1299], Speed: 346.539 samples/sec, CrossEntropy=4.191, SmoothL1=1.785 [Epoch 3][Batch 1399], Speed: 363.604 samples/sec, CrossEntropy=4.183, SmoothL1=1.782 [Epoch 3][Batch 1499], Speed: 345.814 samples/sec, CrossEntropy=4.181, SmoothL1=1.778 [Epoch 3][Batch 1599], Speed: 352.345 samples/sec, CrossEntropy=4.177, SmoothL1=1.778 [Epoch 3][Batch 1699], Speed: 359.171 samples/sec, CrossEntropy=4.174, SmoothL1=1.779 [Epoch 3][Batch 1799], Speed: 361.418 samples/sec, CrossEntropy=4.168, SmoothL1=1.777 [Epoch 3] Training cost: 334.660, CrossEntropy=4.166, SmoothL1=1.777 [Epoch 3] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.078 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.176 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.058 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.004 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.083 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.135 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.103 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.151 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.158 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.007 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.147 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.281 person=18.8 bicycle=2.5 car=7.9 motorcycle=9.2 airplane=18.5 bus=23.0 train=21.9 truck=4.8 boat=1.4 traffic light=1.4 fire hydrant=14.1 stop sign=24.3 parking meter=1.5 bench=2.3 bird=6.2 cat=24.4 dog=18.4 horse=16.9 sheep=11.6 cow=11.4 elephant=18.3 bear=15.7 zebra=22.0 giraffe=25.3 backpack=0.7 umbrella=6.4 handbag=0.5 tie=1.5 suitcase=2.3 frisbee=5.1 skis=1.8 snowboard=0.5 sports ball=4.6 kite=2.8 baseball bat=1.3 baseball glove=0.5 skateboard=5.6 surfboard=3.2 tennis racket=7.9 bottle=3.4 wine glass=3.4 cup=6.2 fork=0.5 knife=0.1 spoon=0.1 bowl=9.9 banana=3.2 apple=1.8 sandwich=7.7 orange=7.1 broccoli=5.4 carrot=1.7 hot dog=0.8 pizza=17.9 donut=11.4 cake=4.9 chair=3.7 couch=8.4 potted plant=2.4 bed=15.5 dining table=11.6 toilet=18.9 tv=21.3 laptop=13.9 mouse=1.2 remote=0.8 keyboard=8.8 cell phone=4.0 microwave=12.3 oven=4.9 toaster=0.0 sink=6.1 refrigerator=5.4 book=1.0 clock=15.8 vase=3.9 scissors=0.6 teddy bear=10.3 hair drier=0.0 toothbrush=0.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =7.8 [Epoch 4][Batch 99], Speed: 358.495 samples/sec, CrossEntropy=4.070, SmoothL1=1.726 [Epoch 4][Batch 199], Speed: 349.782 samples/sec, CrossEntropy=4.058, SmoothL1=1.721 [Epoch 4][Batch 299], Speed: 361.320 samples/sec, CrossEntropy=4.049, SmoothL1=1.724 [Epoch 4][Batch 399], Speed: 358.487 samples/sec, CrossEntropy=4.039, SmoothL1=1.730 [Epoch 4][Batch 499], Speed: 355.615 samples/sec, CrossEntropy=4.041, SmoothL1=1.735 [Epoch 4][Batch 599], Speed: 344.087 samples/sec, CrossEntropy=4.041, SmoothL1=1.732 [Epoch 4][Batch 699], Speed: 361.268 samples/sec, CrossEntropy=4.037, SmoothL1=1.728 [Epoch 4][Batch 799], Speed: 354.849 samples/sec, CrossEntropy=4.034, SmoothL1=1.728 [Epoch 4][Batch 899], Speed: 346.062 samples/sec, CrossEntropy=4.029, SmoothL1=1.732 [Epoch 4][Batch 999], Speed: 359.728 samples/sec, CrossEntropy=4.027, SmoothL1=1.735 [Epoch 4][Batch 1099], Speed: 350.285 samples/sec, CrossEntropy=4.021, SmoothL1=1.729 [Epoch 4][Batch 1199], Speed: 353.309 samples/sec, CrossEntropy=4.020, SmoothL1=1.727 [Epoch 4][Batch 1299], Speed: 364.333 samples/sec, CrossEntropy=4.012, SmoothL1=1.727 [Epoch 4][Batch 1399], Speed: 358.550 samples/sec, CrossEntropy=4.010, SmoothL1=1.729 [Epoch 4][Batch 1499], Speed: 346.488 samples/sec, CrossEntropy=4.003, SmoothL1=1.728 [Epoch 4][Batch 1599], Speed: 345.591 samples/sec, CrossEntropy=3.998, SmoothL1=1.728 [Epoch 4][Batch 1699], Speed: 355.782 samples/sec, CrossEntropy=3.996, SmoothL1=1.726 [Epoch 4][Batch 1799], Speed: 364.338 samples/sec, CrossEntropy=3.990, SmoothL1=1.725 [Epoch 4] Training cost: 335.018, CrossEntropy=3.987, SmoothL1=1.724 [Epoch 4] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.092 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.199 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.075 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.005 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.095 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.164 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.115 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.168 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.175 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.009 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.164 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.317 person=20.2 bicycle=3.3 car=8.3 motorcycle=11.4 airplane=22.9 bus=26.8 train=26.9 truck=5.8 boat=2.3 traffic light=2.1 fire hydrant=19.5 stop sign=26.6 parking meter=4.2 bench=3.1 bird=6.7 cat=28.6 dog=22.9 horse=16.4 sheep=13.7 cow=13.0 elephant=22.6 bear=20.8 zebra=27.1 giraffe=27.4 backpack=0.9 umbrella=7.5 handbag=0.1 tie=2.8 suitcase=3.2 frisbee=7.3 skis=2.4 snowboard=0.6 sports ball=5.9 kite=4.0 baseball bat=1.5 baseball glove=0.9 skateboard=7.0 surfboard=3.5 tennis racket=8.8 bottle=3.9 wine glass=4.7 cup=6.6 fork=1.0 knife=0.1 spoon=0.6 bowl=12.2 banana=3.7 apple=1.8 sandwich=10.6 orange=10.0 broccoli=4.7 carrot=1.3 hot dog=1.1 pizza=19.2 donut=12.2 cake=6.2 chair=4.3 couch=12.0 potted plant=2.2 bed=17.1 dining table=11.7 toilet=24.2 tv=22.8 laptop=20.0 mouse=3.0 remote=0.3 keyboard=10.6 cell phone=5.1 microwave=11.9 oven=5.9 toaster=0.0 sink=6.9 refrigerator=5.8 book=1.1 clock=14.7 vase=4.8 scissors=0.8 teddy bear=10.3 hair drier=0.0 toothbrush=0.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =9.2 [Epoch 5][Batch 99], Speed: 348.015 samples/sec, CrossEntropy=3.910, SmoothL1=1.727 [Epoch 5][Batch 199], Speed: 347.454 samples/sec, CrossEntropy=3.913, SmoothL1=1.711 [Epoch 5][Batch 299], Speed: 359.465 samples/sec, CrossEntropy=3.907, SmoothL1=1.716 [Epoch 5][Batch 399], Speed: 368.026 samples/sec, CrossEntropy=3.908, SmoothL1=1.709 [Epoch 5][Batch 499], Speed: 348.356 samples/sec, CrossEntropy=3.902, SmoothL1=1.709 [Epoch 5][Batch 599], Speed: 359.813 samples/sec, CrossEntropy=3.890, SmoothL1=1.705 [Epoch 5][Batch 699], Speed: 355.604 samples/sec, CrossEntropy=3.889, SmoothL1=1.711 [Epoch 5][Batch 799], Speed: 358.164 samples/sec, CrossEntropy=3.884, SmoothL1=1.706 [Epoch 5][Batch 899], Speed: 363.317 samples/sec, CrossEntropy=3.881, SmoothL1=1.705 [Epoch 5][Batch 999], Speed: 344.371 samples/sec, CrossEntropy=3.880, SmoothL1=1.701 [Epoch 5][Batch 1099], Speed: 354.701 samples/sec, CrossEntropy=3.878, SmoothL1=1.700 [Epoch 5][Batch 1199], Speed: 352.192 samples/sec, CrossEntropy=3.873, SmoothL1=1.698 [Epoch 5][Batch 1299], Speed: 344.087 samples/sec, CrossEntropy=3.870, SmoothL1=1.698 [Epoch 5][Batch 1399], Speed: 358.811 samples/sec, CrossEntropy=3.868, SmoothL1=1.698 [Epoch 5][Batch 1499], Speed: 356.394 samples/sec, CrossEntropy=3.865, SmoothL1=1.698 [Epoch 5][Batch 1599], Speed: 350.878 samples/sec, CrossEntropy=3.865, SmoothL1=1.698 [Epoch 5][Batch 1699], Speed: 349.177 samples/sec, CrossEntropy=3.862, SmoothL1=1.696 [Epoch 5][Batch 1799], Speed: 351.288 samples/sec, CrossEntropy=3.854, SmoothL1=1.693 [Epoch 5] Training cost: 334.543, CrossEntropy=3.853, SmoothL1=1.694 [Epoch 5] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.102 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.220 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.081 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.007 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.109 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.179 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.124 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.179 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.186 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.011 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.182 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.337 person=21.1 bicycle=3.9 car=9.3 motorcycle=12.0 airplane=23.2 bus=27.9 train=27.1 truck=6.6 boat=2.7 traffic light=1.9 fire hydrant=20.5 stop sign=26.2 parking meter=5.5 bench=3.8 bird=7.1 cat=30.0 dog=25.9 horse=19.4 sheep=14.5 cow=14.5 elephant=25.0 bear=26.8 zebra=27.3 giraffe=28.8 backpack=0.7 umbrella=8.1 handbag=0.6 tie=3.7 suitcase=3.4 frisbee=9.3 skis=3.2 snowboard=2.5 sports ball=7.9 kite=4.9 baseball bat=2.7 baseball glove=1.7 skateboard=8.1 surfboard=5.6 tennis racket=10.3 bottle=4.0 wine glass=4.9 cup=7.1 fork=1.6 knife=0.7 spoon=0.6 bowl=13.1 banana=3.8 apple=2.2 sandwich=9.9 orange=9.8 broccoli=6.7 carrot=2.0 hot dog=5.2 pizza=22.4 donut=12.8 cake=5.7 chair=4.5 couch=12.8 potted plant=2.3 bed=18.8 dining table=12.1 toilet=25.3 tv=24.3 laptop=21.1 mouse=6.1 remote=1.0 keyboard=11.4 cell phone=6.6 microwave=12.6 oven=5.3 toaster=0.0 sink=8.2 refrigerator=7.9 book=1.6 clock=16.5 vase=5.5 scissors=0.7 teddy bear=13.6 hair drier=0.0 toothbrush=0.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =10.2 [Epoch 6][Batch 99], Speed: 355.339 samples/sec, CrossEntropy=3.804, SmoothL1=1.684 [Epoch 6][Batch 199], Speed: 361.421 samples/sec, CrossEntropy=3.805, SmoothL1=1.658 [Epoch 6][Batch 299], Speed: 347.822 samples/sec, CrossEntropy=3.787, SmoothL1=1.656 [Epoch 6][Batch 399], Speed: 356.628 samples/sec, CrossEntropy=3.780, SmoothL1=1.660 [Epoch 6][Batch 499], Speed: 361.592 samples/sec, CrossEntropy=3.782, SmoothL1=1.662 [Epoch 6][Batch 599], Speed: 364.897 samples/sec, CrossEntropy=3.779, SmoothL1=1.664 [Epoch 6][Batch 699], Speed: 355.236 samples/sec, CrossEntropy=3.778, SmoothL1=1.661 [Epoch 6][Batch 799], Speed: 354.238 samples/sec, CrossEntropy=3.776, SmoothL1=1.663 [Epoch 6][Batch 899], Speed: 350.718 samples/sec, CrossEntropy=3.777, SmoothL1=1.663 [Epoch 6][Batch 999], Speed: 346.999 samples/sec, CrossEntropy=3.776, SmoothL1=1.663 [Epoch 6][Batch 1099], Speed: 348.625 samples/sec, CrossEntropy=3.774, SmoothL1=1.663 [Epoch 6][Batch 1199], Speed: 345.190 samples/sec, CrossEntropy=3.772, SmoothL1=1.659 [Epoch 6][Batch 1299], Speed: 357.018 samples/sec, CrossEntropy=3.771, SmoothL1=1.661 [Epoch 6][Batch 1399], Speed: 365.362 samples/sec, CrossEntropy=3.768, SmoothL1=1.658 [Epoch 6][Batch 1499], Speed: 351.600 samples/sec, CrossEntropy=3.767, SmoothL1=1.657 [Epoch 6][Batch 1599], Speed: 361.039 samples/sec, CrossEntropy=3.763, SmoothL1=1.657 [Epoch 6][Batch 1699], Speed: 344.008 samples/sec, CrossEntropy=3.762, SmoothL1=1.659 [Epoch 6][Batch 1799], Speed: 350.076 samples/sec, CrossEntropy=3.758, SmoothL1=1.657 [Epoch 6] Training cost: 335.133, CrossEntropy=3.755, SmoothL1=1.656 [Epoch 6] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.110 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.231 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.094 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.011 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.120 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.195 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.131 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.191 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.199 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.016 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.197 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.361 person=21.8 bicycle=4.7 car=9.9 motorcycle=12.5 airplane=24.0 bus=28.7 train=29.6 truck=7.5 boat=3.0 traffic light=2.0 fire hydrant=23.8 stop sign=28.0 parking meter=6.0 bench=4.8 bird=7.5 cat=32.9 dog=24.1 horse=20.3 sheep=15.7 cow=14.1 elephant=27.5 bear=30.4 zebra=30.3 giraffe=30.9 backpack=0.9 umbrella=9.0 handbag=0.6 tie=4.7 suitcase=3.8 frisbee=10.2 skis=2.9 snowboard=1.4 sports ball=8.7 kite=5.6 baseball bat=2.7 baseball glove=2.1 skateboard=8.8 surfboard=6.3 tennis racket=11.0 bottle=4.5 wine glass=5.6 cup=8.2 fork=1.7 knife=0.7 spoon=0.5 bowl=14.1 banana=4.6 apple=2.8 sandwich=14.7 orange=10.9 broccoli=7.4 carrot=2.2 hot dog=5.2 pizza=23.1 donut=13.6 cake=8.7 chair=4.9 couch=14.2 potted plant=3.2 bed=20.8 dining table=12.2 toilet=26.7 tv=26.2 laptop=22.1 mouse=7.8 remote=1.2 keyboard=10.5 cell phone=6.8 microwave=13.2 oven=6.5 toaster=0.0 sink=7.6 refrigerator=9.0 book=1.9 clock=17.4 vase=7.1 scissors=1.1 teddy bear=14.2 hair drier=0.0 toothbrush=0.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =11.0 [Epoch 7][Batch 99], Speed: 348.309 samples/sec, CrossEntropy=3.674, SmoothL1=1.603 [Epoch 7][Batch 199], Speed: 359.064 samples/sec, CrossEntropy=3.677, SmoothL1=1.621 [Epoch 7][Batch 299], Speed: 356.007 samples/sec, CrossEntropy=3.686, SmoothL1=1.630 [Epoch 7][Batch 399], Speed: 349.557 samples/sec, CrossEntropy=3.682, SmoothL1=1.632 [Epoch 7][Batch 499], Speed: 350.838 samples/sec, CrossEntropy=3.679, SmoothL1=1.629 [Epoch 7][Batch 599], Speed: 343.606 samples/sec, CrossEntropy=3.682, SmoothL1=1.626 [Epoch 7][Batch 699], Speed: 351.211 samples/sec, CrossEntropy=3.683, SmoothL1=1.631 [Epoch 7][Batch 799], Speed: 343.565 samples/sec, CrossEntropy=3.679, SmoothL1=1.629 [Epoch 7][Batch 899], Speed: 354.774 samples/sec, CrossEntropy=3.682, SmoothL1=1.629 [Epoch 7][Batch 999], Speed: 355.003 samples/sec, CrossEntropy=3.682, SmoothL1=1.632 [Epoch 7][Batch 1099], Speed: 351.875 samples/sec, CrossEntropy=3.681, SmoothL1=1.634 [Epoch 7][Batch 1199], Speed: 348.327 samples/sec, CrossEntropy=3.678, SmoothL1=1.636 [Epoch 7][Batch 1299], Speed: 341.617 samples/sec, CrossEntropy=3.680, SmoothL1=1.638 [Epoch 7][Batch 1399], Speed: 362.790 samples/sec, CrossEntropy=3.682, SmoothL1=1.638 [Epoch 7][Batch 1499], Speed: 350.285 samples/sec, CrossEntropy=3.677, SmoothL1=1.634 [Epoch 7][Batch 1599], Speed: 350.470 samples/sec, CrossEntropy=3.675, SmoothL1=1.632 [Epoch 7][Batch 1699], Speed: 363.381 samples/sec, CrossEntropy=3.673, SmoothL1=1.631 [Epoch 7][Batch 1799], Speed: 357.470 samples/sec, CrossEntropy=3.670, SmoothL1=1.628 [Epoch 7] Training cost: 334.145, CrossEntropy=3.668, SmoothL1=1.627 [Epoch 7] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.119 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.245 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.104 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.011 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.125 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.212 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.138 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.200 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.208 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.018 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.206 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.374 person=22.2 bicycle=6.3 car=10.5 motorcycle=13.7 airplane=26.9 bus=31.8 train=31.8 truck=8.8 boat=3.5 traffic light=2.3 fire hydrant=25.0 stop sign=31.9 parking meter=10.4 bench=5.5 bird=8.8 cat=37.1 dog=27.4 horse=20.2 sheep=16.8 cow=14.3 elephant=27.9 bear=30.9 zebra=32.7 giraffe=32.1 backpack=0.9 umbrella=10.1 handbag=0.4 tie=5.2 suitcase=4.4 frisbee=12.0 skis=3.8 snowboard=3.3 sports ball=9.2 kite=6.5 baseball bat=3.1 baseball glove=3.9 skateboard=10.0 surfboard=5.9 tennis racket=11.3 bottle=4.9 wine glass=6.4 cup=8.3 fork=1.9 knife=1.3 spoon=1.2 bowl=15.4 banana=4.9 apple=2.4 sandwich=14.9 orange=11.2 broccoli=7.5 carrot=2.4 hot dog=6.7 pizza=23.7 donut=14.5 cake=9.5 chair=5.1 couch=13.8 potted plant=3.2 bed=19.8 dining table=13.9 toilet=27.3 tv=28.0 laptop=24.0 mouse=8.1 remote=1.5 keyboard=12.9 cell phone=7.5 microwave=15.4 oven=6.0 toaster=0.0 sink=8.3 refrigerator=10.5 book=1.3 clock=16.8 vase=7.8 scissors=0.3 teddy bear=14.7 hair drier=0.0 toothbrush=0.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =11.9 [Epoch 8][Batch 99], Speed: 354.885 samples/sec, CrossEntropy=3.610, SmoothL1=1.597 [Epoch 8][Batch 199], Speed: 343.158 samples/sec, CrossEntropy=3.622, SmoothL1=1.608 [Epoch 8][Batch 299], Speed: 360.084 samples/sec, CrossEntropy=3.609, SmoothL1=1.601 [Epoch 8][Batch 399], Speed: 364.368 samples/sec, CrossEntropy=3.623, SmoothL1=1.600 [Epoch 8][Batch 499], Speed: 357.098 samples/sec, CrossEntropy=3.624, SmoothL1=1.593 [Epoch 8][Batch 599], Speed: 352.933 samples/sec, CrossEntropy=3.624, SmoothL1=1.594 [Epoch 8][Batch 699], Speed: 358.285 samples/sec, CrossEntropy=3.622, SmoothL1=1.601 [Epoch 8][Batch 799], Speed: 346.553 samples/sec, CrossEntropy=3.616, SmoothL1=1.603 [Epoch 8][Batch 899], Speed: 354.593 samples/sec, CrossEntropy=3.616, SmoothL1=1.600 [Epoch 8][Batch 999], Speed: 352.536 samples/sec, CrossEntropy=3.619, SmoothL1=1.603 [Epoch 8][Batch 1099], Speed: 358.523 samples/sec, CrossEntropy=3.617, SmoothL1=1.604 [Epoch 8][Batch 1199], Speed: 355.514 samples/sec, CrossEntropy=3.613, SmoothL1=1.604 [Epoch 8][Batch 1299], Speed: 346.990 samples/sec, CrossEntropy=3.615, SmoothL1=1.607 [Epoch 8][Batch 1399], Speed: 352.487 samples/sec, CrossEntropy=3.613, SmoothL1=1.608 [Epoch 8][Batch 1499], Speed: 352.250 samples/sec, CrossEntropy=3.614, SmoothL1=1.610 [Epoch 8][Batch 1599], Speed: 361.036 samples/sec, CrossEntropy=3.613, SmoothL1=1.609 [Epoch 8][Batch 1699], Speed: 348.166 samples/sec, CrossEntropy=3.609, SmoothL1=1.606 [Epoch 8][Batch 1799], Speed: 354.796 samples/sec, CrossEntropy=3.607, SmoothL1=1.606 [Epoch 8] Training cost: 335.515, CrossEntropy=3.606, SmoothL1=1.606 [Epoch 8] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.123 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.256 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.104 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.011 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.132 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.216 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.141 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.205 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.019 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.217 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.382 person=22.8 bicycle=6.2 car=11.1 motorcycle=14.0 airplane=26.8 bus=32.1 train=30.7 truck=9.2 boat=3.6 traffic light=2.5 fire hydrant=25.8 stop sign=26.9 parking meter=10.6 bench=6.0 bird=8.3 cat=35.0 dog=26.7 horse=23.6 sheep=17.9 cow=14.6 elephant=29.0 bear=27.1 zebra=30.1 giraffe=32.3 backpack=0.7 umbrella=9.1 handbag=0.3 tie=4.9 suitcase=5.2 frisbee=12.6 skis=3.9 snowboard=4.2 sports ball=9.8 kite=7.7 baseball bat=4.2 baseball glove=3.6 skateboard=11.0 surfboard=6.5 tennis racket=12.3 bottle=5.1 wine glass=6.7 cup=8.8 fork=2.7 knife=1.1 spoon=0.9 bowl=13.4 banana=4.7 apple=3.0 sandwich=16.0 orange=13.7 broccoli=6.6 carrot=2.7 hot dog=7.0 pizza=25.1 donut=14.3 cake=10.3 chair=5.9 couch=15.0 potted plant=3.4 bed=21.3 dining table=13.5 toilet=27.1 tv=29.3 laptop=26.5 mouse=9.3 remote=1.8 keyboard=15.4 cell phone=7.4 microwave=18.0 oven=8.5 toaster=0.0 sink=9.7 refrigerator=12.5 book=1.4 clock=18.6 vase=7.8 scissors=1.2 teddy bear=15.5 hair drier=0.0 toothbrush=0.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =12.3 [Epoch 9][Batch 99], Speed: 348.831 samples/sec, CrossEntropy=3.566, SmoothL1=1.585 [Epoch 9][Batch 199], Speed: 359.492 samples/sec, CrossEntropy=3.561, SmoothL1=1.593 [Epoch 9][Batch 299], Speed: 355.496 samples/sec, CrossEntropy=3.559, SmoothL1=1.589 [Epoch 9][Batch 399], Speed: 352.635 samples/sec, CrossEntropy=3.562, SmoothL1=1.588 [Epoch 9][Batch 499], Speed: 348.107 samples/sec, CrossEntropy=3.558, SmoothL1=1.596 [Epoch 9][Batch 599], Speed: 360.259 samples/sec, CrossEntropy=3.554, SmoothL1=1.593 [Epoch 9][Batch 699], Speed: 347.160 samples/sec, CrossEntropy=3.551, SmoothL1=1.589 [Epoch 9][Batch 799], Speed: 349.099 samples/sec, CrossEntropy=3.548, SmoothL1=1.592 [Epoch 9][Batch 899], Speed: 356.194 samples/sec, CrossEntropy=3.550, SmoothL1=1.593 [Epoch 9][Batch 999], Speed: 348.508 samples/sec, CrossEntropy=3.550, SmoothL1=1.596 [Epoch 9][Batch 1099], Speed: 349.064 samples/sec, CrossEntropy=3.549, SmoothL1=1.595 [Epoch 9][Batch 1199], Speed: 346.715 samples/sec, CrossEntropy=3.547, SmoothL1=1.593 [Epoch 9][Batch 1299], Speed: 347.207 samples/sec, CrossEntropy=3.547, SmoothL1=1.591 [Epoch 9][Batch 1399], Speed: 344.772 samples/sec, CrossEntropy=3.546, SmoothL1=1.591 [Epoch 9][Batch 1499], Speed: 349.630 samples/sec, CrossEntropy=3.546, SmoothL1=1.594 [Epoch 9][Batch 1599], Speed: 346.300 samples/sec, CrossEntropy=3.544, SmoothL1=1.594 [Epoch 9][Batch 1699], Speed: 364.902 samples/sec, CrossEntropy=3.541, SmoothL1=1.591 [Epoch 9][Batch 1799], Speed: 351.966 samples/sec, CrossEntropy=3.540, SmoothL1=1.591 [Epoch 9] Training cost: 335.610, CrossEntropy=3.540, SmoothL1=1.592 [Epoch 9] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.129 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.115 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.013 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.135 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.226 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.147 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.212 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.221 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.021 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.220 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.396 person=23.7 bicycle=6.7 car=11.4 motorcycle=14.0 airplane=27.5 bus=33.8 train=33.9 truck=11.0 boat=4.9 traffic light=2.8 fire hydrant=25.7 stop sign=30.6 parking meter=12.4 bench=5.6 bird=8.9 cat=37.0 dog=30.2 horse=23.8 sheep=18.5 cow=15.4 elephant=29.8 bear=30.7 zebra=31.6 giraffe=33.5 backpack=1.0 umbrella=10.8 handbag=0.2 tie=4.6 suitcase=5.9 frisbee=13.2 skis=4.2 snowboard=4.6 sports ball=10.8 kite=8.5 baseball bat=4.8 baseball glove=4.1 skateboard=10.9 surfboard=6.8 tennis racket=12.5 bottle=5.0 wine glass=6.6 cup=9.2 fork=2.3 knife=0.8 spoon=1.1 bowl=15.4 banana=5.3 apple=3.2 sandwich=16.4 orange=10.0 broccoli=6.8 carrot=2.4 hot dog=6.4 pizza=24.6 donut=15.9 cake=11.6 chair=5.5 couch=18.7 potted plant=4.9 bed=21.9 dining table=13.5 toilet=28.1 tv=28.7 laptop=26.7 mouse=10.4 remote=1.7 keyboard=15.5 cell phone=8.1 microwave=17.7 oven=10.7 toaster=0.0 sink=10.1 refrigerator=13.3 book=1.5 clock=20.0 vase=7.8 scissors=2.2 teddy bear=16.2 hair drier=0.0 toothbrush=0.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =12.9 [Epoch 10][Batch 99], Speed: 359.041 samples/sec, CrossEntropy=3.543, SmoothL1=1.588 [Epoch 10][Batch 199], Speed: 343.517 samples/sec, CrossEntropy=3.508, SmoothL1=1.565 [Epoch 10][Batch 299], Speed: 351.289 samples/sec, CrossEntropy=3.505, SmoothL1=1.569 [Epoch 10][Batch 399], Speed: 359.638 samples/sec, CrossEntropy=3.504, SmoothL1=1.564 [Epoch 10][Batch 499], Speed: 340.236 samples/sec, CrossEntropy=3.512, SmoothL1=1.572 [Epoch 10][Batch 599], Speed: 343.208 samples/sec, CrossEntropy=3.508, SmoothL1=1.568 [Epoch 10][Batch 699], Speed: 362.541 samples/sec, CrossEntropy=3.508, SmoothL1=1.567 [Epoch 10][Batch 799], Speed: 353.558 samples/sec, CrossEntropy=3.502, SmoothL1=1.561 [Epoch 10][Batch 899], Speed: 358.348 samples/sec, CrossEntropy=3.499, SmoothL1=1.563 [Epoch 10][Batch 999], Speed: 349.695 samples/sec, CrossEntropy=3.502, SmoothL1=1.563 [Epoch 10][Batch 1099], Speed: 336.301 samples/sec, CrossEntropy=3.499, SmoothL1=1.563 [Epoch 10][Batch 1199], Speed: 347.506 samples/sec, CrossEntropy=3.495, SmoothL1=1.561 [Epoch 10][Batch 1299], Speed: 359.209 samples/sec, CrossEntropy=3.496, SmoothL1=1.562 [Epoch 10][Batch 1399], Speed: 350.912 samples/sec, CrossEntropy=3.499, SmoothL1=1.563 [Epoch 10][Batch 1499], Speed: 346.966 samples/sec, CrossEntropy=3.495, SmoothL1=1.564 [Epoch 10][Batch 1599], Speed: 354.026 samples/sec, CrossEntropy=3.493, SmoothL1=1.561 [Epoch 10][Batch 1699], Speed: 360.957 samples/sec, CrossEntropy=3.492, SmoothL1=1.560 [Epoch 10][Batch 1799], Speed: 362.663 samples/sec, CrossEntropy=3.489, SmoothL1=1.559 [Epoch 10] Training cost: 334.995, CrossEntropy=3.487, SmoothL1=1.559 [Epoch 10] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.133 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.272 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.117 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.015 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.143 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.150 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.216 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.225 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.024 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.232 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.396 person=23.7 bicycle=6.4 car=11.2 motorcycle=14.5 airplane=28.7 bus=32.9 train=33.3 truck=11.1 boat=4.4 traffic light=2.7 fire hydrant=26.4 stop sign=29.8 parking meter=13.4 bench=6.3 bird=9.5 cat=40.2 dog=32.0 horse=22.4 sheep=20.9 cow=17.8 elephant=29.2 bear=32.9 zebra=31.2 giraffe=34.0 backpack=1.3 umbrella=9.8 handbag=0.4 tie=5.3 suitcase=6.3 frisbee=14.0 skis=4.4 snowboard=4.9 sports ball=9.9 kite=8.5 baseball bat=3.5 baseball glove=4.5 skateboard=11.8 surfboard=7.8 tennis racket=13.0 bottle=5.1 wine glass=6.3 cup=10.2 fork=3.1 knife=0.8 spoon=1.4 bowl=16.2 banana=6.2 apple=3.1 sandwich=17.8 orange=11.7 broccoli=6.9 carrot=3.3 hot dog=6.5 pizza=24.9 donut=16.1 cake=12.8 chair=5.6 couch=18.4 potted plant=4.4 bed=21.2 dining table=13.4 toilet=25.8 tv=30.1 laptop=27.2 mouse=11.9 remote=1.1 keyboard=15.0 cell phone=7.7 microwave=19.9 oven=10.4 toaster=0.0 sink=11.4 refrigerator=14.3 book=1.7 clock=20.4 vase=7.9 scissors=3.2 teddy bear=19.6 hair drier=0.0 toothbrush=0.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =13.3 [Epoch 11][Batch 99], Speed: 359.949 samples/sec, CrossEntropy=3.503, SmoothL1=1.581 [Epoch 11][Batch 199], Speed: 353.143 samples/sec, CrossEntropy=3.500, SmoothL1=1.573 [Epoch 11][Batch 299], Speed: 346.728 samples/sec, CrossEntropy=3.486, SmoothL1=1.565 [Epoch 11][Batch 399], Speed: 357.763 samples/sec, CrossEntropy=3.479, SmoothL1=1.567 [Epoch 11][Batch 499], Speed: 346.166 samples/sec, CrossEntropy=3.476, SmoothL1=1.563 [Epoch 11][Batch 599], Speed: 341.020 samples/sec, CrossEntropy=3.475, SmoothL1=1.557 [Epoch 11][Batch 699], Speed: 361.884 samples/sec, CrossEntropy=3.470, SmoothL1=1.557 [Epoch 11][Batch 799], Speed: 348.444 samples/sec, CrossEntropy=3.467, SmoothL1=1.554 [Epoch 11][Batch 899], Speed: 351.259 samples/sec, CrossEntropy=3.462, SmoothL1=1.553 [Epoch 11][Batch 999], Speed: 356.841 samples/sec, CrossEntropy=3.465, SmoothL1=1.556 [Epoch 11][Batch 1099], Speed: 361.380 samples/sec, CrossEntropy=3.462, SmoothL1=1.555 [Epoch 11][Batch 1199], Speed: 349.253 samples/sec, CrossEntropy=3.455, SmoothL1=1.553 [Epoch 11][Batch 1299], Speed: 364.409 samples/sec, CrossEntropy=3.454, SmoothL1=1.553 [Epoch 11][Batch 1399], Speed: 357.753 samples/sec, CrossEntropy=3.458, SmoothL1=1.557 [Epoch 11][Batch 1499], Speed: 353.551 samples/sec, CrossEntropy=3.458, SmoothL1=1.556 [Epoch 11][Batch 1599], Speed: 350.476 samples/sec, CrossEntropy=3.457, SmoothL1=1.554 [Epoch 11][Batch 1699], Speed: 357.536 samples/sec, CrossEntropy=3.457, SmoothL1=1.553 [Epoch 11][Batch 1799], Speed: 353.413 samples/sec, CrossEntropy=3.454, SmoothL1=1.553 [Epoch 11] Training cost: 334.093, CrossEntropy=3.453, SmoothL1=1.553 [Epoch 11] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.137 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.279 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.123 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.017 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.145 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.239 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.152 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.221 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.231 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.027 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.239 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.404 person=24.1 bicycle=6.2 car=11.8 motorcycle=16.2 airplane=29.8 bus=34.1 train=34.2 truck=12.0 boat=4.6 traffic light=2.9 fire hydrant=27.8 stop sign=31.1 parking meter=15.0 bench=6.1 bird=9.1 cat=39.6 dog=28.8 horse=23.4 sheep=19.1 cow=16.9 elephant=29.6 bear=37.3 zebra=33.8 giraffe=36.5 backpack=1.1 umbrella=11.1 handbag=0.5 tie=5.1 suitcase=6.8 frisbee=14.8 skis=4.3 snowboard=3.9 sports ball=10.7 kite=8.6 baseball bat=5.8 baseball glove=4.5 skateboard=12.3 surfboard=6.7 tennis racket=14.0 bottle=5.0 wine glass=6.9 cup=10.4 fork=2.9 knife=1.1 spoon=1.3 bowl=16.0 banana=5.7 apple=4.0 sandwich=19.5 orange=12.1 broccoli=7.2 carrot=3.0 hot dog=8.0 pizza=24.6 donut=16.4 cake=12.9 chair=5.7 couch=18.0 potted plant=4.2 bed=22.4 dining table=13.9 toilet=28.9 tv=28.8 laptop=26.7 mouse=12.1 remote=1.5 keyboard=15.9 cell phone=8.4 microwave=20.5 oven=11.5 toaster=0.0 sink=10.9 refrigerator=16.8 book=1.8 clock=20.4 vase=8.6 scissors=1.7 teddy bear=17.3 hair drier=0.0 toothbrush=2.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =13.7 [Epoch 12][Batch 99], Speed: 346.485 samples/sec, CrossEntropy=3.395, SmoothL1=1.525 [Epoch 12][Batch 199], Speed: 349.285 samples/sec, CrossEntropy=3.395, SmoothL1=1.525 [Epoch 12][Batch 299], Speed: 348.380 samples/sec, CrossEntropy=3.400, SmoothL1=1.543 [Epoch 12][Batch 399], Speed: 353.921 samples/sec, CrossEntropy=3.421, SmoothL1=1.547 [Epoch 12][Batch 499], Speed: 345.515 samples/sec, CrossEntropy=3.424, SmoothL1=1.542 [Epoch 12][Batch 599], Speed: 360.704 samples/sec, CrossEntropy=3.422, SmoothL1=1.535 [Epoch 12][Batch 699], Speed: 345.550 samples/sec, CrossEntropy=3.419, SmoothL1=1.535 [Epoch 12][Batch 799], Speed: 355.664 samples/sec, CrossEntropy=3.423, SmoothL1=1.530 [Epoch 12][Batch 899], Speed: 347.901 samples/sec, CrossEntropy=3.422, SmoothL1=1.533 [Epoch 12][Batch 999], Speed: 359.423 samples/sec, CrossEntropy=3.416, SmoothL1=1.534 [Epoch 12][Batch 1099], Speed: 349.851 samples/sec, CrossEntropy=3.418, SmoothL1=1.534 [Epoch 12][Batch 1199], Speed: 349.509 samples/sec, CrossEntropy=3.416, SmoothL1=1.533 [Epoch 12][Batch 1299], Speed: 346.371 samples/sec, CrossEntropy=3.413, SmoothL1=1.530 [Epoch 12][Batch 1399], Speed: 349.021 samples/sec, CrossEntropy=3.411, SmoothL1=1.531 [Epoch 12][Batch 1499], Speed: 346.982 samples/sec, CrossEntropy=3.405, SmoothL1=1.528 [Epoch 12][Batch 1599], Speed: 343.012 samples/sec, CrossEntropy=3.407, SmoothL1=1.528 [Epoch 12][Batch 1699], Speed: 349.589 samples/sec, CrossEntropy=3.404, SmoothL1=1.526 [Epoch 12][Batch 1799], Speed: 358.955 samples/sec, CrossEntropy=3.402, SmoothL1=1.522 [Epoch 12] Training cost: 335.438, CrossEntropy=3.401, SmoothL1=1.523 [Epoch 12] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.143 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.284 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.130 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.017 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.154 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.253 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.156 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.225 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.027 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.241 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.416 person=24.7 bicycle=7.6 car=12.1 motorcycle=16.7 airplane=29.6 bus=34.1 train=35.3 truck=11.4 boat=4.8 traffic light=3.3 fire hydrant=28.1 stop sign=31.4 parking meter=15.2 bench=6.7 bird=9.2 cat=41.3 dog=32.6 horse=25.4 sheep=19.7 cow=19.0 elephant=29.6 bear=40.1 zebra=35.0 giraffe=37.4 backpack=1.8 umbrella=12.0 handbag=0.6 tie=5.7 suitcase=7.3 frisbee=13.6 skis=4.9 snowboard=5.0 sports ball=11.2 kite=8.4 baseball bat=4.9 baseball glove=4.8 skateboard=12.8 surfboard=7.4 tennis racket=15.1 bottle=5.9 wine glass=7.2 cup=10.9 fork=3.9 knife=1.2 spoon=1.2 bowl=17.0 banana=6.7 apple=3.4 sandwich=17.9 orange=13.2 broccoli=7.2 carrot=4.0 hot dog=8.1 pizza=26.4 donut=15.9 cake=13.5 chair=6.2 couch=19.1 potted plant=4.8 bed=22.3 dining table=14.7 toilet=28.6 tv=30.8 laptop=30.5 mouse=13.2 remote=1.7 keyboard=16.2 cell phone=8.4 microwave=20.7 oven=12.7 toaster=0.0 sink=10.9 refrigerator=16.5 book=1.7 clock=20.2 vase=8.9 scissors=2.7 teddy bear=18.3 hair drier=0.0 toothbrush=2.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =14.3 [Epoch 13][Batch 99], Speed: 355.915 samples/sec, CrossEntropy=3.353, SmoothL1=1.521 [Epoch 13][Batch 199], Speed: 350.127 samples/sec, CrossEntropy=3.379, SmoothL1=1.534 [Epoch 13][Batch 299], Speed: 344.906 samples/sec, CrossEntropy=3.381, SmoothL1=1.528 [Epoch 13][Batch 399], Speed: 344.715 samples/sec, CrossEntropy=3.378, SmoothL1=1.525 [Epoch 13][Batch 499], Speed: 348.517 samples/sec, CrossEntropy=3.382, SmoothL1=1.523 [Epoch 13][Batch 599], Speed: 350.436 samples/sec, CrossEntropy=3.376, SmoothL1=1.523 [Epoch 13][Batch 699], Speed: 362.618 samples/sec, CrossEntropy=3.373, SmoothL1=1.523 [Epoch 13][Batch 799], Speed: 350.291 samples/sec, CrossEntropy=3.369, SmoothL1=1.519 [Epoch 13][Batch 899], Speed: 347.238 samples/sec, CrossEntropy=3.367, SmoothL1=1.518 [Epoch 13][Batch 999], Speed: 344.456 samples/sec, CrossEntropy=3.366, SmoothL1=1.519 [Epoch 13][Batch 1099], Speed: 347.144 samples/sec, CrossEntropy=3.366, SmoothL1=1.522 [Epoch 13][Batch 1199], Speed: 346.953 samples/sec, CrossEntropy=3.365, SmoothL1=1.522 [Epoch 13][Batch 1299], Speed: 356.624 samples/sec, CrossEntropy=3.361, SmoothL1=1.521 [Epoch 13][Batch 1399], Speed: 350.861 samples/sec, CrossEntropy=3.361, SmoothL1=1.520 [Epoch 13][Batch 1499], Speed: 356.372 samples/sec, CrossEntropy=3.361, SmoothL1=1.517 [Epoch 13][Batch 1599], Speed: 352.253 samples/sec, CrossEntropy=3.359, SmoothL1=1.518 [Epoch 13][Batch 1699], Speed: 349.751 samples/sec, CrossEntropy=3.358, SmoothL1=1.516 [Epoch 13][Batch 1799], Speed: 362.395 samples/sec, CrossEntropy=3.355, SmoothL1=1.516 [Epoch 13] Training cost: 335.262, CrossEntropy=3.355, SmoothL1=1.516 [Epoch 13] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.148 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.290 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.138 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.017 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.153 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.259 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.159 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.229 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.239 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.030 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.246 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.417 person=25.1 bicycle=8.1 car=12.4 motorcycle=17.8 airplane=31.7 bus=35.2 train=35.8 truck=12.4 boat=4.8 traffic light=3.2 fire hydrant=30.6 stop sign=33.1 parking meter=15.8 bench=7.4 bird=9.1 cat=41.8 dog=35.5 horse=23.2 sheep=21.2 cow=18.4 elephant=31.6 bear=39.9 zebra=35.3 giraffe=37.5 backpack=1.2 umbrella=12.6 handbag=0.9 tie=6.0 suitcase=7.8 frisbee=15.0 skis=4.9 snowboard=4.0 sports ball=10.1 kite=9.4 baseball bat=5.2 baseball glove=4.8 skateboard=12.3 surfboard=8.5 tennis racket=14.7 bottle=5.5 wine glass=7.6 cup=11.1 fork=3.1 knife=0.7 spoon=1.4 bowl=16.6 banana=7.9 apple=3.7 sandwich=21.2 orange=12.5 broccoli=9.7 carrot=3.2 hot dog=8.3 pizza=27.9 donut=16.4 cake=13.2 chair=6.3 couch=20.4 potted plant=4.8 bed=25.3 dining table=14.5 toilet=29.5 tv=31.2 laptop=29.9 mouse=15.1 remote=1.5 keyboard=17.9 cell phone=8.7 microwave=21.1 oven=13.3 toaster=0.0 sink=12.1 refrigerator=17.7 book=1.8 clock=23.0 vase=8.6 scissors=2.0 teddy bear=19.3 hair drier=0.0 toothbrush=1.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =14.8 [Epoch 14][Batch 99], Speed: 340.614 samples/sec, CrossEntropy=3.337, SmoothL1=1.483 [Epoch 14][Batch 199], Speed: 358.835 samples/sec, CrossEntropy=3.345, SmoothL1=1.498 [Epoch 14][Batch 299], Speed: 351.938 samples/sec, CrossEntropy=3.340, SmoothL1=1.496 [Epoch 14][Batch 399], Speed: 346.172 samples/sec, CrossEntropy=3.334, SmoothL1=1.491 [Epoch 14][Batch 499], Speed: 354.465 samples/sec, CrossEntropy=3.340, SmoothL1=1.496 [Epoch 14][Batch 599], Speed: 361.926 samples/sec, CrossEntropy=3.337, SmoothL1=1.496 [Epoch 14][Batch 699], Speed: 364.008 samples/sec, CrossEntropy=3.330, SmoothL1=1.494 [Epoch 14][Batch 799], Speed: 343.923 samples/sec, CrossEntropy=3.329, SmoothL1=1.489 [Epoch 14][Batch 899], Speed: 352.481 samples/sec, CrossEntropy=3.333, SmoothL1=1.493 [Epoch 14][Batch 999], Speed: 358.474 samples/sec, CrossEntropy=3.334, SmoothL1=1.496 [Epoch 14][Batch 1099], Speed: 354.044 samples/sec, CrossEntropy=3.331, SmoothL1=1.494 [Epoch 14][Batch 1199], Speed: 349.001 samples/sec, CrossEntropy=3.334, SmoothL1=1.492 [Epoch 14][Batch 1299], Speed: 351.185 samples/sec, CrossEntropy=3.332, SmoothL1=1.492 [Epoch 14][Batch 1399], Speed: 359.935 samples/sec, CrossEntropy=3.333, SmoothL1=1.493 [Epoch 14][Batch 1499], Speed: 360.776 samples/sec, CrossEntropy=3.331, SmoothL1=1.492 [Epoch 14][Batch 1599], Speed: 346.687 samples/sec, CrossEntropy=3.331, SmoothL1=1.492 [Epoch 14][Batch 1699], Speed: 361.224 samples/sec, CrossEntropy=3.328, SmoothL1=1.492 [Epoch 14][Batch 1799], Speed: 355.541 samples/sec, CrossEntropy=3.326, SmoothL1=1.492 [Epoch 14] Training cost: 335.095, CrossEntropy=3.326, SmoothL1=1.492 [Epoch 14] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.148 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.294 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.138 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.018 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.158 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.263 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.161 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.232 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.242 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.030 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.251 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.431 person=25.1 bicycle=8.5 car=12.5 motorcycle=17.3 airplane=32.5 bus=35.1 train=35.1 truck=12.8 boat=5.1 traffic light=3.3 fire hydrant=29.4 stop sign=30.5 parking meter=15.0 bench=7.3 bird=9.2 cat=40.6 dog=33.0 horse=25.7 sheep=20.1 cow=19.7 elephant=33.1 bear=39.9 zebra=35.2 giraffe=37.6 backpack=1.3 umbrella=12.2 handbag=0.7 tie=6.8 suitcase=7.2 frisbee=16.7 skis=4.9 snowboard=4.8 sports ball=12.3 kite=9.0 baseball bat=5.8 baseball glove=4.2 skateboard=12.7 surfboard=8.8 tennis racket=15.7 bottle=6.0 wine glass=8.2 cup=11.2 fork=3.6 knife=1.4 spoon=1.6 bowl=17.3 banana=7.8 apple=2.7 sandwich=17.4 orange=12.6 broccoli=9.1 carrot=4.5 hot dog=8.7 pizza=27.2 donut=16.5 cake=13.5 chair=6.4 couch=20.0 potted plant=5.2 bed=25.7 dining table=13.6 toilet=30.9 tv=30.3 laptop=29.6 mouse=15.0 remote=1.5 keyboard=17.3 cell phone=9.6 microwave=21.8 oven=13.2 toaster=0.0 sink=10.9 refrigerator=18.5 book=1.8 clock=22.2 vase=10.0 scissors=5.2 teddy bear=19.2 hair drier=0.0 toothbrush=1.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =14.8 [Epoch 15][Batch 99], Speed: 352.162 samples/sec, CrossEntropy=3.298, SmoothL1=1.482 [Epoch 15][Batch 199], Speed: 352.767 samples/sec, CrossEntropy=3.306, SmoothL1=1.489 [Epoch 15][Batch 299], Speed: 345.319 samples/sec, CrossEntropy=3.307, SmoothL1=1.490 [Epoch 15][Batch 399], Speed: 358.530 samples/sec, CrossEntropy=3.302, SmoothL1=1.484 [Epoch 15][Batch 499], Speed: 346.766 samples/sec, CrossEntropy=3.302, SmoothL1=1.477 [Epoch 15][Batch 599], Speed: 365.261 samples/sec, CrossEntropy=3.312, SmoothL1=1.482 [Epoch 15][Batch 699], Speed: 356.920 samples/sec, CrossEntropy=3.315, SmoothL1=1.481 [Epoch 15][Batch 799], Speed: 357.388 samples/sec, CrossEntropy=3.309, SmoothL1=1.478 [Epoch 15][Batch 899], Speed: 357.768 samples/sec, CrossEntropy=3.311, SmoothL1=1.482 [Epoch 15][Batch 999], Speed: 360.210 samples/sec, CrossEntropy=3.308, SmoothL1=1.484 [Epoch 15][Batch 1099], Speed: 358.872 samples/sec, CrossEntropy=3.306, SmoothL1=1.482 [Epoch 15][Batch 1199], Speed: 362.480 samples/sec, CrossEntropy=3.306, SmoothL1=1.484 [Epoch 15][Batch 1299], Speed: 362.772 samples/sec, CrossEntropy=3.305, SmoothL1=1.485 [Epoch 15][Batch 1399], Speed: 361.398 samples/sec, CrossEntropy=3.302, SmoothL1=1.485 [Epoch 15][Batch 1499], Speed: 354.892 samples/sec, CrossEntropy=3.305, SmoothL1=1.487 [Epoch 15][Batch 1599], Speed: 348.013 samples/sec, CrossEntropy=3.303, SmoothL1=1.486 [Epoch 15][Batch 1699], Speed: 348.747 samples/sec, CrossEntropy=3.304, SmoothL1=1.486 [Epoch 15][Batch 1799], Speed: 359.844 samples/sec, CrossEntropy=3.305, SmoothL1=1.489 [Epoch 15] Training cost: 334.587, CrossEntropy=3.303, SmoothL1=1.488 [Epoch 15] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.154 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.298 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.146 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.018 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.161 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.275 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.165 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.237 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.031 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.255 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 person=25.5 bicycle=8.5 car=13.0 motorcycle=19.0 airplane=33.5 bus=36.7 train=37.6 truck=13.8 boat=5.6 traffic light=3.4 fire hydrant=29.1 stop sign=34.5 parking meter=16.1 bench=7.4 bird=9.4 cat=43.9 dog=33.8 horse=27.1 sheep=21.6 cow=19.3 elephant=32.8 bear=43.2 zebra=35.5 giraffe=37.5 backpack=1.1 umbrella=12.7 handbag=0.9 tie=7.1 suitcase=7.8 frisbee=17.8 skis=5.5 snowboard=6.3 sports ball=10.4 kite=9.8 baseball bat=4.9 baseball glove=4.9 skateboard=13.9 surfboard=9.3 tennis racket=14.9 bottle=6.9 wine glass=7.3 cup=11.8 fork=3.4 knife=1.2 spoon=1.2 bowl=17.5 banana=7.7 apple=3.7 sandwich=19.5 orange=12.9 broccoli=10.0 carrot=4.4 hot dog=9.8 pizza=27.8 donut=15.8 cake=13.4 chair=6.9 couch=23.3 potted plant=5.5 bed=24.6 dining table=15.3 toilet=31.5 tv=31.4 laptop=32.2 mouse=15.8 remote=1.5 keyboard=17.9 cell phone=9.2 microwave=21.3 oven=14.7 toaster=0.0 sink=10.8 refrigerator=19.0 book=2.0 clock=21.1 vase=8.9 scissors=6.7 teddy bear=19.9 hair drier=0.0 toothbrush=2.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =15.4 [Epoch 16][Batch 99], Speed: 352.553 samples/sec, CrossEntropy=3.252, SmoothL1=1.494 [Epoch 16][Batch 199], Speed: 349.851 samples/sec, CrossEntropy=3.267, SmoothL1=1.499 [Epoch 16][Batch 299], Speed: 356.336 samples/sec, CrossEntropy=3.280, SmoothL1=1.490 [Epoch 16][Batch 399], Speed: 348.051 samples/sec, CrossEntropy=3.271, SmoothL1=1.486 [Epoch 16][Batch 499], Speed: 352.623 samples/sec, CrossEntropy=3.273, SmoothL1=1.481 [Epoch 16][Batch 599], Speed: 350.058 samples/sec, CrossEntropy=3.277, SmoothL1=1.481 [Epoch 16][Batch 699], Speed: 361.162 samples/sec, CrossEntropy=3.273, SmoothL1=1.476 [Epoch 16][Batch 799], Speed: 356.947 samples/sec, CrossEntropy=3.271, SmoothL1=1.472 [Epoch 16][Batch 899], Speed: 342.782 samples/sec, CrossEntropy=3.272, SmoothL1=1.473 [Epoch 16][Batch 999], Speed: 350.329 samples/sec, CrossEntropy=3.275, SmoothL1=1.478 [Epoch 16][Batch 1099], Speed: 353.104 samples/sec, CrossEntropy=3.276, SmoothL1=1.482 [Epoch 16][Batch 1199], Speed: 362.519 samples/sec, CrossEntropy=3.279, SmoothL1=1.482 [Epoch 16][Batch 1299], Speed: 350.188 samples/sec, CrossEntropy=3.276, SmoothL1=1.482 [Epoch 16][Batch 1399], Speed: 363.584 samples/sec, CrossEntropy=3.277, SmoothL1=1.486 [Epoch 16][Batch 1499], Speed: 344.050 samples/sec, CrossEntropy=3.275, SmoothL1=1.487 [Epoch 16][Batch 1599], Speed: 359.738 samples/sec, CrossEntropy=3.275, SmoothL1=1.486 [Epoch 16][Batch 1699], Speed: 358.751 samples/sec, CrossEntropy=3.271, SmoothL1=1.485 [Epoch 16][Batch 1799], Speed: 353.146 samples/sec, CrossEntropy=3.271, SmoothL1=1.485 [Epoch 16] Training cost: 334.939, CrossEntropy=3.271, SmoothL1=1.484 [Epoch 16] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.156 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.301 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.147 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.018 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.162 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.276 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.166 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.239 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.033 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.260 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.434 person=25.2 bicycle=8.2 car=13.1 motorcycle=16.5 airplane=33.6 bus=36.6 train=37.5 truck=14.3 boat=6.1 traffic light=3.8 fire hydrant=30.5 stop sign=31.3 parking meter=19.0 bench=8.4 bird=8.9 cat=43.7 dog=34.2 horse=26.5 sheep=21.6 cow=18.5 elephant=32.5 bear=43.9 zebra=35.9 giraffe=37.8 backpack=1.2 umbrella=12.9 handbag=0.9 tie=6.7 suitcase=8.5 frisbee=17.3 skis=5.4 snowboard=5.7 sports ball=10.3 kite=9.1 baseball bat=5.2 baseball glove=6.2 skateboard=14.5 surfboard=9.4 tennis racket=16.7 bottle=6.5 wine glass=7.7 cup=12.3 fork=4.4 knife=1.3 spoon=1.5 bowl=18.8 banana=8.8 apple=3.3 sandwich=20.7 orange=15.4 broccoli=9.7 carrot=5.0 hot dog=9.7 pizza=26.1 donut=18.5 cake=14.5 chair=6.4 couch=21.9 potted plant=4.9 bed=24.3 dining table=14.8 toilet=32.4 tv=32.2 laptop=30.2 mouse=18.7 remote=1.7 keyboard=17.0 cell phone=9.5 microwave=25.0 oven=13.3 toaster=0.0 sink=11.6 refrigerator=18.8 book=2.4 clock=22.0 vase=10.1 scissors=2.2 teddy bear=21.8 hair drier=0.0 toothbrush=1.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =15.6 [Epoch 17][Batch 99], Speed: 344.518 samples/sec, CrossEntropy=3.268, SmoothL1=1.483 [Epoch 17][Batch 199], Speed: 359.453 samples/sec, CrossEntropy=3.257, SmoothL1=1.476 [Epoch 17][Batch 299], Speed: 342.926 samples/sec, CrossEntropy=3.251, SmoothL1=1.474 [Epoch 17][Batch 399], Speed: 343.488 samples/sec, CrossEntropy=3.255, SmoothL1=1.470 [Epoch 17][Batch 499], Speed: 349.492 samples/sec, CrossEntropy=3.260, SmoothL1=1.471 [Epoch 17][Batch 599], Speed: 351.951 samples/sec, CrossEntropy=3.255, SmoothL1=1.466 [Epoch 17][Batch 699], Speed: 365.077 samples/sec, CrossEntropy=3.259, SmoothL1=1.466 [Epoch 17][Batch 799], Speed: 359.116 samples/sec, CrossEntropy=3.258, SmoothL1=1.464 [Epoch 17][Batch 899], Speed: 340.459 samples/sec, CrossEntropy=3.261, SmoothL1=1.464 [Epoch 17][Batch 999], Speed: 354.896 samples/sec, CrossEntropy=3.259, SmoothL1=1.462 [Epoch 17][Batch 1099], Speed: 358.166 samples/sec, CrossEntropy=3.259, SmoothL1=1.461 [Epoch 17][Batch 1199], Speed: 347.205 samples/sec, CrossEntropy=3.257, SmoothL1=1.461 [Epoch 17][Batch 1299], Speed: 351.281 samples/sec, CrossEntropy=3.257, SmoothL1=1.464 [Epoch 17][Batch 1399], Speed: 345.369 samples/sec, CrossEntropy=3.252, SmoothL1=1.462 [Epoch 17][Batch 1499], Speed: 363.463 samples/sec, CrossEntropy=3.251, SmoothL1=1.462 [Epoch 17][Batch 1599], Speed: 365.202 samples/sec, CrossEntropy=3.249, SmoothL1=1.462 [Epoch 17][Batch 1699], Speed: 352.363 samples/sec, CrossEntropy=3.245, SmoothL1=1.461 [Epoch 17][Batch 1799], Speed: 349.194 samples/sec, CrossEntropy=3.243, SmoothL1=1.461 [Epoch 17] Training cost: 334.950, CrossEntropy=3.242, SmoothL1=1.461 [Epoch 17] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.158 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.308 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.150 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.019 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.163 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.282 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.167 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.242 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.253 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.035 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.262 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.443 person=25.8 bicycle=7.9 car=13.5 motorcycle=18.9 airplane=33.6 bus=37.8 train=36.8 truck=14.3 boat=6.3 traffic light=3.4 fire hydrant=29.1 stop sign=32.7 parking meter=18.5 bench=7.8 bird=9.4 cat=43.4 dog=33.0 horse=26.2 sheep=21.2 cow=21.0 elephant=33.3 bear=42.9 zebra=35.6 giraffe=37.3 backpack=1.5 umbrella=13.5 handbag=1.0 tie=7.4 suitcase=9.0 frisbee=17.0 skis=5.8 snowboard=5.3 sports ball=11.5 kite=10.3 baseball bat=6.5 baseball glove=5.7 skateboard=15.1 surfboard=9.1 tennis racket=16.9 bottle=6.9 wine glass=8.3 cup=12.3 fork=4.3 knife=1.5 spoon=1.0 bowl=18.5 banana=9.0 apple=4.5 sandwich=19.7 orange=13.9 broccoli=10.0 carrot=5.5 hot dog=10.7 pizza=28.4 donut=17.8 cake=13.8 chair=7.5 couch=21.4 potted plant=5.6 bed=27.1 dining table=14.3 toilet=28.6 tv=32.2 laptop=30.7 mouse=19.1 remote=2.3 keyboard=17.7 cell phone=10.1 microwave=27.4 oven=13.4 toaster=0.0 sink=12.0 refrigerator=19.2 book=1.9 clock=22.6 vase=9.4 scissors=6.3 teddy bear=21.3 hair drier=0.0 toothbrush=2.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =15.8 [Epoch 18][Batch 99], Speed: 348.899 samples/sec, CrossEntropy=3.230, SmoothL1=1.490 [Epoch 18][Batch 199], Speed: 359.540 samples/sec, CrossEntropy=3.228, SmoothL1=1.480 [Epoch 18][Batch 299], Speed: 355.781 samples/sec, CrossEntropy=3.216, SmoothL1=1.458 [Epoch 18][Batch 399], Speed: 346.010 samples/sec, CrossEntropy=3.217, SmoothL1=1.451 [Epoch 18][Batch 499], Speed: 351.847 samples/sec, CrossEntropy=3.209, SmoothL1=1.451 [Epoch 18][Batch 599], Speed: 352.877 samples/sec, CrossEntropy=3.209, SmoothL1=1.451 [Epoch 18][Batch 699], Speed: 361.011 samples/sec, CrossEntropy=3.216, SmoothL1=1.451 [Epoch 18][Batch 799], Speed: 349.671 samples/sec, CrossEntropy=3.216, SmoothL1=1.454 [Epoch 18][Batch 899], Speed: 354.054 samples/sec, CrossEntropy=3.216, SmoothL1=1.453 [Epoch 18][Batch 999], Speed: 358.814 samples/sec, CrossEntropy=3.218, SmoothL1=1.455 [Epoch 18][Batch 1099], Speed: 353.948 samples/sec, CrossEntropy=3.217, SmoothL1=1.451 [Epoch 18][Batch 1199], Speed: 352.633 samples/sec, CrossEntropy=3.215, SmoothL1=1.452 [Epoch 18][Batch 1299], Speed: 350.566 samples/sec, CrossEntropy=3.217, SmoothL1=1.452 [Epoch 18][Batch 1399], Speed: 362.823 samples/sec, CrossEntropy=3.217, SmoothL1=1.453 [Epoch 18][Batch 1499], Speed: 353.828 samples/sec, CrossEntropy=3.216, SmoothL1=1.452 [Epoch 18][Batch 1599], Speed: 350.437 samples/sec, CrossEntropy=3.214, SmoothL1=1.451 [Epoch 18][Batch 1699], Speed: 356.397 samples/sec, CrossEntropy=3.209, SmoothL1=1.448 [Epoch 18][Batch 1799], Speed: 362.047 samples/sec, CrossEntropy=3.207, SmoothL1=1.449 [Epoch 18] Training cost: 334.584, CrossEntropy=3.208, SmoothL1=1.450 [Epoch 18] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.160 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.311 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.154 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.019 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.166 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.288 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.171 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.244 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.254 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.035 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.446 person=26.2 bicycle=7.8 car=13.7 motorcycle=18.6 airplane=33.1 bus=37.7 train=37.5 truck=14.4 boat=6.4 traffic light=3.5 fire hydrant=31.0 stop sign=32.0 parking meter=16.3 bench=7.9 bird=10.3 cat=43.7 dog=35.3 horse=27.5 sheep=22.2 cow=21.6 elephant=33.1 bear=43.8 zebra=35.2 giraffe=36.6 backpack=1.4 umbrella=13.3 handbag=0.9 tie=6.9 suitcase=8.0 frisbee=17.7 skis=4.9 snowboard=6.1 sports ball=11.4 kite=10.5 baseball bat=6.2 baseball glove=5.6 skateboard=15.2 surfboard=9.8 tennis racket=16.8 bottle=6.3 wine glass=7.3 cup=12.5 fork=3.8 knife=1.6 spoon=1.4 bowl=18.7 banana=9.1 apple=4.5 sandwich=21.9 orange=13.4 broccoli=10.8 carrot=5.5 hot dog=13.0 pizza=29.4 donut=18.0 cake=15.3 chair=7.4 couch=21.2 potted plant=6.1 bed=26.5 dining table=14.4 toilet=30.5 tv=33.2 laptop=32.2 mouse=19.3 remote=1.6 keyboard=21.0 cell phone=9.6 microwave=25.8 oven=15.1 toaster=0.0 sink=13.7 refrigerator=20.9 book=2.2 clock=22.3 vase=10.1 scissors=4.5 teddy bear=20.2 hair drier=0.0 toothbrush=2.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =16.0 [Epoch 19][Batch 99], Speed: 349.585 samples/sec, CrossEntropy=3.167, SmoothL1=1.453 [Epoch 19][Batch 199], Speed: 353.319 samples/sec, CrossEntropy=3.182, SmoothL1=1.457 [Epoch 19][Batch 299], Speed: 348.366 samples/sec, CrossEntropy=3.165, SmoothL1=1.440 [Epoch 19][Batch 399], Speed: 349.981 samples/sec, CrossEntropy=3.168, SmoothL1=1.440 [Epoch 19][Batch 499], Speed: 353.641 samples/sec, CrossEntropy=3.171, SmoothL1=1.442 [Epoch 19][Batch 599], Speed: 344.315 samples/sec, CrossEntropy=3.175, SmoothL1=1.439 [Epoch 19][Batch 699], Speed: 355.273 samples/sec, CrossEntropy=3.179, SmoothL1=1.440 [Epoch 19][Batch 799], Speed: 350.388 samples/sec, CrossEntropy=3.177, SmoothL1=1.439 [Epoch 19][Batch 899], Speed: 353.069 samples/sec, CrossEntropy=3.178, SmoothL1=1.435 [Epoch 19][Batch 999], Speed: 347.942 samples/sec, CrossEntropy=3.181, SmoothL1=1.438 [Epoch 19][Batch 1099], Speed: 355.584 samples/sec, CrossEntropy=3.180, SmoothL1=1.439 [Epoch 19][Batch 1199], Speed: 363.244 samples/sec, CrossEntropy=3.183, SmoothL1=1.436 [Epoch 19][Batch 1299], Speed: 347.856 samples/sec, CrossEntropy=3.178, SmoothL1=1.435 [Epoch 19][Batch 1399], Speed: 349.818 samples/sec, CrossEntropy=3.180, SmoothL1=1.439 [Epoch 19][Batch 1499], Speed: 365.916 samples/sec, CrossEntropy=3.180, SmoothL1=1.440 [Epoch 19][Batch 1599], Speed: 352.377 samples/sec, CrossEntropy=3.180, SmoothL1=1.438 [Epoch 19][Batch 1699], Speed: 355.987 samples/sec, CrossEntropy=3.180, SmoothL1=1.441 [Epoch 19][Batch 1799], Speed: 341.019 samples/sec, CrossEntropy=3.180, SmoothL1=1.439 [Epoch 19] Training cost: 335.621, CrossEntropy=3.181, SmoothL1=1.439 [Epoch 19] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.164 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.312 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.158 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.021 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.163 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.291 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.171 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.246 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.257 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.036 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.268 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.447 person=26.8 bicycle=9.0 car=13.9 motorcycle=19.8 airplane=35.5 bus=38.1 train=39.2 truck=14.8 boat=6.4 traffic light=3.6 fire hydrant=29.8 stop sign=36.9 parking meter=18.6 bench=8.1 bird=10.2 cat=43.1 dog=36.8 horse=27.9 sheep=22.4 cow=21.1 elephant=35.4 bear=41.2 zebra=36.9 giraffe=38.9 backpack=1.4 umbrella=13.6 handbag=1.0 tie=7.3 suitcase=9.0 frisbee=17.6 skis=6.5 snowboard=7.9 sports ball=12.4 kite=10.6 baseball bat=6.2 baseball glove=5.5 skateboard=15.2 surfboard=10.5 tennis racket=17.5 bottle=6.2 wine glass=7.4 cup=12.3 fork=4.6 knife=1.9 spoon=1.3 bowl=18.1 banana=8.2 apple=4.7 sandwich=20.1 orange=13.7 broccoli=9.4 carrot=5.1 hot dog=9.3 pizza=29.2 donut=16.7 cake=16.2 chair=7.2 couch=24.3 potted plant=6.1 bed=26.7 dining table=15.8 toilet=32.2 tv=30.6 laptop=31.7 mouse=19.2 remote=1.6 keyboard=21.4 cell phone=9.6 microwave=30.4 oven=13.9 toaster=0.0 sink=13.9 refrigerator=21.1 book=2.2 clock=21.9 vase=11.2 scissors=3.8 teddy bear=22.6 hair drier=0.0 toothbrush=1.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =16.4 [Epoch 20][Batch 99], Speed: 344.171 samples/sec, CrossEntropy=3.165, SmoothL1=1.406 [Epoch 20][Batch 199], Speed: 363.434 samples/sec, CrossEntropy=3.185, SmoothL1=1.417 [Epoch 20][Batch 299], Speed: 364.656 samples/sec, CrossEntropy=3.177, SmoothL1=1.421 [Epoch 20][Batch 399], Speed: 355.065 samples/sec, CrossEntropy=3.166, SmoothL1=1.413 [Epoch 20][Batch 499], Speed: 348.045 samples/sec, CrossEntropy=3.160, SmoothL1=1.416 [Epoch 20][Batch 599], Speed: 345.381 samples/sec, CrossEntropy=3.158, SmoothL1=1.418 [Epoch 20][Batch 699], Speed: 348.746 samples/sec, CrossEntropy=3.159, SmoothL1=1.420 [Epoch 20][Batch 799], Speed: 357.190 samples/sec, CrossEntropy=3.156, SmoothL1=1.419 [Epoch 20][Batch 899], Speed: 352.689 samples/sec, CrossEntropy=3.163, SmoothL1=1.424 [Epoch 20][Batch 999], Speed: 346.957 samples/sec, CrossEntropy=3.163, SmoothL1=1.421 [Epoch 20][Batch 1099], Speed: 358.685 samples/sec, CrossEntropy=3.160, SmoothL1=1.421 [Epoch 20][Batch 1199], Speed: 345.604 samples/sec, CrossEntropy=3.161, SmoothL1=1.422 [Epoch 20][Batch 1299], Speed: 360.718 samples/sec, CrossEntropy=3.164, SmoothL1=1.420 [Epoch 20][Batch 1399], Speed: 346.247 samples/sec, CrossEntropy=3.163, SmoothL1=1.419 [Epoch 20][Batch 1499], Speed: 356.383 samples/sec, CrossEntropy=3.166, SmoothL1=1.419 [Epoch 20][Batch 1599], Speed: 357.730 samples/sec, CrossEntropy=3.164, SmoothL1=1.419 [Epoch 20][Batch 1699], Speed: 345.012 samples/sec, CrossEntropy=3.162, SmoothL1=1.420 [Epoch 20][Batch 1799], Speed: 362.727 samples/sec, CrossEntropy=3.161, SmoothL1=1.419 [Epoch 20] Training cost: 335.791, CrossEntropy=3.161, SmoothL1=1.419 [Epoch 20] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.166 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.314 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.163 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.021 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.174 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.296 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.174 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.251 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.263 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.037 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.276 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.456 person=26.9 bicycle=8.7 car=13.5 motorcycle=19.2 airplane=34.0 bus=40.0 train=41.5 truck=15.3 boat=6.9 traffic light=3.8 fire hydrant=29.2 stop sign=34.2 parking meter=18.9 bench=8.6 bird=10.7 cat=44.5 dog=35.3 horse=27.9 sheep=22.6 cow=21.7 elephant=33.5 bear=43.0 zebra=37.7 giraffe=38.9 backpack=1.5 umbrella=13.4 handbag=1.0 tie=7.4 suitcase=8.4 frisbee=18.0 skis=6.2 snowboard=6.4 sports ball=12.6 kite=10.5 baseball bat=4.8 baseball glove=5.8 skateboard=16.4 surfboard=10.6 tennis racket=17.9 bottle=6.8 wine glass=7.7 cup=12.5 fork=4.1 knife=1.6 spoon=1.3 bowl=19.1 banana=9.5 apple=6.0 sandwich=22.9 orange=14.4 broccoli=10.6 carrot=5.3 hot dog=13.0 pizza=28.8 donut=18.7 cake=16.0 chair=7.3 couch=23.0 potted plant=6.5 bed=28.5 dining table=15.6 toilet=33.8 tv=32.2 laptop=32.0 mouse=20.1 remote=2.4 keyboard=19.3 cell phone=10.0 microwave=25.9 oven=15.5 toaster=0.0 sink=13.5 refrigerator=23.2 book=2.5 clock=23.8 vase=10.2 scissors=4.5 teddy bear=22.6 hair drier=0.0 toothbrush=1.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =16.6 [Epoch 21][Batch 99], Speed: 346.153 samples/sec, CrossEntropy=3.143, SmoothL1=1.434 [Epoch 21][Batch 199], Speed: 353.942 samples/sec, CrossEntropy=3.154, SmoothL1=1.418 [Epoch 21][Batch 299], Speed: 345.683 samples/sec, CrossEntropy=3.152, SmoothL1=1.416 [Epoch 21][Batch 399], Speed: 360.062 samples/sec, CrossEntropy=3.144, SmoothL1=1.415 [Epoch 21][Batch 499], Speed: 360.707 samples/sec, CrossEntropy=3.149, SmoothL1=1.413 [Epoch 21][Batch 599], Speed: 366.273 samples/sec, CrossEntropy=3.152, SmoothL1=1.415 [Epoch 21][Batch 699], Speed: 344.252 samples/sec, CrossEntropy=3.152, SmoothL1=1.417 [Epoch 21][Batch 799], Speed: 352.761 samples/sec, CrossEntropy=3.154, SmoothL1=1.415 [Epoch 21][Batch 899], Speed: 359.283 samples/sec, CrossEntropy=3.153, SmoothL1=1.413 [Epoch 21][Batch 999], Speed: 349.080 samples/sec, CrossEntropy=3.150, SmoothL1=1.412 [Epoch 21][Batch 1099], Speed: 348.971 samples/sec, CrossEntropy=3.153, SmoothL1=1.413 [Epoch 21][Batch 1199], Speed: 355.094 samples/sec, CrossEntropy=3.153, SmoothL1=1.417 [Epoch 21][Batch 1299], Speed: 348.625 samples/sec, CrossEntropy=3.153, SmoothL1=1.417 [Epoch 21][Batch 1399], Speed: 363.148 samples/sec, CrossEntropy=3.156, SmoothL1=1.419 [Epoch 21][Batch 1499], Speed: 345.030 samples/sec, CrossEntropy=3.157, SmoothL1=1.417 [Epoch 21][Batch 1599], Speed: 346.354 samples/sec, CrossEntropy=3.151, SmoothL1=1.416 [Epoch 21][Batch 1699], Speed: 352.444 samples/sec, CrossEntropy=3.150, SmoothL1=1.415 [Epoch 21][Batch 1799], Speed: 348.113 samples/sec, CrossEntropy=3.151, SmoothL1=1.415 [Epoch 21] Training cost: 335.530, CrossEntropy=3.151, SmoothL1=1.415 [Epoch 21] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.168 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.320 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.166 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.021 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.169 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.301 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.176 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.253 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.265 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.039 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.275 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.467 person=26.3 bicycle=10.1 car=14.0 motorcycle=19.5 airplane=32.7 bus=40.3 train=40.9 truck=15.3 boat=7.0 traffic light=3.7 fire hydrant=30.8 stop sign=36.0 parking meter=18.4 bench=9.0 bird=10.8 cat=43.9 dog=34.7 horse=27.5 sheep=23.7 cow=20.9 elephant=35.1 bear=42.5 zebra=37.5 giraffe=39.4 backpack=1.4 umbrella=14.3 handbag=1.1 tie=6.1 suitcase=9.6 frisbee=18.2 skis=6.0 snowboard=7.4 sports ball=13.1 kite=10.8 baseball bat=7.3 baseball glove=6.2 skateboard=15.8 surfboard=11.4 tennis racket=16.2 bottle=6.7 wine glass=9.0 cup=13.2 fork=4.6 knife=1.8 spoon=1.0 bowl=18.8 banana=9.2 apple=5.1 sandwich=23.1 orange=14.1 broccoli=10.1 carrot=6.0 hot dog=12.6 pizza=30.9 donut=18.7 cake=15.2 chair=7.3 couch=24.3 potted plant=6.4 bed=27.4 dining table=15.6 toilet=30.9 tv=33.5 laptop=33.3 mouse=20.9 remote=2.0 keyboard=22.3 cell phone=10.5 microwave=26.0 oven=16.5 toaster=0.0 sink=14.0 refrigerator=21.8 book=2.3 clock=22.8 vase=10.5 scissors=8.6 teddy bear=23.4 hair drier=0.0 toothbrush=1.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =16.8 [Epoch 22][Batch 99], Speed: 358.802 samples/sec, CrossEntropy=3.071, SmoothL1=1.381 [Epoch 22][Batch 199], Speed: 359.107 samples/sec, CrossEntropy=3.097, SmoothL1=1.393 [Epoch 22][Batch 299], Speed: 351.727 samples/sec, CrossEntropy=3.096, SmoothL1=1.390 [Epoch 22][Batch 399], Speed: 350.121 samples/sec, CrossEntropy=3.096, SmoothL1=1.394 [Epoch 22][Batch 499], Speed: 344.207 samples/sec, CrossEntropy=3.101, SmoothL1=1.399 [Epoch 22][Batch 599], Speed: 356.498 samples/sec, CrossEntropy=3.106, SmoothL1=1.405 [Epoch 22][Batch 699], Speed: 352.854 samples/sec, CrossEntropy=3.118, SmoothL1=1.413 [Epoch 22][Batch 799], Speed: 354.851 samples/sec, CrossEntropy=3.115, SmoothL1=1.406 [Epoch 22][Batch 899], Speed: 358.952 samples/sec, CrossEntropy=3.118, SmoothL1=1.409 [Epoch 22][Batch 999], Speed: 359.377 samples/sec, CrossEntropy=3.118, SmoothL1=1.407 [Epoch 22][Batch 1099], Speed: 350.530 samples/sec, CrossEntropy=3.119, SmoothL1=1.406 [Epoch 22][Batch 1199], Speed: 344.498 samples/sec, CrossEntropy=3.119, SmoothL1=1.405 [Epoch 22][Batch 1299], Speed: 357.966 samples/sec, CrossEntropy=3.124, SmoothL1=1.406 [Epoch 22][Batch 1399], Speed: 362.782 samples/sec, CrossEntropy=3.125, SmoothL1=1.406 [Epoch 22][Batch 1499], Speed: 351.602 samples/sec, CrossEntropy=3.123, SmoothL1=1.405 [Epoch 22][Batch 1599], Speed: 362.342 samples/sec, CrossEntropy=3.120, SmoothL1=1.404 [Epoch 22][Batch 1699], Speed: 356.532 samples/sec, CrossEntropy=3.120, SmoothL1=1.405 [Epoch 22][Batch 1799], Speed: 353.074 samples/sec, CrossEntropy=3.120, SmoothL1=1.405 [Epoch 22] Training cost: 334.090, CrossEntropy=3.119, SmoothL1=1.404 [Epoch 22] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.170 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.322 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.168 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.023 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.176 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.305 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.177 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.254 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.265 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.039 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.276 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.465 person=26.3 bicycle=9.9 car=14.4 motorcycle=19.5 airplane=35.3 bus=41.8 train=40.5 truck=15.0 boat=6.9 traffic light=3.7 fire hydrant=31.0 stop sign=36.8 parking meter=18.2 bench=8.8 bird=11.2 cat=45.3 dog=35.7 horse=29.9 sheep=21.9 cow=22.6 elephant=35.1 bear=41.8 zebra=38.2 giraffe=40.6 backpack=1.6 umbrella=15.4 handbag=1.1 tie=8.1 suitcase=10.0 frisbee=18.2 skis=5.6 snowboard=6.6 sports ball=12.8 kite=11.2 baseball bat=5.7 baseball glove=6.3 skateboard=16.0 surfboard=10.3 tennis racket=16.3 bottle=6.7 wine glass=7.7 cup=13.1 fork=4.0 knife=1.7 spoon=1.3 bowl=19.8 banana=10.2 apple=5.0 sandwich=21.5 orange=15.9 broccoli=10.9 carrot=5.5 hot dog=10.7 pizza=30.5 donut=19.1 cake=15.0 chair=7.9 couch=24.7 potted plant=6.8 bed=26.4 dining table=17.2 toilet=34.9 tv=33.3 laptop=33.2 mouse=21.0 remote=2.8 keyboard=24.8 cell phone=10.9 microwave=26.3 oven=15.4 toaster=0.0 sink=14.1 refrigerator=22.3 book=2.2 clock=23.9 vase=11.6 scissors=6.2 teddy bear=21.2 hair drier=0.0 toothbrush=2.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =17.0 [Epoch 23][Batch 99], Speed: 355.867 samples/sec, CrossEntropy=3.113, SmoothL1=1.418 [Epoch 23][Batch 199], Speed: 360.972 samples/sec, CrossEntropy=3.098, SmoothL1=1.413 [Epoch 23][Batch 299], Speed: 345.682 samples/sec, CrossEntropy=3.099, SmoothL1=1.404 [Epoch 23][Batch 399], Speed: 353.195 samples/sec, CrossEntropy=3.102, SmoothL1=1.403 [Epoch 23][Batch 499], Speed: 348.326 samples/sec, CrossEntropy=3.105, SmoothL1=1.398 [Epoch 23][Batch 599], Speed: 360.166 samples/sec, CrossEntropy=3.115, SmoothL1=1.402 [Epoch 23][Batch 699], Speed: 344.144 samples/sec, CrossEntropy=3.119, SmoothL1=1.406 [Epoch 23][Batch 799], Speed: 345.221 samples/sec, CrossEntropy=3.118, SmoothL1=1.405 [Epoch 23][Batch 899], Speed: 359.839 samples/sec, CrossEntropy=3.122, SmoothL1=1.407 [Epoch 23][Batch 999], Speed: 352.150 samples/sec, CrossEntropy=3.126, SmoothL1=1.408 [Epoch 23][Batch 1099], Speed: 354.867 samples/sec, CrossEntropy=3.127, SmoothL1=1.410 [Epoch 23][Batch 1199], Speed: 354.997 samples/sec, CrossEntropy=3.124, SmoothL1=1.409 [Epoch 23][Batch 1299], Speed: 348.949 samples/sec, CrossEntropy=3.123, SmoothL1=1.408 [Epoch 23][Batch 1399], Speed: 342.855 samples/sec, CrossEntropy=3.120, SmoothL1=1.408 [Epoch 23][Batch 1499], Speed: 343.445 samples/sec, CrossEntropy=3.119, SmoothL1=1.409 [Epoch 23][Batch 1599], Speed: 358.595 samples/sec, CrossEntropy=3.113, SmoothL1=1.407 [Epoch 23][Batch 1699], Speed: 349.152 samples/sec, CrossEntropy=3.111, SmoothL1=1.406 [Epoch 23][Batch 1799], Speed: 347.121 samples/sec, CrossEntropy=3.111, SmoothL1=1.406 [Epoch 23] Training cost: 334.742, CrossEntropy=3.112, SmoothL1=1.408 [Epoch 23] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.173 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.325 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.170 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.022 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.176 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.307 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.178 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.255 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.266 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.039 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.278 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.464 person=27.5 bicycle=9.4 car=14.3 motorcycle=19.3 airplane=35.5 bus=39.7 train=40.6 truck=13.8 boat=6.7 traffic light=4.0 fire hydrant=31.8 stop sign=36.3 parking meter=19.4 bench=8.5 bird=10.9 cat=43.4 dog=36.9 horse=28.6 sheep=23.0 cow=22.8 elephant=35.7 bear=43.8 zebra=38.8 giraffe=41.3 backpack=1.8 umbrella=14.5 handbag=1.3 tie=7.6 suitcase=10.6 frisbee=18.0 skis=6.6 snowboard=6.8 sports ball=12.8 kite=10.8 baseball bat=7.3 baseball glove=6.3 skateboard=16.8 surfboard=11.4 tennis racket=18.2 bottle=7.0 wine glass=8.0 cup=13.3 fork=5.0 knife=1.7 spoon=1.6 bowl=19.5 banana=10.1 apple=5.7 sandwich=22.1 orange=16.1 broccoli=9.7 carrot=5.4 hot dog=15.4 pizza=30.0 donut=18.5 cake=16.8 chair=7.9 couch=23.8 potted plant=6.6 bed=27.6 dining table=16.7 toilet=34.3 tv=33.7 laptop=34.7 mouse=19.1 remote=2.7 keyboard=23.1 cell phone=10.7 microwave=28.2 oven=17.2 toaster=0.0 sink=13.4 refrigerator=23.3 book=2.5 clock=23.7 vase=11.2 scissors=5.9 teddy bear=23.4 hair drier=0.0 toothbrush=2.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =17.3 [Epoch 24][Batch 99], Speed: 350.224 samples/sec, CrossEntropy=3.070, SmoothL1=1.379 [Epoch 24][Batch 199], Speed: 349.615 samples/sec, CrossEntropy=3.075, SmoothL1=1.386 [Epoch 24][Batch 299], Speed: 350.896 samples/sec, CrossEntropy=3.088, SmoothL1=1.392 [Epoch 24][Batch 399], Speed: 356.015 samples/sec, CrossEntropy=3.084, SmoothL1=1.383 [Epoch 24][Batch 499], Speed: 352.159 samples/sec, CrossEntropy=3.087, SmoothL1=1.389 [Epoch 24][Batch 599], Speed: 344.650 samples/sec, CrossEntropy=3.088, SmoothL1=1.387 [Epoch 24][Batch 699], Speed: 363.369 samples/sec, CrossEntropy=3.090, SmoothL1=1.391 [Epoch 24][Batch 799], Speed: 358.985 samples/sec, CrossEntropy=3.088, SmoothL1=1.391 [Epoch 24][Batch 899], Speed: 350.654 samples/sec, CrossEntropy=3.091, SmoothL1=1.392 [Epoch 24][Batch 999], Speed: 349.533 samples/sec, CrossEntropy=3.090, SmoothL1=1.393 [Epoch 24][Batch 1099], Speed: 360.609 samples/sec, CrossEntropy=3.093, SmoothL1=1.394 [Epoch 24][Batch 1199], Speed: 338.962 samples/sec, CrossEntropy=3.091, SmoothL1=1.395 [Epoch 24][Batch 1299], Speed: 364.333 samples/sec, CrossEntropy=3.092, SmoothL1=1.394 [Epoch 24][Batch 1399], Speed: 352.777 samples/sec, CrossEntropy=3.091, SmoothL1=1.393 [Epoch 24][Batch 1499], Speed: 359.433 samples/sec, CrossEntropy=3.091, SmoothL1=1.392 [Epoch 24][Batch 1599], Speed: 345.556 samples/sec, CrossEntropy=3.090, SmoothL1=1.392 [Epoch 24][Batch 1699], Speed: 361.194 samples/sec, CrossEntropy=3.088, SmoothL1=1.391 [Epoch 24][Batch 1799], Speed: 356.229 samples/sec, CrossEntropy=3.089, SmoothL1=1.392 [Epoch 24] Training cost: 335.448, CrossEntropy=3.089, SmoothL1=1.392 [Epoch 24] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.173 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.325 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.170 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.022 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.177 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.310 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.179 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.256 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.268 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.039 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.278 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.471 person=27.0 bicycle=10.1 car=14.4 motorcycle=20.5 airplane=35.7 bus=40.7 train=41.0 truck=15.4 boat=6.9 traffic light=4.2 fire hydrant=32.0 stop sign=38.5 parking meter=20.4 bench=9.3 bird=11.2 cat=45.9 dog=36.7 horse=29.3 sheep=22.7 cow=22.4 elephant=35.3 bear=45.1 zebra=37.8 giraffe=41.1 backpack=2.1 umbrella=15.5 handbag=1.3 tie=7.1 suitcase=10.5 frisbee=17.3 skis=5.9 snowboard=7.2 sports ball=13.2 kite=12.0 baseball bat=6.3 baseball glove=6.4 skateboard=16.0 surfboard=10.6 tennis racket=17.7 bottle=7.1 wine glass=8.1 cup=13.1 fork=4.5 knife=2.0 spoon=1.3 bowl=18.8 banana=9.2 apple=5.7 sandwich=24.1 orange=14.7 broccoli=10.5 carrot=5.5 hot dog=13.6 pizza=29.8 donut=19.8 cake=16.3 chair=7.3 couch=24.8 potted plant=6.6 bed=27.0 dining table=17.3 toilet=34.4 tv=33.4 laptop=32.4 mouse=19.7 remote=3.1 keyboard=23.5 cell phone=10.9 microwave=25.8 oven=16.8 toaster=0.0 sink=13.1 refrigerator=24.3 book=2.2 clock=23.5 vase=10.6 scissors=7.7 teddy bear=22.4 hair drier=0.0 toothbrush=2.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =17.3 [Epoch 25][Batch 99], Speed: 347.384 samples/sec, CrossEntropy=3.076, SmoothL1=1.407 [Epoch 25][Batch 199], Speed: 352.899 samples/sec, CrossEntropy=3.076, SmoothL1=1.399 [Epoch 25][Batch 299], Speed: 356.697 samples/sec, CrossEntropy=3.060, SmoothL1=1.385 [Epoch 25][Batch 399], Speed: 345.679 samples/sec, CrossEntropy=3.061, SmoothL1=1.387 [Epoch 25][Batch 499], Speed: 349.283 samples/sec, CrossEntropy=3.074, SmoothL1=1.389 [Epoch 25][Batch 599], Speed: 353.868 samples/sec, CrossEntropy=3.067, SmoothL1=1.388 [Epoch 25][Batch 699], Speed: 348.794 samples/sec, CrossEntropy=3.067, SmoothL1=1.384 [Epoch 25][Batch 799], Speed: 354.049 samples/sec, CrossEntropy=3.066, SmoothL1=1.382 [Epoch 25][Batch 899], Speed: 349.574 samples/sec, CrossEntropy=3.067, SmoothL1=1.386 [Epoch 25][Batch 999], Speed: 345.753 samples/sec, CrossEntropy=3.066, SmoothL1=1.384 [Epoch 25][Batch 1099], Speed: 356.636 samples/sec, CrossEntropy=3.064, SmoothL1=1.380 [Epoch 25][Batch 1199], Speed: 348.331 samples/sec, CrossEntropy=3.064, SmoothL1=1.377 [Epoch 25][Batch 1299], Speed: 358.476 samples/sec, CrossEntropy=3.064, SmoothL1=1.377 [Epoch 25][Batch 1399], Speed: 354.359 samples/sec, CrossEntropy=3.064, SmoothL1=1.375 [Epoch 25][Batch 1499], Speed: 353.892 samples/sec, CrossEntropy=3.063, SmoothL1=1.376 [Epoch 25][Batch 1599], Speed: 345.350 samples/sec, CrossEntropy=3.063, SmoothL1=1.374 [Epoch 25][Batch 1699], Speed: 351.814 samples/sec, CrossEntropy=3.061, SmoothL1=1.376 [Epoch 25][Batch 1799], Speed: 357.986 samples/sec, CrossEntropy=3.059, SmoothL1=1.377 [Epoch 25] Training cost: 335.231, CrossEntropy=3.057, SmoothL1=1.374 [Epoch 25] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.176 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.330 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.174 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.022 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.182 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.314 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.180 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.260 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.272 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.039 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.289 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.471 person=27.0 bicycle=9.5 car=14.2 motorcycle=20.5 airplane=33.2 bus=40.6 train=41.2 truck=15.1 boat=7.1 traffic light=4.0 fire hydrant=31.3 stop sign=37.6 parking meter=20.4 bench=9.3 bird=10.8 cat=44.6 dog=35.4 horse=30.0 sheep=23.5 cow=22.0 elephant=36.0 bear=46.0 zebra=39.6 giraffe=41.1 backpack=1.8 umbrella=15.4 handbag=1.3 tie=7.9 suitcase=11.0 frisbee=18.3 skis=6.8 snowboard=6.8 sports ball=13.1 kite=12.8 baseball bat=5.2 baseball glove=6.1 skateboard=16.4 surfboard=11.8 tennis racket=18.4 bottle=7.1 wine glass=8.3 cup=13.7 fork=5.2 knife=1.9 spoon=1.8 bowl=20.5 banana=9.1 apple=5.9 sandwich=26.8 orange=17.2 broccoli=10.7 carrot=6.3 hot dog=16.6 pizza=29.9 donut=18.7 cake=16.3 chair=7.9 couch=25.9 potted plant=6.8 bed=28.5 dining table=17.1 toilet=34.2 tv=35.2 laptop=32.7 mouse=19.9 remote=2.9 keyboard=22.7 cell phone=10.3 microwave=24.2 oven=16.8 toaster=0.0 sink=13.7 refrigerator=24.6 book=2.5 clock=24.1 vase=11.6 scissors=9.0 teddy bear=23.3 hair drier=0.0 toothbrush=1.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =17.6 [Epoch 26][Batch 99], Speed: 356.659 samples/sec, CrossEntropy=3.048, SmoothL1=1.370 [Epoch 26][Batch 199], Speed: 357.038 samples/sec, CrossEntropy=3.079, SmoothL1=1.376 [Epoch 26][Batch 299], Speed: 347.122 samples/sec, CrossEntropy=3.084, SmoothL1=1.394 [Epoch 26][Batch 399], Speed: 345.452 samples/sec, CrossEntropy=3.069, SmoothL1=1.385 [Epoch 26][Batch 499], Speed: 341.195 samples/sec, CrossEntropy=3.063, SmoothL1=1.379 [Epoch 26][Batch 599], Speed: 362.886 samples/sec, CrossEntropy=3.061, SmoothL1=1.374 [Epoch 26][Batch 699], Speed: 357.704 samples/sec, CrossEntropy=3.064, SmoothL1=1.377 [Epoch 26][Batch 799], Speed: 361.741 samples/sec, CrossEntropy=3.066, SmoothL1=1.376 [Epoch 26][Batch 899], Speed: 350.727 samples/sec, CrossEntropy=3.067, SmoothL1=1.374 [Epoch 26][Batch 999], Speed: 362.596 samples/sec, CrossEntropy=3.057, SmoothL1=1.373 [Epoch 26][Batch 1099], Speed: 353.066 samples/sec, CrossEntropy=3.061, SmoothL1=1.378 [Epoch 26][Batch 1199], Speed: 350.813 samples/sec, CrossEntropy=3.066, SmoothL1=1.382 [Epoch 26][Batch 1299], Speed: 362.338 samples/sec, CrossEntropy=3.069, SmoothL1=1.381 [Epoch 26][Batch 1399], Speed: 359.503 samples/sec, CrossEntropy=3.064, SmoothL1=1.383 [Epoch 26][Batch 1499], Speed: 356.413 samples/sec, CrossEntropy=3.062, SmoothL1=1.383 [Epoch 26][Batch 1599], Speed: 351.209 samples/sec, CrossEntropy=3.060, SmoothL1=1.382 [Epoch 26][Batch 1699], Speed: 350.035 samples/sec, CrossEntropy=3.060, SmoothL1=1.384 [Epoch 26][Batch 1799], Speed: 351.563 samples/sec, CrossEntropy=3.060, SmoothL1=1.384 [Epoch 26] Training cost: 335.864, CrossEntropy=3.060, SmoothL1=1.384 [Epoch 26] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.175 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.328 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.171 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.023 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.181 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.311 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.179 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.256 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.267 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.281 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.464 person=27.3 bicycle=10.2 car=14.2 motorcycle=20.0 airplane=34.0 bus=39.3 train=40.8 truck=15.4 boat=7.0 traffic light=4.2 fire hydrant=32.4 stop sign=36.3 parking meter=20.9 bench=9.0 bird=11.4 cat=45.0 dog=37.7 horse=30.0 sheep=23.4 cow=23.2 elephant=34.3 bear=43.7 zebra=38.9 giraffe=40.9 backpack=1.9 umbrella=15.8 handbag=1.3 tie=7.9 suitcase=10.3 frisbee=19.3 skis=5.7 snowboard=7.5 sports ball=12.9 kite=11.7 baseball bat=6.0 baseball glove=6.2 skateboard=15.6 surfboard=10.9 tennis racket=17.7 bottle=7.2 wine glass=8.1 cup=13.6 fork=5.6 knife=2.1 spoon=2.1 bowl=19.3 banana=9.1 apple=4.4 sandwich=23.5 orange=15.4 broccoli=11.8 carrot=6.4 hot dog=14.9 pizza=29.7 donut=18.4 cake=17.2 chair=8.0 couch=25.2 potted plant=6.6 bed=27.6 dining table=16.8 toilet=33.6 tv=32.6 laptop=33.9 mouse=22.2 remote=3.1 keyboard=24.6 cell phone=11.9 microwave=29.9 oven=16.5 toaster=0.0 sink=13.8 refrigerator=23.1 book=2.1 clock=23.8 vase=11.4 scissors=6.3 teddy bear=23.8 hair drier=0.0 toothbrush=0.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =17.5 [Epoch 27][Batch 99], Speed: 343.344 samples/sec, CrossEntropy=3.059, SmoothL1=1.366 [Epoch 27][Batch 199], Speed: 366.195 samples/sec, CrossEntropy=3.048, SmoothL1=1.357 [Epoch 27][Batch 299], Speed: 356.646 samples/sec, CrossEntropy=3.039, SmoothL1=1.371 [Epoch 27][Batch 399], Speed: 357.752 samples/sec, CrossEntropy=3.026, SmoothL1=1.371 [Epoch 27][Batch 499], Speed: 349.900 samples/sec, CrossEntropy=3.030, SmoothL1=1.369 [Epoch 27][Batch 599], Speed: 354.910 samples/sec, CrossEntropy=3.032, SmoothL1=1.368 [Epoch 27][Batch 699], Speed: 347.044 samples/sec, CrossEntropy=3.036, SmoothL1=1.368 [Epoch 27][Batch 799], Speed: 356.495 samples/sec, CrossEntropy=3.036, SmoothL1=1.368 [Epoch 27][Batch 899], Speed: 354.115 samples/sec, CrossEntropy=3.033, SmoothL1=1.367 [Epoch 27][Batch 999], Speed: 361.863 samples/sec, CrossEntropy=3.031, SmoothL1=1.363 [Epoch 27][Batch 1099], Speed: 357.687 samples/sec, CrossEntropy=3.032, SmoothL1=1.364 [Epoch 27][Batch 1199], Speed: 356.534 samples/sec, CrossEntropy=3.036, SmoothL1=1.369 [Epoch 27][Batch 1299], Speed: 351.820 samples/sec, CrossEntropy=3.037, SmoothL1=1.367 [Epoch 27][Batch 1399], Speed: 361.158 samples/sec, CrossEntropy=3.040, SmoothL1=1.368 [Epoch 27][Batch 1499], Speed: 354.128 samples/sec, CrossEntropy=3.040, SmoothL1=1.369 [Epoch 27][Batch 1599], Speed: 357.471 samples/sec, CrossEntropy=3.040, SmoothL1=1.370 [Epoch 27][Batch 1699], Speed: 358.795 samples/sec, CrossEntropy=3.039, SmoothL1=1.368 [Epoch 27][Batch 1799], Speed: 354.620 samples/sec, CrossEntropy=3.038, SmoothL1=1.367 [Epoch 27] Training cost: 334.493, CrossEntropy=3.038, SmoothL1=1.367 [Epoch 27] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.178 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.334 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.177 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.023 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.187 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.315 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.183 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.261 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.273 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.042 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.293 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.472 person=27.8 bicycle=10.8 car=14.3 motorcycle=20.4 airplane=36.2 bus=39.4 train=39.1 truck=14.5 boat=7.8 traffic light=4.7 fire hydrant=32.2 stop sign=36.6 parking meter=21.3 bench=9.6 bird=11.2 cat=47.0 dog=37.3 horse=29.5 sheep=23.6 cow=23.0 elephant=35.1 bear=44.6 zebra=37.9 giraffe=40.6 backpack=2.0 umbrella=15.9 handbag=1.3 tie=7.4 suitcase=10.7 frisbee=20.7 skis=6.4 snowboard=7.1 sports ball=13.8 kite=13.0 baseball bat=7.3 baseball glove=6.9 skateboard=17.0 surfboard=12.8 tennis racket=18.3 bottle=7.3 wine glass=8.6 cup=13.6 fork=5.7 knife=2.4 spoon=1.9 bowl=19.4 banana=9.5 apple=5.9 sandwich=24.1 orange=12.8 broccoli=11.1 carrot=5.3 hot dog=15.7 pizza=31.3 donut=19.8 cake=17.0 chair=8.2 couch=27.1 potted plant=7.1 bed=27.8 dining table=17.1 toilet=33.6 tv=35.0 laptop=35.5 mouse=23.1 remote=3.0 keyboard=24.1 cell phone=10.7 microwave=27.5 oven=16.5 toaster=0.0 sink=15.7 refrigerator=24.7 book=2.5 clock=24.0 vase=10.7 scissors=8.0 teddy bear=24.3 hair drier=0.0 toothbrush=2.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =17.8 [Epoch 28][Batch 99], Speed: 351.579 samples/sec, CrossEntropy=3.014, SmoothL1=1.355 [Epoch 28][Batch 199], Speed: 353.904 samples/sec, CrossEntropy=3.003, SmoothL1=1.376 [Epoch 28][Batch 299], Speed: 352.971 samples/sec, CrossEntropy=3.006, SmoothL1=1.372 [Epoch 28][Batch 399], Speed: 364.852 samples/sec, CrossEntropy=3.022, SmoothL1=1.366 [Epoch 28][Batch 499], Speed: 358.716 samples/sec, CrossEntropy=3.030, SmoothL1=1.378 [Epoch 28][Batch 599], Speed: 361.380 samples/sec, CrossEntropy=3.037, SmoothL1=1.380 [Epoch 28][Batch 699], Speed: 352.444 samples/sec, CrossEntropy=3.038, SmoothL1=1.374 [Epoch 28][Batch 799], Speed: 347.009 samples/sec, CrossEntropy=3.038, SmoothL1=1.373 [Epoch 28][Batch 899], Speed: 358.953 samples/sec, CrossEntropy=3.038, SmoothL1=1.374 [Epoch 28][Batch 999], Speed: 354.529 samples/sec, CrossEntropy=3.036, SmoothL1=1.375 [Epoch 28][Batch 1099], Speed: 353.009 samples/sec, CrossEntropy=3.038, SmoothL1=1.375 [Epoch 28][Batch 1199], Speed: 347.116 samples/sec, CrossEntropy=3.035, SmoothL1=1.374 [Epoch 28][Batch 1299], Speed: 357.663 samples/sec, CrossEntropy=3.038, SmoothL1=1.373 [Epoch 28][Batch 1399], Speed: 354.269 samples/sec, CrossEntropy=3.040, SmoothL1=1.374 [Epoch 28][Batch 1499], Speed: 350.560 samples/sec, CrossEntropy=3.039, SmoothL1=1.372 [Epoch 28][Batch 1599], Speed: 352.149 samples/sec, CrossEntropy=3.037, SmoothL1=1.373 [Epoch 28][Batch 1699], Speed: 346.279 samples/sec, CrossEntropy=3.034, SmoothL1=1.372 [Epoch 28][Batch 1799], Speed: 361.989 samples/sec, CrossEntropy=3.031, SmoothL1=1.370 [Epoch 28] Training cost: 335.047, CrossEntropy=3.031, SmoothL1=1.369 [Epoch 28] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.178 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.333 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.175 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.023 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.186 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.316 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.181 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.258 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.269 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.285 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.467 person=28.3 bicycle=9.6 car=14.3 motorcycle=18.7 airplane=34.4 bus=38.4 train=40.6 truck=15.1 boat=7.2 traffic light=4.5 fire hydrant=31.5 stop sign=38.6 parking meter=19.9 bench=9.3 bird=12.1 cat=45.7 dog=38.0 horse=29.4 sheep=23.6 cow=23.4 elephant=35.4 bear=48.7 zebra=36.8 giraffe=40.0 backpack=1.8 umbrella=16.0 handbag=1.6 tie=8.6 suitcase=9.7 frisbee=19.5 skis=6.1 snowboard=6.6 sports ball=13.6 kite=10.8 baseball bat=6.3 baseball glove=8.1 skateboard=18.1 surfboard=11.5 tennis racket=18.2 bottle=7.8 wine glass=8.2 cup=13.3 fork=4.7 knife=2.4 spoon=2.1 bowl=20.1 banana=10.0 apple=6.1 sandwich=22.2 orange=15.2 broccoli=9.8 carrot=6.4 hot dog=12.7 pizza=31.6 donut=20.1 cake=16.7 chair=8.5 couch=26.9 potted plant=6.9 bed=28.7 dining table=16.3 toilet=35.2 tv=34.1 laptop=33.9 mouse=21.7 remote=3.3 keyboard=23.0 cell phone=11.4 microwave=28.2 oven=17.7 toaster=0.0 sink=16.5 refrigerator=25.3 book=2.6 clock=23.7 vase=11.8 scissors=9.5 teddy bear=24.1 hair drier=0.0 toothbrush=1.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =17.8 [Epoch 29][Batch 99], Speed: 360.051 samples/sec, CrossEntropy=3.006, SmoothL1=1.325 [Epoch 29][Batch 199], Speed: 356.238 samples/sec, CrossEntropy=2.998, SmoothL1=1.334 [Epoch 29][Batch 299], Speed: 366.902 samples/sec, CrossEntropy=3.001, SmoothL1=1.339 [Epoch 29][Batch 399], Speed: 344.759 samples/sec, CrossEntropy=3.001, SmoothL1=1.345 [Epoch 29][Batch 499], Speed: 347.140 samples/sec, CrossEntropy=2.998, SmoothL1=1.346 [Epoch 29][Batch 599], Speed: 350.026 samples/sec, CrossEntropy=3.005, SmoothL1=1.351 [Epoch 29][Batch 699], Speed: 356.548 samples/sec, CrossEntropy=3.006, SmoothL1=1.346 [Epoch 29][Batch 799], Speed: 357.542 samples/sec, CrossEntropy=3.008, SmoothL1=1.346 [Epoch 29][Batch 899], Speed: 349.063 samples/sec, CrossEntropy=3.012, SmoothL1=1.346 [Epoch 29][Batch 999], Speed: 353.566 samples/sec, CrossEntropy=3.013, SmoothL1=1.347 [Epoch 29][Batch 1099], Speed: 360.202 samples/sec, CrossEntropy=3.011, SmoothL1=1.347 [Epoch 29][Batch 1199], Speed: 347.603 samples/sec, CrossEntropy=3.013, SmoothL1=1.350 [Epoch 29][Batch 1299], Speed: 348.002 samples/sec, CrossEntropy=3.013, SmoothL1=1.350 [Epoch 29][Batch 1399], Speed: 354.777 samples/sec, CrossEntropy=3.015, SmoothL1=1.351 [Epoch 29][Batch 1499], Speed: 360.303 samples/sec, CrossEntropy=3.014, SmoothL1=1.351 [Epoch 29][Batch 1599], Speed: 345.794 samples/sec, CrossEntropy=3.012, SmoothL1=1.347 [Epoch 29][Batch 1699], Speed: 362.957 samples/sec, CrossEntropy=3.015, SmoothL1=1.348 [Epoch 29][Batch 1799], Speed: 345.704 samples/sec, CrossEntropy=3.011, SmoothL1=1.348 [Epoch 29] Training cost: 335.005, CrossEntropy=3.010, SmoothL1=1.348 [Epoch 29] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.181 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.337 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.182 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.025 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.185 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.325 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.185 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.265 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.277 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.044 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.294 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.485 person=27.7 bicycle=11.0 car=14.7 motorcycle=20.4 airplane=34.7 bus=40.4 train=41.5 truck=15.1 boat=7.4 traffic light=4.6 fire hydrant=32.7 stop sign=37.7 parking meter=17.8 bench=9.2 bird=11.0 cat=47.5 dog=37.1 horse=29.6 sheep=25.0 cow=24.0 elephant=37.4 bear=48.2 zebra=37.8 giraffe=40.6 backpack=1.8 umbrella=16.1 handbag=1.4 tie=8.7 suitcase=11.3 frisbee=20.2 skis=7.4 snowboard=7.2 sports ball=14.1 kite=13.0 baseball bat=7.4 baseball glove=6.5 skateboard=17.8 surfboard=11.8 tennis racket=19.0 bottle=7.4 wine glass=8.9 cup=13.5 fork=5.3 knife=2.4 spoon=2.3 bowl=21.1 banana=10.8 apple=7.3 sandwich=23.9 orange=15.8 broccoli=11.4 carrot=5.9 hot dog=15.8 pizza=32.0 donut=18.9 cake=17.3 chair=8.6 couch=26.2 potted plant=7.3 bed=28.2 dining table=16.7 toilet=35.6 tv=34.1 laptop=35.4 mouse=21.9 remote=3.2 keyboard=23.8 cell phone=12.0 microwave=27.1 oven=18.6 toaster=0.0 sink=15.1 refrigerator=26.1 book=2.5 clock=24.1 vase=11.3 scissors=11.8 teddy bear=24.1 hair drier=0.0 toothbrush=1.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =18.1 [Epoch 30][Batch 99], Speed: 360.331 samples/sec, CrossEntropy=3.000, SmoothL1=1.364 [Epoch 30][Batch 199], Speed: 364.105 samples/sec, CrossEntropy=3.004, SmoothL1=1.367 [Epoch 30][Batch 299], Speed: 352.469 samples/sec, CrossEntropy=3.008, SmoothL1=1.362 [Epoch 30][Batch 399], Speed: 361.961 samples/sec, CrossEntropy=3.009, SmoothL1=1.366 [Epoch 30][Batch 499], Speed: 353.407 samples/sec, CrossEntropy=3.004, SmoothL1=1.355 [Epoch 30][Batch 599], Speed: 358.958 samples/sec, CrossEntropy=3.005, SmoothL1=1.358 [Epoch 30][Batch 699], Speed: 351.143 samples/sec, CrossEntropy=3.003, SmoothL1=1.354 [Epoch 30][Batch 799], Speed: 358.572 samples/sec, CrossEntropy=3.001, SmoothL1=1.353 [Epoch 30][Batch 899], Speed: 347.004 samples/sec, CrossEntropy=3.002, SmoothL1=1.355 [Epoch 30][Batch 999], Speed: 350.158 samples/sec, CrossEntropy=3.003, SmoothL1=1.355 [Epoch 30][Batch 1099], Speed: 347.978 samples/sec, CrossEntropy=3.007, SmoothL1=1.355 [Epoch 30][Batch 1199], Speed: 354.504 samples/sec, CrossEntropy=3.002, SmoothL1=1.353 [Epoch 30][Batch 1299], Speed: 354.853 samples/sec, CrossEntropy=3.000, SmoothL1=1.348 [Epoch 30][Batch 1399], Speed: 348.029 samples/sec, CrossEntropy=3.001, SmoothL1=1.349 [Epoch 30][Batch 1499], Speed: 357.103 samples/sec, CrossEntropy=2.997, SmoothL1=1.348 [Epoch 30][Batch 1599], Speed: 360.322 samples/sec, CrossEntropy=2.997, SmoothL1=1.349 [Epoch 30][Batch 1699], Speed: 358.677 samples/sec, CrossEntropy=2.998, SmoothL1=1.350 [Epoch 30][Batch 1799], Speed: 354.286 samples/sec, CrossEntropy=2.997, SmoothL1=1.351 [Epoch 30] Training cost: 335.565, CrossEntropy=2.997, SmoothL1=1.350 [Epoch 30] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.184 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.339 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.184 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.024 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.190 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.325 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.186 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.265 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.277 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.044 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.297 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.479 person=28.2 bicycle=10.8 car=15.2 motorcycle=21.5 airplane=35.0 bus=42.5 train=42.6 truck=16.1 boat=8.5 traffic light=4.4 fire hydrant=34.6 stop sign=38.6 parking meter=21.3 bench=9.4 bird=11.6 cat=46.8 dog=38.7 horse=30.3 sheep=22.8 cow=24.2 elephant=36.1 bear=48.0 zebra=39.0 giraffe=40.8 backpack=2.1 umbrella=15.9 handbag=1.7 tie=9.0 suitcase=11.7 frisbee=20.8 skis=7.6 snowboard=5.5 sports ball=13.8 kite=12.3 baseball bat=6.8 baseball glove=7.4 skateboard=18.1 surfboard=12.6 tennis racket=19.7 bottle=7.5 wine glass=9.1 cup=14.1 fork=5.8 knife=2.6 spoon=2.1 bowl=21.4 banana=10.7 apple=5.1 sandwich=21.3 orange=15.8 broccoli=11.3 carrot=6.8 hot dog=16.3 pizza=30.2 donut=18.7 cake=17.8 chair=8.8 couch=27.2 potted plant=7.5 bed=28.7 dining table=17.4 toilet=36.5 tv=37.1 laptop=34.1 mouse=21.0 remote=3.2 keyboard=26.2 cell phone=12.4 microwave=25.3 oven=19.7 toaster=0.0 sink=16.2 refrigerator=25.8 book=2.7 clock=24.4 vase=12.7 scissors=9.9 teddy bear=22.4 hair drier=0.0 toothbrush=2.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =18.4 [Epoch 31][Batch 99], Speed: 349.285 samples/sec, CrossEntropy=2.988, SmoothL1=1.344 [Epoch 31][Batch 199], Speed: 346.736 samples/sec, CrossEntropy=2.993, SmoothL1=1.335 [Epoch 31][Batch 299], Speed: 352.008 samples/sec, CrossEntropy=2.999, SmoothL1=1.340 [Epoch 31][Batch 399], Speed: 347.498 samples/sec, CrossEntropy=2.991, SmoothL1=1.333 [Epoch 31][Batch 499], Speed: 355.382 samples/sec, CrossEntropy=2.984, SmoothL1=1.336 [Epoch 31][Batch 599], Speed: 357.459 samples/sec, CrossEntropy=2.986, SmoothL1=1.339 [Epoch 31][Batch 699], Speed: 347.681 samples/sec, CrossEntropy=2.985, SmoothL1=1.338 [Epoch 31][Batch 799], Speed: 361.569 samples/sec, CrossEntropy=2.985, SmoothL1=1.340 [Epoch 31][Batch 899], Speed: 353.679 samples/sec, CrossEntropy=2.983, SmoothL1=1.339 [Epoch 31][Batch 999], Speed: 351.946 samples/sec, CrossEntropy=2.986, SmoothL1=1.340 [Epoch 31][Batch 1099], Speed: 356.682 samples/sec, CrossEntropy=2.988, SmoothL1=1.341 [Epoch 31][Batch 1199], Speed: 349.669 samples/sec, CrossEntropy=2.990, SmoothL1=1.341 [Epoch 31][Batch 1299], Speed: 344.746 samples/sec, CrossEntropy=2.988, SmoothL1=1.341 [Epoch 31][Batch 1399], Speed: 359.397 samples/sec, CrossEntropy=2.986, SmoothL1=1.339 [Epoch 31][Batch 1499], Speed: 361.747 samples/sec, CrossEntropy=2.986, SmoothL1=1.341 [Epoch 31][Batch 1599], Speed: 350.730 samples/sec, CrossEntropy=2.989, SmoothL1=1.343 [Epoch 31][Batch 1699], Speed: 362.830 samples/sec, CrossEntropy=2.990, SmoothL1=1.346 [Epoch 31][Batch 1799], Speed: 349.511 samples/sec, CrossEntropy=2.990, SmoothL1=1.347 [Epoch 31] Training cost: 335.091, CrossEntropy=2.990, SmoothL1=1.347 [Epoch 31] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.181 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.336 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.177 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.025 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.193 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.324 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.184 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.264 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.276 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.043 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.292 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.480 person=27.3 bicycle=10.3 car=14.5 motorcycle=20.4 airplane=33.1 bus=40.7 train=41.7 truck=15.4 boat=7.7 traffic light=4.7 fire hydrant=33.3 stop sign=37.6 parking meter=21.5 bench=9.6 bird=11.6 cat=46.3 dog=35.8 horse=30.9 sheep=23.9 cow=24.5 elephant=36.6 bear=46.8 zebra=38.4 giraffe=41.7 backpack=2.2 umbrella=15.2 handbag=1.4 tie=9.1 suitcase=11.0 frisbee=21.0 skis=7.7 snowboard=6.8 sports ball=13.6 kite=12.2 baseball bat=8.1 baseball glove=7.3 skateboard=17.3 surfboard=12.8 tennis racket=19.2 bottle=8.3 wine glass=8.6 cup=13.5 fork=4.5 knife=2.2 spoon=2.3 bowl=20.5 banana=10.2 apple=7.6 sandwich=21.0 orange=17.7 broccoli=10.3 carrot=5.7 hot dog=14.8 pizza=29.6 donut=18.9 cake=16.1 chair=8.4 couch=26.3 potted plant=7.2 bed=29.3 dining table=17.3 toilet=37.0 tv=35.1 laptop=33.6 mouse=23.6 remote=3.1 keyboard=24.1 cell phone=11.3 microwave=29.4 oven=16.8 toaster=0.0 sink=15.8 refrigerator=26.1 book=3.0 clock=24.3 vase=11.3 scissors=7.2 teddy bear=23.9 hair drier=0.0 toothbrush=1.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =18.1 [Epoch 32][Batch 99], Speed: 344.573 samples/sec, CrossEntropy=2.999, SmoothL1=1.350 [Epoch 32][Batch 199], Speed: 345.742 samples/sec, CrossEntropy=2.962, SmoothL1=1.335 [Epoch 32][Batch 299], Speed: 353.247 samples/sec, CrossEntropy=2.967, SmoothL1=1.344 [Epoch 32][Batch 399], Speed: 350.218 samples/sec, CrossEntropy=2.966, SmoothL1=1.337 [Epoch 32][Batch 499], Speed: 346.212 samples/sec, CrossEntropy=2.973, SmoothL1=1.331 [Epoch 32][Batch 599], Speed: 353.499 samples/sec, CrossEntropy=2.971, SmoothL1=1.326 [Epoch 32][Batch 699], Speed: 361.219 samples/sec, CrossEntropy=2.974, SmoothL1=1.330 [Epoch 32][Batch 799], Speed: 360.360 samples/sec, CrossEntropy=2.974, SmoothL1=1.329 [Epoch 32][Batch 899], Speed: 353.565 samples/sec, CrossEntropy=2.970, SmoothL1=1.331 [Epoch 32][Batch 999], Speed: 350.694 samples/sec, CrossEntropy=2.969, SmoothL1=1.332 [Epoch 32][Batch 1099], Speed: 353.538 samples/sec, CrossEntropy=2.971, SmoothL1=1.335 [Epoch 32][Batch 1199], Speed: 357.880 samples/sec, CrossEntropy=2.969, SmoothL1=1.333 [Epoch 32][Batch 1299], Speed: 357.376 samples/sec, CrossEntropy=2.968, SmoothL1=1.335 [Epoch 32][Batch 1399], Speed: 350.443 samples/sec, CrossEntropy=2.967, SmoothL1=1.336 [Epoch 32][Batch 1499], Speed: 354.957 samples/sec, CrossEntropy=2.967, SmoothL1=1.335 [Epoch 32][Batch 1599], Speed: 358.971 samples/sec, CrossEntropy=2.965, SmoothL1=1.335 [Epoch 32][Batch 1699], Speed: 361.677 samples/sec, CrossEntropy=2.963, SmoothL1=1.334 [Epoch 32][Batch 1799], Speed: 349.936 samples/sec, CrossEntropy=2.963, SmoothL1=1.334 [Epoch 32] Training cost: 335.606, CrossEntropy=2.961, SmoothL1=1.333 [Epoch 32] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.186 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.343 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.186 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.027 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.191 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.326 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.188 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.271 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.283 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.299 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.481 person=28.7 bicycle=11.5 car=14.8 motorcycle=20.5 airplane=36.4 bus=40.4 train=43.3 truck=15.5 boat=8.6 traffic light=5.4 fire hydrant=34.7 stop sign=39.5 parking meter=22.7 bench=10.1 bird=12.3 cat=48.8 dog=36.7 horse=30.3 sheep=23.4 cow=25.2 elephant=38.2 bear=47.6 zebra=39.4 giraffe=41.3 backpack=2.0 umbrella=16.0 handbag=1.5 tie=9.5 suitcase=11.5 frisbee=20.1 skis=7.3 snowboard=8.1 sports ball=14.2 kite=11.6 baseball bat=7.0 baseball glove=7.2 skateboard=18.7 surfboard=12.3 tennis racket=19.0 bottle=8.2 wine glass=8.6 cup=14.4 fork=5.1 knife=2.0 spoon=2.1 bowl=20.5 banana=10.5 apple=6.6 sandwich=24.0 orange=18.1 broccoli=12.6 carrot=7.3 hot dog=16.1 pizza=30.6 donut=19.9 cake=17.6 chair=8.6 couch=27.8 potted plant=7.8 bed=30.0 dining table=18.0 toilet=33.7 tv=35.7 laptop=36.9 mouse=22.6 remote=3.3 keyboard=25.8 cell phone=11.0 microwave=27.8 oven=17.8 toaster=0.0 sink=15.3 refrigerator=26.9 book=2.8 clock=24.9 vase=12.3 scissors=8.0 teddy bear=23.6 hair drier=0.0 toothbrush=2.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =18.6 [Epoch 33][Batch 99], Speed: 347.428 samples/sec, CrossEntropy=2.996, SmoothL1=1.321 [Epoch 33][Batch 199], Speed: 360.938 samples/sec, CrossEntropy=2.976, SmoothL1=1.326 [Epoch 33][Batch 299], Speed: 352.880 samples/sec, CrossEntropy=2.970, SmoothL1=1.326 [Epoch 33][Batch 399], Speed: 352.742 samples/sec, CrossEntropy=2.964, SmoothL1=1.332 [Epoch 33][Batch 499], Speed: 355.049 samples/sec, CrossEntropy=2.968, SmoothL1=1.341 [Epoch 33][Batch 599], Speed: 360.772 samples/sec, CrossEntropy=2.966, SmoothL1=1.345 [Epoch 33][Batch 699], Speed: 349.009 samples/sec, CrossEntropy=2.965, SmoothL1=1.342 [Epoch 33][Batch 799], Speed: 354.025 samples/sec, CrossEntropy=2.968, SmoothL1=1.344 [Epoch 33][Batch 899], Speed: 353.397 samples/sec, CrossEntropy=2.969, SmoothL1=1.342 [Epoch 33][Batch 999], Speed: 359.899 samples/sec, CrossEntropy=2.969, SmoothL1=1.346 [Epoch 33][Batch 1099], Speed: 347.163 samples/sec, CrossEntropy=2.967, SmoothL1=1.344 [Epoch 33][Batch 1199], Speed: 361.000 samples/sec, CrossEntropy=2.972, SmoothL1=1.348 [Epoch 33][Batch 1299], Speed: 361.018 samples/sec, CrossEntropy=2.976, SmoothL1=1.347 [Epoch 33][Batch 1399], Speed: 350.177 samples/sec, CrossEntropy=2.974, SmoothL1=1.346 [Epoch 33][Batch 1499], Speed: 350.332 samples/sec, CrossEntropy=2.973, SmoothL1=1.344 [Epoch 33][Batch 1599], Speed: 353.578 samples/sec, CrossEntropy=2.973, SmoothL1=1.343 [Epoch 33][Batch 1699], Speed: 360.265 samples/sec, CrossEntropy=2.973, SmoothL1=1.345 [Epoch 33][Batch 1799], Speed: 353.289 samples/sec, CrossEntropy=2.972, SmoothL1=1.347 [Epoch 33] Training cost: 334.798, CrossEntropy=2.973, SmoothL1=1.346 [Epoch 33] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.185 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.344 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.183 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.026 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.194 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.329 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.188 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.269 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.282 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.046 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.303 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.488 person=28.5 bicycle=11.3 car=15.5 motorcycle=21.6 airplane=36.3 bus=41.2 train=43.1 truck=15.5 boat=7.1 traffic light=5.0 fire hydrant=33.4 stop sign=41.4 parking meter=21.2 bench=9.6 bird=11.0 cat=47.9 dog=36.9 horse=30.3 sheep=24.8 cow=24.3 elephant=36.4 bear=48.3 zebra=38.9 giraffe=41.0 backpack=2.1 umbrella=16.2 handbag=1.4 tie=10.1 suitcase=11.6 frisbee=20.6 skis=6.8 snowboard=7.9 sports ball=14.4 kite=12.1 baseball bat=6.9 baseball glove=6.8 skateboard=18.9 surfboard=11.5 tennis racket=18.8 bottle=8.2 wine glass=8.8 cup=13.8 fork=5.3 knife=2.3 spoon=2.1 bowl=20.8 banana=10.3 apple=5.9 sandwich=24.0 orange=16.5 broccoli=11.8 carrot=6.4 hot dog=15.7 pizza=30.0 donut=19.7 cake=17.4 chair=8.9 couch=26.4 potted plant=7.4 bed=28.8 dining table=17.8 toilet=35.9 tv=36.8 laptop=34.8 mouse=25.2 remote=4.1 keyboard=25.7 cell phone=12.2 microwave=26.9 oven=18.9 toaster=0.0 sink=15.9 refrigerator=27.5 book=3.1 clock=24.8 vase=11.8 scissors=4.8 teddy bear=24.3 hair drier=0.0 toothbrush=2.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =18.5 [Epoch 34][Batch 99], Speed: 352.608 samples/sec, CrossEntropy=2.935, SmoothL1=1.309 [Epoch 34][Batch 199], Speed: 347.675 samples/sec, CrossEntropy=2.962, SmoothL1=1.315 [Epoch 34][Batch 299], Speed: 364.735 samples/sec, CrossEntropy=2.960, SmoothL1=1.308 [Epoch 34][Batch 399], Speed: 357.944 samples/sec, CrossEntropy=2.950, SmoothL1=1.307 [Epoch 34][Batch 499], Speed: 354.770 samples/sec, CrossEntropy=2.962, SmoothL1=1.316 [Epoch 34][Batch 599], Speed: 347.171 samples/sec, CrossEntropy=2.961, SmoothL1=1.318 [Epoch 34][Batch 699], Speed: 359.281 samples/sec, CrossEntropy=2.967, SmoothL1=1.320 [Epoch 34][Batch 799], Speed: 348.795 samples/sec, CrossEntropy=2.967, SmoothL1=1.323 [Epoch 34][Batch 899], Speed: 352.065 samples/sec, CrossEntropy=2.963, SmoothL1=1.320 [Epoch 34][Batch 999], Speed: 348.253 samples/sec, CrossEntropy=2.960, SmoothL1=1.318 [Epoch 34][Batch 1099], Speed: 347.925 samples/sec, CrossEntropy=2.963, SmoothL1=1.319 [Epoch 34][Batch 1199], Speed: 352.917 samples/sec, CrossEntropy=2.964, SmoothL1=1.321 [Epoch 34][Batch 1299], Speed: 360.756 samples/sec, CrossEntropy=2.968, SmoothL1=1.323 [Epoch 34][Batch 1399], Speed: 350.509 samples/sec, CrossEntropy=2.965, SmoothL1=1.322 [Epoch 34][Batch 1499], Speed: 354.037 samples/sec, CrossEntropy=2.961, SmoothL1=1.323 [Epoch 34][Batch 1599], Speed: 346.476 samples/sec, CrossEntropy=2.960, SmoothL1=1.323 [Epoch 34][Batch 1699], Speed: 354.474 samples/sec, CrossEntropy=2.960, SmoothL1=1.324 [Epoch 34][Batch 1799], Speed: 361.081 samples/sec, CrossEntropy=2.957, SmoothL1=1.322 [Epoch 34] Training cost: 334.966, CrossEntropy=2.957, SmoothL1=1.324 [Epoch 34] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.188 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.344 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.189 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.026 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.195 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.338 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.189 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.272 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.284 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.046 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.305 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.492 person=28.4 bicycle=11.7 car=15.7 motorcycle=21.1 airplane=38.0 bus=42.2 train=45.3 truck=16.3 boat=7.6 traffic light=5.1 fire hydrant=33.2 stop sign=41.8 parking meter=21.8 bench=10.7 bird=11.7 cat=47.6 dog=38.0 horse=29.7 sheep=24.6 cow=24.4 elephant=37.3 bear=47.2 zebra=40.4 giraffe=41.6 backpack=2.0 umbrella=16.9 handbag=1.5 tie=8.4 suitcase=10.8 frisbee=20.5 skis=6.9 snowboard=8.4 sports ball=13.6 kite=12.4 baseball bat=6.1 baseball glove=6.8 skateboard=18.8 surfboard=11.5 tennis racket=19.3 bottle=8.2 wine glass=8.8 cup=14.8 fork=5.9 knife=2.9 spoon=2.6 bowl=19.6 banana=10.5 apple=7.8 sandwich=23.5 orange=17.2 broccoli=11.8 carrot=6.5 hot dog=16.9 pizza=32.7 donut=20.7 cake=17.4 chair=9.2 couch=28.1 potted plant=7.7 bed=29.7 dining table=18.1 toilet=35.7 tv=36.6 laptop=36.6 mouse=22.1 remote=3.8 keyboard=24.5 cell phone=11.3 microwave=29.3 oven=18.4 toaster=0.0 sink=15.3 refrigerator=27.3 book=2.7 clock=24.6 vase=12.5 scissors=10.4 teddy bear=24.6 hair drier=0.0 toothbrush=1.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =18.8 [Epoch 35][Batch 99], Speed: 356.574 samples/sec, CrossEntropy=2.989, SmoothL1=1.344 [Epoch 35][Batch 199], Speed: 357.047 samples/sec, CrossEntropy=2.977, SmoothL1=1.343 [Epoch 35][Batch 299], Speed: 343.278 samples/sec, CrossEntropy=2.962, SmoothL1=1.332 [Epoch 35][Batch 399], Speed: 361.741 samples/sec, CrossEntropy=2.964, SmoothL1=1.333 [Epoch 35][Batch 499], Speed: 352.304 samples/sec, CrossEntropy=2.948, SmoothL1=1.327 [Epoch 35][Batch 599], Speed: 347.834 samples/sec, CrossEntropy=2.948, SmoothL1=1.326 [Epoch 35][Batch 699], Speed: 352.419 samples/sec, CrossEntropy=2.942, SmoothL1=1.324 [Epoch 35][Batch 799], Speed: 349.870 samples/sec, CrossEntropy=2.944, SmoothL1=1.322 [Epoch 35][Batch 899], Speed: 360.085 samples/sec, CrossEntropy=2.945, SmoothL1=1.325 [Epoch 35][Batch 999], Speed: 358.282 samples/sec, CrossEntropy=2.945, SmoothL1=1.326 [Epoch 35][Batch 1099], Speed: 356.005 samples/sec, CrossEntropy=2.946, SmoothL1=1.325 [Epoch 35][Batch 1199], Speed: 362.385 samples/sec, CrossEntropy=2.943, SmoothL1=1.325 [Epoch 35][Batch 1299], Speed: 355.951 samples/sec, CrossEntropy=2.941, SmoothL1=1.322 [Epoch 35][Batch 1399], Speed: 349.482 samples/sec, CrossEntropy=2.939, SmoothL1=1.321 [Epoch 35][Batch 1499], Speed: 356.081 samples/sec, CrossEntropy=2.940, SmoothL1=1.322 [Epoch 35][Batch 1599], Speed: 347.631 samples/sec, CrossEntropy=2.939, SmoothL1=1.319 [Epoch 35][Batch 1699], Speed: 351.491 samples/sec, CrossEntropy=2.940, SmoothL1=1.320 [Epoch 35][Batch 1799], Speed: 360.981 samples/sec, CrossEntropy=2.940, SmoothL1=1.323 [Epoch 35] Training cost: 334.727, CrossEntropy=2.940, SmoothL1=1.322 [Epoch 35] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.189 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.347 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.190 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.028 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.196 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.339 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.190 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.273 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.285 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.047 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.308 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.497 person=28.5 bicycle=11.9 car=15.4 motorcycle=20.8 airplane=36.9 bus=41.8 train=40.7 truck=14.6 boat=7.7 traffic light=5.1 fire hydrant=34.1 stop sign=40.4 parking meter=20.9 bench=9.5 bird=11.8 cat=49.4 dog=38.2 horse=31.5 sheep=24.9 cow=24.4 elephant=36.0 bear=45.0 zebra=41.6 giraffe=43.2 backpack=2.4 umbrella=17.0 handbag=1.5 tie=9.4 suitcase=11.1 frisbee=21.3 skis=7.3 snowboard=7.0 sports ball=14.0 kite=12.9 baseball bat=7.4 baseball glove=7.2 skateboard=18.9 surfboard=13.3 tennis racket=19.9 bottle=8.5 wine glass=8.5 cup=14.9 fork=6.5 knife=2.6 spoon=2.3 bowl=21.4 banana=10.1 apple=8.4 sandwich=23.4 orange=17.3 broccoli=11.9 carrot=7.1 hot dog=18.0 pizza=31.8 donut=19.7 cake=18.9 chair=9.3 couch=26.7 potted plant=8.0 bed=28.9 dining table=18.9 toilet=36.9 tv=36.4 laptop=36.2 mouse=22.6 remote=4.1 keyboard=24.5 cell phone=12.3 microwave=26.3 oven=18.8 toaster=0.0 sink=17.2 refrigerator=29.3 book=3.1 clock=25.4 vase=12.4 scissors=11.0 teddy bear=24.8 hair drier=0.0 toothbrush=4.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =18.9 [Epoch 36][Batch 99], Speed: 360.075 samples/sec, CrossEntropy=2.958, SmoothL1=1.307 [Epoch 36][Batch 199], Speed: 347.949 samples/sec, CrossEntropy=2.945, SmoothL1=1.318 [Epoch 36][Batch 299], Speed: 363.099 samples/sec, CrossEntropy=2.932, SmoothL1=1.317 [Epoch 36][Batch 399], Speed: 364.767 samples/sec, CrossEntropy=2.926, SmoothL1=1.315 [Epoch 36][Batch 499], Speed: 346.900 samples/sec, CrossEntropy=2.920, SmoothL1=1.313 [Epoch 36][Batch 599], Speed: 351.971 samples/sec, CrossEntropy=2.921, SmoothL1=1.313 [Epoch 36][Batch 699], Speed: 349.791 samples/sec, CrossEntropy=2.922, SmoothL1=1.315 [Epoch 36][Batch 799], Speed: 361.354 samples/sec, CrossEntropy=2.924, SmoothL1=1.316 [Epoch 36][Batch 899], Speed: 350.510 samples/sec, CrossEntropy=2.925, SmoothL1=1.318 [Epoch 36][Batch 999], Speed: 349.756 samples/sec, CrossEntropy=2.927, SmoothL1=1.322 [Epoch 36][Batch 1099], Speed: 356.414 samples/sec, CrossEntropy=2.926, SmoothL1=1.319 [Epoch 36][Batch 1199], Speed: 359.049 samples/sec, CrossEntropy=2.930, SmoothL1=1.320 [Epoch 36][Batch 1299], Speed: 347.272 samples/sec, CrossEntropy=2.927, SmoothL1=1.319 [Epoch 36][Batch 1399], Speed: 355.703 samples/sec, CrossEntropy=2.927, SmoothL1=1.319 [Epoch 36][Batch 1499], Speed: 359.473 samples/sec, CrossEntropy=2.923, SmoothL1=1.316 [Epoch 36][Batch 1599], Speed: 363.239 samples/sec, CrossEntropy=2.922, SmoothL1=1.318 [Epoch 36][Batch 1699], Speed: 350.187 samples/sec, CrossEntropy=2.922, SmoothL1=1.317 [Epoch 36][Batch 1799], Speed: 350.963 samples/sec, CrossEntropy=2.922, SmoothL1=1.316 [Epoch 36] Training cost: 335.086, CrossEntropy=2.923, SmoothL1=1.316 [Epoch 36] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.189 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.347 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.190 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.027 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.198 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.336 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.189 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.272 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.284 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.047 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.305 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.488 person=29.0 bicycle=11.6 car=15.7 motorcycle=20.4 airplane=35.0 bus=40.8 train=40.6 truck=16.1 boat=8.2 traffic light=5.1 fire hydrant=33.9 stop sign=39.2 parking meter=21.1 bench=10.0 bird=12.4 cat=47.7 dog=38.7 horse=31.9 sheep=26.0 cow=23.8 elephant=38.1 bear=51.6 zebra=40.7 giraffe=41.1 backpack=2.2 umbrella=16.9 handbag=1.7 tie=7.7 suitcase=11.1 frisbee=20.9 skis=7.4 snowboard=8.0 sports ball=14.4 kite=13.0 baseball bat=7.9 baseball glove=7.0 skateboard=18.9 surfboard=13.2 tennis racket=19.0 bottle=8.0 wine glass=9.1 cup=14.7 fork=5.7 knife=2.3 spoon=2.2 bowl=21.2 banana=9.4 apple=6.6 sandwich=23.8 orange=16.0 broccoli=13.1 carrot=7.2 hot dog=16.3 pizza=33.2 donut=20.0 cake=18.3 chair=9.3 couch=27.0 potted plant=7.9 bed=27.6 dining table=17.8 toilet=36.3 tv=37.4 laptop=35.7 mouse=19.5 remote=4.4 keyboard=26.2 cell phone=12.7 microwave=29.3 oven=19.0 toaster=0.0 sink=17.0 refrigerator=26.4 book=2.8 clock=24.4 vase=13.7 scissors=11.6 teddy bear=27.1 hair drier=0.0 toothbrush=2.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =18.9 [Epoch 37][Batch 99], Speed: 349.797 samples/sec, CrossEntropy=2.909, SmoothL1=1.296 [Epoch 37][Batch 199], Speed: 357.614 samples/sec, CrossEntropy=2.940, SmoothL1=1.320 [Epoch 37][Batch 299], Speed: 362.208 samples/sec, CrossEntropy=2.940, SmoothL1=1.325 [Epoch 37][Batch 399], Speed: 350.857 samples/sec, CrossEntropy=2.932, SmoothL1=1.320 [Epoch 37][Batch 499], Speed: 350.654 samples/sec, CrossEntropy=2.927, SmoothL1=1.317 [Epoch 37][Batch 599], Speed: 349.128 samples/sec, CrossEntropy=2.925, SmoothL1=1.319 [Epoch 37][Batch 699], Speed: 353.532 samples/sec, CrossEntropy=2.922, SmoothL1=1.316 [Epoch 37][Batch 799], Speed: 359.467 samples/sec, CrossEntropy=2.918, SmoothL1=1.316 [Epoch 37][Batch 899], Speed: 363.159 samples/sec, CrossEntropy=2.916, SmoothL1=1.312 [Epoch 37][Batch 999], Speed: 354.615 samples/sec, CrossEntropy=2.923, SmoothL1=1.316 [Epoch 37][Batch 1099], Speed: 357.044 samples/sec, CrossEntropy=2.922, SmoothL1=1.316 [Epoch 37][Batch 1199], Speed: 354.009 samples/sec, CrossEntropy=2.921, SmoothL1=1.316 [Epoch 37][Batch 1299], Speed: 349.483 samples/sec, CrossEntropy=2.920, SmoothL1=1.317 [Epoch 37][Batch 1399], Speed: 344.586 samples/sec, CrossEntropy=2.915, SmoothL1=1.315 [Epoch 37][Batch 1499], Speed: 359.331 samples/sec, CrossEntropy=2.917, SmoothL1=1.316 [Epoch 37][Batch 1599], Speed: 363.545 samples/sec, CrossEntropy=2.919, SmoothL1=1.315 [Epoch 37][Batch 1699], Speed: 353.215 samples/sec, CrossEntropy=2.917, SmoothL1=1.313 [Epoch 37][Batch 1799], Speed: 338.203 samples/sec, CrossEntropy=2.917, SmoothL1=1.313 [Epoch 37] Training cost: 334.900, CrossEntropy=2.917, SmoothL1=1.313 [Epoch 37] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.192 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.351 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.193 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.028 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.202 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.193 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.276 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.289 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.307 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.498 person=28.8 bicycle=13.3 car=15.7 motorcycle=23.3 airplane=37.6 bus=42.7 train=44.7 truck=16.9 boat=8.0 traffic light=5.1 fire hydrant=36.2 stop sign=40.2 parking meter=22.3 bench=9.7 bird=11.5 cat=47.2 dog=39.1 horse=32.3 sheep=22.8 cow=24.0 elephant=37.8 bear=48.7 zebra=40.5 giraffe=41.3 backpack=2.4 umbrella=17.4 handbag=1.9 tie=9.3 suitcase=11.2 frisbee=21.4 skis=8.2 snowboard=8.9 sports ball=14.7 kite=13.0 baseball bat=8.0 baseball glove=7.3 skateboard=20.0 surfboard=13.6 tennis racket=19.7 bottle=8.9 wine glass=8.7 cup=14.8 fork=6.2 knife=2.6 spoon=2.9 bowl=21.0 banana=11.1 apple=6.1 sandwich=25.5 orange=17.0 broccoli=11.6 carrot=6.5 hot dog=17.6 pizza=32.0 donut=19.7 cake=18.3 chair=9.4 couch=28.8 potted plant=8.8 bed=30.9 dining table=18.2 toilet=37.0 tv=37.5 laptop=37.4 mouse=24.2 remote=3.5 keyboard=26.1 cell phone=12.1 microwave=27.4 oven=18.8 toaster=0.0 sink=16.2 refrigerator=27.3 book=3.0 clock=25.8 vase=12.7 scissors=8.2 teddy bear=25.2 hair drier=0.0 toothbrush=4.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.2 [Epoch 38][Batch 99], Speed: 352.115 samples/sec, CrossEntropy=2.884, SmoothL1=1.295 [Epoch 38][Batch 199], Speed: 360.387 samples/sec, CrossEntropy=2.901, SmoothL1=1.295 [Epoch 38][Batch 299], Speed: 346.618 samples/sec, CrossEntropy=2.916, SmoothL1=1.304 [Epoch 38][Batch 399], Speed: 361.786 samples/sec, CrossEntropy=2.914, SmoothL1=1.303 [Epoch 38][Batch 499], Speed: 350.352 samples/sec, CrossEntropy=2.919, SmoothL1=1.306 [Epoch 38][Batch 599], Speed: 345.439 samples/sec, CrossEntropy=2.918, SmoothL1=1.302 [Epoch 38][Batch 699], Speed: 359.784 samples/sec, CrossEntropy=2.915, SmoothL1=1.298 [Epoch 38][Batch 799], Speed: 358.430 samples/sec, CrossEntropy=2.916, SmoothL1=1.302 [Epoch 38][Batch 899], Speed: 348.084 samples/sec, CrossEntropy=2.921, SmoothL1=1.305 [Epoch 38][Batch 999], Speed: 359.313 samples/sec, CrossEntropy=2.920, SmoothL1=1.307 [Epoch 38][Batch 1099], Speed: 348.794 samples/sec, CrossEntropy=2.922, SmoothL1=1.309 [Epoch 38][Batch 1199], Speed: 341.775 samples/sec, CrossEntropy=2.920, SmoothL1=1.308 [Epoch 38][Batch 1299], Speed: 346.892 samples/sec, CrossEntropy=2.919, SmoothL1=1.309 [Epoch 38][Batch 1399], Speed: 349.731 samples/sec, CrossEntropy=2.918, SmoothL1=1.308 [Epoch 38][Batch 1499], Speed: 356.104 samples/sec, CrossEntropy=2.916, SmoothL1=1.308 [Epoch 38][Batch 1599], Speed: 358.096 samples/sec, CrossEntropy=2.917, SmoothL1=1.309 [Epoch 38][Batch 1699], Speed: 358.475 samples/sec, CrossEntropy=2.916, SmoothL1=1.308 [Epoch 38][Batch 1799], Speed: 360.664 samples/sec, CrossEntropy=2.916, SmoothL1=1.308 [Epoch 38] Training cost: 336.001, CrossEntropy=2.916, SmoothL1=1.310 [Epoch 38] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.191 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.347 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.191 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.026 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.201 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.191 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.275 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.288 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.046 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.507 person=28.9 bicycle=12.8 car=15.7 motorcycle=21.4 airplane=38.3 bus=39.9 train=42.4 truck=16.3 boat=8.8 traffic light=4.8 fire hydrant=35.5 stop sign=40.2 parking meter=21.7 bench=10.6 bird=11.7 cat=46.7 dog=36.6 horse=31.4 sheep=25.5 cow=25.8 elephant=36.9 bear=48.3 zebra=39.3 giraffe=41.5 backpack=2.2 umbrella=17.5 handbag=1.7 tie=9.7 suitcase=11.5 frisbee=20.6 skis=7.6 snowboard=8.8 sports ball=14.0 kite=13.1 baseball bat=7.7 baseball glove=8.2 skateboard=18.9 surfboard=13.2 tennis racket=19.9 bottle=9.3 wine glass=9.3 cup=14.9 fork=6.8 knife=2.5 spoon=2.4 bowl=21.5 banana=10.2 apple=7.4 sandwich=26.9 orange=17.9 broccoli=13.4 carrot=6.4 hot dog=16.2 pizza=29.8 donut=20.0 cake=17.6 chair=9.5 couch=27.7 potted plant=9.2 bed=29.8 dining table=18.2 toilet=36.4 tv=36.6 laptop=35.3 mouse=22.8 remote=3.9 keyboard=27.1 cell phone=13.0 microwave=30.3 oven=19.7 toaster=0.0 sink=14.8 refrigerator=26.7 book=2.5 clock=25.4 vase=13.2 scissors=11.8 teddy bear=24.3 hair drier=0.0 toothbrush=1.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.1 [Epoch 39][Batch 99], Speed: 345.383 samples/sec, CrossEntropy=2.914, SmoothL1=1.310 [Epoch 39][Batch 199], Speed: 359.182 samples/sec, CrossEntropy=2.917, SmoothL1=1.308 [Epoch 39][Batch 299], Speed: 353.895 samples/sec, CrossEntropy=2.914, SmoothL1=1.302 [Epoch 39][Batch 399], Speed: 349.077 samples/sec, CrossEntropy=2.907, SmoothL1=1.297 [Epoch 39][Batch 499], Speed: 353.024 samples/sec, CrossEntropy=2.915, SmoothL1=1.303 [Epoch 39][Batch 599], Speed: 357.315 samples/sec, CrossEntropy=2.919, SmoothL1=1.297 [Epoch 39][Batch 699], Speed: 363.067 samples/sec, CrossEntropy=2.910, SmoothL1=1.293 [Epoch 39][Batch 799], Speed: 351.468 samples/sec, CrossEntropy=2.913, SmoothL1=1.299 [Epoch 39][Batch 899], Speed: 352.244 samples/sec, CrossEntropy=2.914, SmoothL1=1.304 [Epoch 39][Batch 999], Speed: 358.564 samples/sec, CrossEntropy=2.908, SmoothL1=1.302 [Epoch 39][Batch 1099], Speed: 348.405 samples/sec, CrossEntropy=2.906, SmoothL1=1.301 [Epoch 39][Batch 1199], Speed: 351.205 samples/sec, CrossEntropy=2.904, SmoothL1=1.301 [Epoch 39][Batch 1299], Speed: 359.508 samples/sec, CrossEntropy=2.903, SmoothL1=1.299 [Epoch 39][Batch 1399], Speed: 356.317 samples/sec, CrossEntropy=2.901, SmoothL1=1.301 [Epoch 39][Batch 1499], Speed: 349.261 samples/sec, CrossEntropy=2.900, SmoothL1=1.300 [Epoch 39][Batch 1599], Speed: 344.260 samples/sec, CrossEntropy=2.898, SmoothL1=1.299 [Epoch 39][Batch 1699], Speed: 345.246 samples/sec, CrossEntropy=2.896, SmoothL1=1.297 [Epoch 39][Batch 1799], Speed: 356.992 samples/sec, CrossEntropy=2.896, SmoothL1=1.295 [Epoch 39] Training cost: 334.624, CrossEntropy=2.895, SmoothL1=1.296 [Epoch 39] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.192 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.346 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.192 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.027 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.198 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.347 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.193 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.275 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.287 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.046 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.305 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.505 person=29.1 bicycle=12.7 car=15.8 motorcycle=23.8 airplane=35.9 bus=42.0 train=44.5 truck=16.6 boat=7.7 traffic light=4.7 fire hydrant=36.5 stop sign=40.8 parking meter=24.8 bench=10.7 bird=11.9 cat=45.8 dog=38.5 horse=32.9 sheep=23.4 cow=25.0 elephant=36.2 bear=45.0 zebra=41.4 giraffe=40.3 backpack=2.3 umbrella=17.1 handbag=1.3 tie=8.3 suitcase=12.7 frisbee=20.7 skis=7.8 snowboard=9.0 sports ball=14.0 kite=12.2 baseball bat=7.6 baseball glove=8.6 skateboard=19.2 surfboard=13.3 tennis racket=19.6 bottle=8.9 wine glass=9.4 cup=14.9 fork=6.1 knife=2.5 spoon=2.9 bowl=19.6 banana=10.2 apple=8.0 sandwich=23.9 orange=17.2 broccoli=12.3 carrot=6.2 hot dog=18.2 pizza=32.0 donut=22.0 cake=17.3 chair=9.4 couch=27.6 potted plant=8.3 bed=29.4 dining table=19.2 toilet=37.8 tv=38.2 laptop=38.4 mouse=23.1 remote=3.8 keyboard=26.7 cell phone=12.1 microwave=25.9 oven=19.5 toaster=0.0 sink=16.6 refrigerator=28.5 book=2.7 clock=24.5 vase=11.6 scissors=11.7 teddy bear=24.1 hair drier=0.0 toothbrush=4.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.2 [Epoch 40][Batch 99], Speed: 349.928 samples/sec, CrossEntropy=2.897, SmoothL1=1.272 [Epoch 40][Batch 199], Speed: 361.023 samples/sec, CrossEntropy=2.899, SmoothL1=1.281 [Epoch 40][Batch 299], Speed: 352.913 samples/sec, CrossEntropy=2.899, SmoothL1=1.275 [Epoch 40][Batch 399], Speed: 362.094 samples/sec, CrossEntropy=2.900, SmoothL1=1.284 [Epoch 40][Batch 499], Speed: 345.331 samples/sec, CrossEntropy=2.899, SmoothL1=1.284 [Epoch 40][Batch 599], Speed: 352.273 samples/sec, CrossEntropy=2.895, SmoothL1=1.284 [Epoch 40][Batch 699], Speed: 362.807 samples/sec, CrossEntropy=2.891, SmoothL1=1.284 [Epoch 40][Batch 799], Speed: 338.035 samples/sec, CrossEntropy=2.887, SmoothL1=1.283 [Epoch 40][Batch 899], Speed: 356.781 samples/sec, CrossEntropy=2.891, SmoothL1=1.286 [Epoch 40][Batch 999], Speed: 357.283 samples/sec, CrossEntropy=2.893, SmoothL1=1.286 [Epoch 40][Batch 1099], Speed: 360.973 samples/sec, CrossEntropy=2.897, SmoothL1=1.291 [Epoch 40][Batch 1199], Speed: 353.522 samples/sec, CrossEntropy=2.897, SmoothL1=1.292 [Epoch 40][Batch 1299], Speed: 342.588 samples/sec, CrossEntropy=2.894, SmoothL1=1.296 [Epoch 40][Batch 1399], Speed: 359.340 samples/sec, CrossEntropy=2.892, SmoothL1=1.296 [Epoch 40][Batch 1499], Speed: 353.751 samples/sec, CrossEntropy=2.890, SmoothL1=1.294 [Epoch 40][Batch 1599], Speed: 348.116 samples/sec, CrossEntropy=2.888, SmoothL1=1.293 [Epoch 40][Batch 1699], Speed: 347.950 samples/sec, CrossEntropy=2.887, SmoothL1=1.295 [Epoch 40][Batch 1799], Speed: 351.465 samples/sec, CrossEntropy=2.888, SmoothL1=1.296 [Epoch 40] Training cost: 334.887, CrossEntropy=2.888, SmoothL1=1.296 [Epoch 40] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.193 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.352 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.193 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.027 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.203 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.343 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.192 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.277 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.289 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.315 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.493 person=29.2 bicycle=12.4 car=15.8 motorcycle=22.3 airplane=36.2 bus=41.3 train=42.9 truck=17.2 boat=7.8 traffic light=5.4 fire hydrant=34.9 stop sign=39.9 parking meter=23.9 bench=10.1 bird=12.1 cat=47.8 dog=41.3 horse=29.9 sheep=24.8 cow=25.5 elephant=37.1 bear=48.4 zebra=40.9 giraffe=41.7 backpack=2.4 umbrella=17.4 handbag=1.6 tie=9.9 suitcase=12.7 frisbee=20.4 skis=7.9 snowboard=7.9 sports ball=14.2 kite=11.2 baseball bat=6.6 baseball glove=8.1 skateboard=18.6 surfboard=13.8 tennis racket=20.7 bottle=9.2 wine glass=9.0 cup=15.2 fork=7.4 knife=2.7 spoon=2.9 bowl=21.1 banana=11.4 apple=7.9 sandwich=26.0 orange=17.2 broccoli=13.8 carrot=7.0 hot dog=17.6 pizza=32.7 donut=19.9 cake=17.2 chair=9.2 couch=29.2 potted plant=9.0 bed=29.9 dining table=18.3 toilet=38.0 tv=37.5 laptop=37.4 mouse=25.1 remote=3.7 keyboard=28.4 cell phone=12.5 microwave=26.8 oven=18.1 toaster=0.0 sink=15.4 refrigerator=27.7 book=3.0 clock=25.8 vase=13.1 scissors=9.5 teddy bear=24.7 hair drier=0.0 toothbrush=3.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.3 [Epoch 41][Batch 99], Speed: 339.787 samples/sec, CrossEntropy=2.870, SmoothL1=1.308 [Epoch 41][Batch 199], Speed: 356.879 samples/sec, CrossEntropy=2.891, SmoothL1=1.331 [Epoch 41][Batch 299], Speed: 349.946 samples/sec, CrossEntropy=2.870, SmoothL1=1.314 [Epoch 41][Batch 399], Speed: 361.728 samples/sec, CrossEntropy=2.884, SmoothL1=1.317 [Epoch 41][Batch 499], Speed: 360.150 samples/sec, CrossEntropy=2.885, SmoothL1=1.310 [Epoch 41][Batch 599], Speed: 359.886 samples/sec, CrossEntropy=2.890, SmoothL1=1.307 [Epoch 41][Batch 699], Speed: 355.273 samples/sec, CrossEntropy=2.884, SmoothL1=1.304 [Epoch 41][Batch 799], Speed: 348.652 samples/sec, CrossEntropy=2.884, SmoothL1=1.303 [Epoch 41][Batch 899], Speed: 352.931 samples/sec, CrossEntropy=2.884, SmoothL1=1.302 [Epoch 41][Batch 999], Speed: 358.249 samples/sec, CrossEntropy=2.889, SmoothL1=1.303 [Epoch 41][Batch 1099], Speed: 355.763 samples/sec, CrossEntropy=2.888, SmoothL1=1.298 [Epoch 41][Batch 1199], Speed: 357.831 samples/sec, CrossEntropy=2.885, SmoothL1=1.297 [Epoch 41][Batch 1299], Speed: 349.444 samples/sec, CrossEntropy=2.884, SmoothL1=1.295 [Epoch 41][Batch 1399], Speed: 343.766 samples/sec, CrossEntropy=2.885, SmoothL1=1.297 [Epoch 41][Batch 1499], Speed: 348.579 samples/sec, CrossEntropy=2.884, SmoothL1=1.298 [Epoch 41][Batch 1599], Speed: 345.821 samples/sec, CrossEntropy=2.884, SmoothL1=1.297 [Epoch 41][Batch 1699], Speed: 363.769 samples/sec, CrossEntropy=2.883, SmoothL1=1.295 [Epoch 41][Batch 1799], Speed: 346.000 samples/sec, CrossEntropy=2.882, SmoothL1=1.295 [Epoch 41] Training cost: 334.583, CrossEntropy=2.882, SmoothL1=1.297 [Epoch 41] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.195 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.354 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.195 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.027 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.204 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.347 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.193 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.277 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.290 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.047 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.314 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.503 person=29.1 bicycle=13.2 car=16.4 motorcycle=21.9 airplane=37.4 bus=43.3 train=46.0 truck=17.1 boat=8.3 traffic light=5.4 fire hydrant=37.4 stop sign=42.0 parking meter=21.6 bench=10.5 bird=12.3 cat=46.8 dog=37.5 horse=32.6 sheep=24.8 cow=25.5 elephant=36.6 bear=44.2 zebra=42.3 giraffe=44.9 backpack=2.6 umbrella=17.3 handbag=1.4 tie=8.8 suitcase=12.3 frisbee=20.9 skis=8.0 snowboard=8.2 sports ball=13.9 kite=13.0 baseball bat=7.0 baseball glove=8.0 skateboard=20.4 surfboard=13.9 tennis racket=20.4 bottle=8.1 wine glass=10.4 cup=15.0 fork=7.2 knife=3.0 spoon=2.8 bowl=21.2 banana=10.5 apple=7.4 sandwich=26.3 orange=17.4 broccoli=13.5 carrot=7.0 hot dog=20.2 pizza=32.8 donut=19.5 cake=17.7 chair=9.5 couch=27.6 potted plant=8.6 bed=30.2 dining table=18.8 toilet=35.4 tv=37.2 laptop=37.7 mouse=22.1 remote=4.7 keyboard=26.6 cell phone=12.3 microwave=27.9 oven=19.8 toaster=0.0 sink=17.0 refrigerator=29.5 book=2.9 clock=24.5 vase=13.2 scissors=10.5 teddy bear=26.6 hair drier=0.0 toothbrush=4.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.5 [Epoch 42][Batch 99], Speed: 345.311 samples/sec, CrossEntropy=2.860, SmoothL1=1.265 [Epoch 42][Batch 199], Speed: 342.000 samples/sec, CrossEntropy=2.860, SmoothL1=1.281 [Epoch 42][Batch 299], Speed: 345.912 samples/sec, CrossEntropy=2.865, SmoothL1=1.280 [Epoch 42][Batch 399], Speed: 350.156 samples/sec, CrossEntropy=2.885, SmoothL1=1.285 [Epoch 42][Batch 499], Speed: 336.474 samples/sec, CrossEntropy=2.883, SmoothL1=1.288 [Epoch 42][Batch 599], Speed: 357.445 samples/sec, CrossEntropy=2.892, SmoothL1=1.289 [Epoch 42][Batch 699], Speed: 344.711 samples/sec, CrossEntropy=2.890, SmoothL1=1.286 [Epoch 42][Batch 799], Speed: 357.247 samples/sec, CrossEntropy=2.896, SmoothL1=1.291 [Epoch 42][Batch 899], Speed: 346.624 samples/sec, CrossEntropy=2.894, SmoothL1=1.294 [Epoch 42][Batch 999], Speed: 355.817 samples/sec, CrossEntropy=2.889, SmoothL1=1.293 [Epoch 42][Batch 1099], Speed: 350.460 samples/sec, CrossEntropy=2.886, SmoothL1=1.290 [Epoch 42][Batch 1199], Speed: 341.177 samples/sec, CrossEntropy=2.886, SmoothL1=1.292 [Epoch 42][Batch 1299], Speed: 359.618 samples/sec, CrossEntropy=2.880, SmoothL1=1.289 [Epoch 42][Batch 1399], Speed: 348.589 samples/sec, CrossEntropy=2.877, SmoothL1=1.290 [Epoch 42][Batch 1499], Speed: 351.926 samples/sec, CrossEntropy=2.877, SmoothL1=1.290 [Epoch 42][Batch 1599], Speed: 348.889 samples/sec, CrossEntropy=2.878, SmoothL1=1.289 [Epoch 42][Batch 1699], Speed: 358.631 samples/sec, CrossEntropy=2.877, SmoothL1=1.288 [Epoch 42][Batch 1799], Speed: 354.513 samples/sec, CrossEntropy=2.874, SmoothL1=1.288 [Epoch 42] Training cost: 336.293, CrossEntropy=2.874, SmoothL1=1.289 [Epoch 42] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.194 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.353 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.194 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.029 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.203 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.347 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.193 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.278 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.289 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.314 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.493 person=29.3 bicycle=12.9 car=16.0 motorcycle=21.8 airplane=38.4 bus=40.3 train=44.0 truck=16.5 boat=8.3 traffic light=5.4 fire hydrant=37.8 stop sign=41.9 parking meter=20.6 bench=10.6 bird=12.6 cat=46.2 dog=39.8 horse=33.1 sheep=25.3 cow=25.7 elephant=37.8 bear=44.9 zebra=41.3 giraffe=45.5 backpack=2.3 umbrella=17.2 handbag=1.8 tie=9.2 suitcase=12.0 frisbee=21.3 skis=7.9 snowboard=8.1 sports ball=13.4 kite=13.2 baseball bat=7.3 baseball glove=8.2 skateboard=21.1 surfboard=13.2 tennis racket=20.3 bottle=9.0 wine glass=9.3 cup=14.4 fork=7.5 knife=3.2 spoon=3.4 bowl=21.1 banana=11.3 apple=7.3 sandwich=24.4 orange=17.1 broccoli=10.8 carrot=7.3 hot dog=18.1 pizza=29.1 donut=20.0 cake=18.4 chair=9.3 couch=27.7 potted plant=10.4 bed=29.8 dining table=18.3 toilet=35.5 tv=35.4 laptop=36.4 mouse=23.0 remote=3.9 keyboard=27.1 cell phone=12.8 microwave=29.1 oven=20.4 toaster=0.0 sink=17.3 refrigerator=29.5 book=3.2 clock=24.7 vase=12.9 scissors=10.8 teddy bear=27.2 hair drier=0.0 toothbrush=3.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.4 [Epoch 43][Batch 99], Speed: 349.151 samples/sec, CrossEntropy=2.880, SmoothL1=1.268 [Epoch 43][Batch 199], Speed: 344.131 samples/sec, CrossEntropy=2.858, SmoothL1=1.266 [Epoch 43][Batch 299], Speed: 352.930 samples/sec, CrossEntropy=2.858, SmoothL1=1.273 [Epoch 43][Batch 399], Speed: 357.089 samples/sec, CrossEntropy=2.862, SmoothL1=1.277 [Epoch 43][Batch 499], Speed: 359.990 samples/sec, CrossEntropy=2.865, SmoothL1=1.283 [Epoch 43][Batch 599], Speed: 351.115 samples/sec, CrossEntropy=2.865, SmoothL1=1.290 [Epoch 43][Batch 699], Speed: 346.722 samples/sec, CrossEntropy=2.859, SmoothL1=1.287 [Epoch 43][Batch 799], Speed: 363.813 samples/sec, CrossEntropy=2.863, SmoothL1=1.286 [Epoch 43][Batch 899], Speed: 356.104 samples/sec, CrossEntropy=2.859, SmoothL1=1.283 [Epoch 43][Batch 999], Speed: 359.033 samples/sec, CrossEntropy=2.858, SmoothL1=1.281 [Epoch 43][Batch 1099], Speed: 353.784 samples/sec, CrossEntropy=2.862, SmoothL1=1.283 [Epoch 43][Batch 1199], Speed: 349.113 samples/sec, CrossEntropy=2.860, SmoothL1=1.279 [Epoch 43][Batch 1299], Speed: 354.856 samples/sec, CrossEntropy=2.861, SmoothL1=1.281 [Epoch 43][Batch 1399], Speed: 355.740 samples/sec, CrossEntropy=2.858, SmoothL1=1.278 [Epoch 43][Batch 1499], Speed: 348.902 samples/sec, CrossEntropy=2.856, SmoothL1=1.278 [Epoch 43][Batch 1599], Speed: 352.261 samples/sec, CrossEntropy=2.856, SmoothL1=1.279 [Epoch 43][Batch 1699], Speed: 345.685 samples/sec, CrossEntropy=2.855, SmoothL1=1.278 [Epoch 43][Batch 1799], Speed: 350.116 samples/sec, CrossEntropy=2.854, SmoothL1=1.277 [Epoch 43] Training cost: 335.784, CrossEntropy=2.854, SmoothL1=1.277 [Epoch 43] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.196 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.356 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.199 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.028 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.206 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.352 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.197 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.279 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.291 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.314 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.500 person=29.6 bicycle=13.0 car=16.0 motorcycle=21.1 airplane=38.6 bus=41.9 train=43.7 truck=16.9 boat=8.1 traffic light=4.8 fire hydrant=36.6 stop sign=42.2 parking meter=24.1 bench=10.5 bird=12.3 cat=45.8 dog=37.6 horse=31.5 sheep=25.4 cow=24.5 elephant=37.5 bear=49.9 zebra=39.8 giraffe=43.0 backpack=2.6 umbrella=17.6 handbag=1.6 tie=9.0 suitcase=12.3 frisbee=22.3 skis=7.9 snowboard=7.9 sports ball=14.4 kite=11.6 baseball bat=8.2 baseball glove=8.9 skateboard=19.9 surfboard=12.4 tennis racket=20.2 bottle=8.7 wine glass=10.0 cup=15.1 fork=7.6 knife=3.2 spoon=2.6 bowl=21.6 banana=11.0 apple=7.5 sandwich=25.4 orange=17.3 broccoli=13.1 carrot=6.4 hot dog=17.1 pizza=32.1 donut=22.0 cake=18.8 chair=9.4 couch=29.2 potted plant=8.7 bed=32.3 dining table=18.0 toilet=38.6 tv=37.2 laptop=38.8 mouse=25.6 remote=4.3 keyboard=26.7 cell phone=13.1 microwave=29.9 oven=19.9 toaster=0.0 sink=17.2 refrigerator=30.2 book=2.8 clock=25.9 vase=13.4 scissors=10.3 teddy bear=26.5 hair drier=0.0 toothbrush=2.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.6 [Epoch 44][Batch 99], Speed: 347.259 samples/sec, CrossEntropy=2.869, SmoothL1=1.271 [Epoch 44][Batch 199], Speed: 351.953 samples/sec, CrossEntropy=2.862, SmoothL1=1.275 [Epoch 44][Batch 299], Speed: 357.145 samples/sec, CrossEntropy=2.872, SmoothL1=1.276 [Epoch 44][Batch 399], Speed: 352.277 samples/sec, CrossEntropy=2.863, SmoothL1=1.270 [Epoch 44][Batch 499], Speed: 356.534 samples/sec, CrossEntropy=2.866, SmoothL1=1.276 [Epoch 44][Batch 599], Speed: 349.552 samples/sec, CrossEntropy=2.856, SmoothL1=1.275 [Epoch 44][Batch 699], Speed: 340.285 samples/sec, CrossEntropy=2.848, SmoothL1=1.273 [Epoch 44][Batch 799], Speed: 361.464 samples/sec, CrossEntropy=2.847, SmoothL1=1.277 [Epoch 44][Batch 899], Speed: 347.465 samples/sec, CrossEntropy=2.847, SmoothL1=1.279 [Epoch 44][Batch 999], Speed: 348.071 samples/sec, CrossEntropy=2.851, SmoothL1=1.280 [Epoch 44][Batch 1099], Speed: 347.472 samples/sec, CrossEntropy=2.850, SmoothL1=1.278 [Epoch 44][Batch 1199], Speed: 349.238 samples/sec, CrossEntropy=2.849, SmoothL1=1.277 [Epoch 44][Batch 1299], Speed: 360.314 samples/sec, CrossEntropy=2.850, SmoothL1=1.276 [Epoch 44][Batch 1399], Speed: 359.173 samples/sec, CrossEntropy=2.850, SmoothL1=1.276 [Epoch 44][Batch 1499], Speed: 358.647 samples/sec, CrossEntropy=2.847, SmoothL1=1.276 [Epoch 44][Batch 1599], Speed: 353.119 samples/sec, CrossEntropy=2.845, SmoothL1=1.275 [Epoch 44][Batch 1699], Speed: 357.226 samples/sec, CrossEntropy=2.846, SmoothL1=1.275 [Epoch 44][Batch 1799], Speed: 357.647 samples/sec, CrossEntropy=2.846, SmoothL1=1.275 [Epoch 44] Training cost: 334.953, CrossEntropy=2.846, SmoothL1=1.275 [Epoch 44] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.194 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.351 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.196 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.027 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.205 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.193 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.278 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.290 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.311 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.498 person=29.4 bicycle=12.9 car=15.8 motorcycle=21.6 airplane=37.9 bus=43.9 train=44.2 truck=16.4 boat=8.5 traffic light=5.3 fire hydrant=36.4 stop sign=39.9 parking meter=23.7 bench=10.6 bird=12.2 cat=46.1 dog=38.6 horse=32.9 sheep=25.3 cow=26.2 elephant=36.7 bear=48.1 zebra=41.9 giraffe=44.9 backpack=1.6 umbrella=16.1 handbag=1.9 tie=8.6 suitcase=13.5 frisbee=21.1 skis=8.0 snowboard=9.1 sports ball=13.8 kite=12.1 baseball bat=7.4 baseball glove=8.1 skateboard=20.3 surfboard=13.0 tennis racket=21.2 bottle=10.0 wine glass=9.2 cup=14.7 fork=7.1 knife=3.3 spoon=2.8 bowl=20.2 banana=10.3 apple=7.6 sandwich=23.3 orange=17.1 broccoli=11.2 carrot=6.8 hot dog=17.9 pizza=31.1 donut=21.1 cake=16.9 chair=9.6 couch=28.2 potted plant=9.0 bed=31.2 dining table=18.8 toilet=34.5 tv=37.4 laptop=37.6 mouse=24.5 remote=4.4 keyboard=24.0 cell phone=12.5 microwave=29.0 oven=19.8 toaster=0.0 sink=15.7 refrigerator=27.7 book=2.8 clock=25.8 vase=12.7 scissors=11.9 teddy bear=26.0 hair drier=0.0 toothbrush=2.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.4 [Epoch 45][Batch 99], Speed: 357.527 samples/sec, CrossEntropy=2.810, SmoothL1=1.230 [Epoch 45][Batch 199], Speed: 358.973 samples/sec, CrossEntropy=2.833, SmoothL1=1.261 [Epoch 45][Batch 299], Speed: 351.840 samples/sec, CrossEntropy=2.839, SmoothL1=1.261 [Epoch 45][Batch 399], Speed: 349.556 samples/sec, CrossEntropy=2.840, SmoothL1=1.266 [Epoch 45][Batch 499], Speed: 342.261 samples/sec, CrossEntropy=2.842, SmoothL1=1.267 [Epoch 45][Batch 599], Speed: 344.507 samples/sec, CrossEntropy=2.846, SmoothL1=1.269 [Epoch 45][Batch 699], Speed: 352.844 samples/sec, CrossEntropy=2.852, SmoothL1=1.269 [Epoch 45][Batch 799], Speed: 359.249 samples/sec, CrossEntropy=2.853, SmoothL1=1.270 [Epoch 45][Batch 899], Speed: 343.126 samples/sec, CrossEntropy=2.852, SmoothL1=1.274 [Epoch 45][Batch 999], Speed: 357.755 samples/sec, CrossEntropy=2.850, SmoothL1=1.277 [Epoch 45][Batch 1099], Speed: 355.776 samples/sec, CrossEntropy=2.852, SmoothL1=1.275 [Epoch 45][Batch 1199], Speed: 357.676 samples/sec, CrossEntropy=2.851, SmoothL1=1.273 [Epoch 45][Batch 1299], Speed: 359.349 samples/sec, CrossEntropy=2.846, SmoothL1=1.274 [Epoch 45][Batch 1399], Speed: 345.307 samples/sec, CrossEntropy=2.849, SmoothL1=1.276 [Epoch 45][Batch 1499], Speed: 349.661 samples/sec, CrossEntropy=2.847, SmoothL1=1.274 [Epoch 45][Batch 1599], Speed: 353.606 samples/sec, CrossEntropy=2.847, SmoothL1=1.274 [Epoch 45][Batch 1699], Speed: 334.775 samples/sec, CrossEntropy=2.847, SmoothL1=1.274 [Epoch 45][Batch 1799], Speed: 341.422 samples/sec, CrossEntropy=2.846, SmoothL1=1.273 [Epoch 45] Training cost: 335.059, CrossEntropy=2.845, SmoothL1=1.273 [Epoch 45] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.193 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.354 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.194 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.027 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.207 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.339 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.194 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.276 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.289 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.313 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.492 person=29.6 bicycle=12.5 car=16.1 motorcycle=23.1 airplane=37.5 bus=41.4 train=44.3 truck=16.7 boat=8.6 traffic light=5.3 fire hydrant=37.6 stop sign=38.0 parking meter=26.2 bench=11.0 bird=11.6 cat=47.4 dog=37.7 horse=32.2 sheep=26.0 cow=23.6 elephant=37.2 bear=47.4 zebra=42.8 giraffe=41.1 backpack=2.7 umbrella=17.7 handbag=1.6 tie=9.2 suitcase=13.5 frisbee=20.9 skis=8.6 snowboard=8.5 sports ball=14.2 kite=12.1 baseball bat=7.5 baseball glove=8.7 skateboard=18.7 surfboard=14.5 tennis racket=20.0 bottle=8.7 wine glass=9.1 cup=14.7 fork=7.2 knife=3.5 spoon=3.3 bowl=20.1 banana=10.1 apple=7.1 sandwich=23.6 orange=15.7 broccoli=11.0 carrot=7.1 hot dog=18.9 pizza=31.3 donut=21.1 cake=16.7 chair=9.7 couch=27.7 potted plant=8.5 bed=30.7 dining table=17.4 toilet=37.7 tv=37.0 laptop=36.9 mouse=22.8 remote=4.8 keyboard=28.4 cell phone=12.5 microwave=28.7 oven=19.6 toaster=0.0 sink=15.9 refrigerator=28.5 book=3.1 clock=25.8 vase=12.6 scissors=9.0 teddy bear=24.1 hair drier=0.0 toothbrush=2.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.3 [Epoch 46][Batch 99], Speed: 352.235 samples/sec, CrossEntropy=2.830, SmoothL1=1.253 [Epoch 46][Batch 199], Speed: 359.029 samples/sec, CrossEntropy=2.847, SmoothL1=1.267 [Epoch 46][Batch 299], Speed: 352.144 samples/sec, CrossEntropy=2.848, SmoothL1=1.282 [Epoch 46][Batch 399], Speed: 349.687 samples/sec, CrossEntropy=2.849, SmoothL1=1.278 [Epoch 46][Batch 499], Speed: 352.872 samples/sec, CrossEntropy=2.847, SmoothL1=1.270 [Epoch 46][Batch 599], Speed: 351.741 samples/sec, CrossEntropy=2.844, SmoothL1=1.271 [Epoch 46][Batch 699], Speed: 351.671 samples/sec, CrossEntropy=2.849, SmoothL1=1.273 [Epoch 46][Batch 799], Speed: 359.012 samples/sec, CrossEntropy=2.849, SmoothL1=1.276 [Epoch 46][Batch 899], Speed: 355.525 samples/sec, CrossEntropy=2.850, SmoothL1=1.273 [Epoch 46][Batch 999], Speed: 345.468 samples/sec, CrossEntropy=2.844, SmoothL1=1.267 [Epoch 46][Batch 1099], Speed: 359.096 samples/sec, CrossEntropy=2.844, SmoothL1=1.267 [Epoch 46][Batch 1199], Speed: 353.001 samples/sec, CrossEntropy=2.846, SmoothL1=1.270 [Epoch 46][Batch 1299], Speed: 349.161 samples/sec, CrossEntropy=2.843, SmoothL1=1.268 [Epoch 46][Batch 1399], Speed: 353.009 samples/sec, CrossEntropy=2.842, SmoothL1=1.268 [Epoch 46][Batch 1499], Speed: 352.408 samples/sec, CrossEntropy=2.841, SmoothL1=1.269 [Epoch 46][Batch 1599], Speed: 346.436 samples/sec, CrossEntropy=2.842, SmoothL1=1.268 [Epoch 46][Batch 1699], Speed: 337.427 samples/sec, CrossEntropy=2.844, SmoothL1=1.268 [Epoch 46][Batch 1799], Speed: 353.563 samples/sec, CrossEntropy=2.842, SmoothL1=1.268 [Epoch 46] Training cost: 334.928, CrossEntropy=2.842, SmoothL1=1.269 [Epoch 46] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.200 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.359 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.202 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.029 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.206 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.357 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.199 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.283 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.294 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.314 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.507 person=30.0 bicycle=12.9 car=16.2 motorcycle=22.2 airplane=38.7 bus=43.5 train=46.2 truck=17.5 boat=8.4 traffic light=5.3 fire hydrant=37.0 stop sign=40.7 parking meter=23.0 bench=10.8 bird=12.6 cat=50.9 dog=41.1 horse=31.9 sheep=24.8 cow=24.5 elephant=41.2 bear=50.1 zebra=41.1 giraffe=44.3 backpack=2.6 umbrella=17.1 handbag=1.9 tie=9.7 suitcase=12.9 frisbee=21.3 skis=8.0 snowboard=8.5 sports ball=14.4 kite=12.5 baseball bat=7.6 baseball glove=8.4 skateboard=21.5 surfboard=14.1 tennis racket=21.4 bottle=9.1 wine glass=9.7 cup=14.4 fork=7.2 knife=3.2 spoon=2.9 bowl=21.1 banana=10.2 apple=8.9 sandwich=26.8 orange=16.1 broccoli=13.3 carrot=6.9 hot dog=18.8 pizza=32.9 donut=21.0 cake=16.8 chair=10.3 couch=28.3 potted plant=9.4 bed=33.1 dining table=18.6 toilet=38.1 tv=38.2 laptop=37.5 mouse=24.6 remote=4.3 keyboard=26.9 cell phone=13.4 microwave=30.4 oven=21.7 toaster=0.0 sink=16.3 refrigerator=29.6 book=3.3 clock=25.7 vase=12.9 scissors=14.3 teddy bear=27.2 hair drier=0.0 toothbrush=3.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.0 [Epoch 47][Batch 99], Speed: 350.461 samples/sec, CrossEntropy=2.851, SmoothL1=1.297 [Epoch 47][Batch 199], Speed: 349.019 samples/sec, CrossEntropy=2.822, SmoothL1=1.268 [Epoch 47][Batch 299], Speed: 349.649 samples/sec, CrossEntropy=2.821, SmoothL1=1.259 [Epoch 47][Batch 399], Speed: 363.554 samples/sec, CrossEntropy=2.832, SmoothL1=1.268 [Epoch 47][Batch 499], Speed: 356.726 samples/sec, CrossEntropy=2.833, SmoothL1=1.270 [Epoch 47][Batch 599], Speed: 350.085 samples/sec, CrossEntropy=2.834, SmoothL1=1.276 [Epoch 47][Batch 699], Speed: 364.421 samples/sec, CrossEntropy=2.834, SmoothL1=1.279 [Epoch 47][Batch 799], Speed: 349.354 samples/sec, CrossEntropy=2.833, SmoothL1=1.275 [Epoch 47][Batch 899], Speed: 358.322 samples/sec, CrossEntropy=2.833, SmoothL1=1.277 [Epoch 47][Batch 999], Speed: 350.649 samples/sec, CrossEntropy=2.832, SmoothL1=1.278 [Epoch 47][Batch 1099], Speed: 346.107 samples/sec, CrossEntropy=2.832, SmoothL1=1.279 [Epoch 47][Batch 1199], Speed: 353.858 samples/sec, CrossEntropy=2.831, SmoothL1=1.274 [Epoch 47][Batch 1299], Speed: 359.684 samples/sec, CrossEntropy=2.829, SmoothL1=1.274 [Epoch 47][Batch 1399], Speed: 365.131 samples/sec, CrossEntropy=2.829, SmoothL1=1.274 [Epoch 47][Batch 1499], Speed: 353.635 samples/sec, CrossEntropy=2.829, SmoothL1=1.273 [Epoch 47][Batch 1599], Speed: 358.505 samples/sec, CrossEntropy=2.830, SmoothL1=1.272 [Epoch 47][Batch 1699], Speed: 347.465 samples/sec, CrossEntropy=2.829, SmoothL1=1.272 [Epoch 47][Batch 1799], Speed: 338.344 samples/sec, CrossEntropy=2.828, SmoothL1=1.271 [Epoch 47] Training cost: 334.510, CrossEntropy=2.827, SmoothL1=1.270 [Epoch 47] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.198 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.357 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.200 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.030 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.211 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.356 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.196 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.282 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.295 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.053 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.317 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.506 person=29.5 bicycle=12.8 car=16.4 motorcycle=21.4 airplane=37.2 bus=41.7 train=44.1 truck=16.4 boat=7.9 traffic light=5.8 fire hydrant=37.8 stop sign=40.4 parking meter=23.3 bench=11.1 bird=12.2 cat=49.2 dog=39.0 horse=32.3 sheep=25.9 cow=24.7 elephant=38.9 bear=45.8 zebra=42.0 giraffe=41.7 backpack=2.0 umbrella=17.7 handbag=1.7 tie=9.4 suitcase=12.1 frisbee=21.4 skis=8.3 snowboard=10.2 sports ball=14.6 kite=12.9 baseball bat=6.5 baseball glove=8.8 skateboard=22.4 surfboard=13.2 tennis racket=21.2 bottle=10.1 wine glass=9.7 cup=15.6 fork=7.9 knife=3.1 spoon=3.1 bowl=20.6 banana=11.7 apple=7.5 sandwich=23.9 orange=18.8 broccoli=11.6 carrot=6.7 hot dog=18.1 pizza=33.0 donut=22.4 cake=19.0 chair=9.6 couch=28.1 potted plant=9.9 bed=29.2 dining table=18.0 toilet=40.1 tv=37.6 laptop=37.0 mouse=25.6 remote=5.0 keyboard=28.5 cell phone=13.4 microwave=29.0 oven=20.0 toaster=0.0 sink=17.5 refrigerator=30.7 book=3.1 clock=25.5 vase=13.0 scissors=11.2 teddy bear=27.1 hair drier=0.0 toothbrush=4.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.8 [Epoch 48][Batch 99], Speed: 349.337 samples/sec, CrossEntropy=2.818, SmoothL1=1.279 [Epoch 48][Batch 199], Speed: 349.296 samples/sec, CrossEntropy=2.843, SmoothL1=1.279 [Epoch 48][Batch 299], Speed: 346.782 samples/sec, CrossEntropy=2.842, SmoothL1=1.265 [Epoch 48][Batch 399], Speed: 349.110 samples/sec, CrossEntropy=2.846, SmoothL1=1.276 [Epoch 48][Batch 499], Speed: 353.606 samples/sec, CrossEntropy=2.832, SmoothL1=1.271 [Epoch 48][Batch 599], Speed: 357.067 samples/sec, CrossEntropy=2.835, SmoothL1=1.274 [Epoch 48][Batch 699], Speed: 352.241 samples/sec, CrossEntropy=2.838, SmoothL1=1.274 [Epoch 48][Batch 799], Speed: 361.951 samples/sec, CrossEntropy=2.839, SmoothL1=1.271 [Epoch 48][Batch 899], Speed: 360.148 samples/sec, CrossEntropy=2.837, SmoothL1=1.272 [Epoch 48][Batch 999], Speed: 358.335 samples/sec, CrossEntropy=2.840, SmoothL1=1.273 [Epoch 48][Batch 1099], Speed: 353.239 samples/sec, CrossEntropy=2.840, SmoothL1=1.273 [Epoch 48][Batch 1199], Speed: 353.310 samples/sec, CrossEntropy=2.835, SmoothL1=1.271 [Epoch 48][Batch 1299], Speed: 350.772 samples/sec, CrossEntropy=2.834, SmoothL1=1.272 [Epoch 48][Batch 1399], Speed: 347.917 samples/sec, CrossEntropy=2.832, SmoothL1=1.269 [Epoch 48][Batch 1499], Speed: 361.183 samples/sec, CrossEntropy=2.832, SmoothL1=1.268 [Epoch 48][Batch 1599], Speed: 350.963 samples/sec, CrossEntropy=2.832, SmoothL1=1.267 [Epoch 48][Batch 1699], Speed: 340.174 samples/sec, CrossEntropy=2.830, SmoothL1=1.267 [Epoch 48][Batch 1799], Speed: 360.828 samples/sec, CrossEntropy=2.830, SmoothL1=1.267 [Epoch 48] Training cost: 335.790, CrossEntropy=2.829, SmoothL1=1.267 [Epoch 48] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.197 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.358 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.201 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.029 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.211 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.355 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.197 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.281 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.293 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.313 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.510 person=29.6 bicycle=14.2 car=16.3 motorcycle=22.2 airplane=38.1 bus=43.4 train=44.5 truck=16.2 boat=8.6 traffic light=5.1 fire hydrant=37.3 stop sign=38.2 parking meter=24.8 bench=10.4 bird=12.0 cat=47.4 dog=37.2 horse=33.0 sheep=25.3 cow=24.7 elephant=39.6 bear=44.0 zebra=40.3 giraffe=42.3 backpack=2.8 umbrella=18.5 handbag=2.0 tie=9.4 suitcase=12.6 frisbee=22.6 skis=9.4 snowboard=9.0 sports ball=14.6 kite=11.6 baseball bat=7.0 baseball glove=9.1 skateboard=19.7 surfboard=14.1 tennis racket=20.2 bottle=9.8 wine glass=10.0 cup=15.5 fork=7.8 knife=3.0 spoon=2.9 bowl=22.2 banana=10.1 apple=7.0 sandwich=25.3 orange=17.6 broccoli=11.7 carrot=7.0 hot dog=18.3 pizza=31.4 donut=21.5 cake=18.2 chair=10.1 couch=27.5 potted plant=9.1 bed=31.2 dining table=18.7 toilet=38.3 tv=37.5 laptop=37.0 mouse=23.1 remote=4.5 keyboard=25.6 cell phone=13.1 microwave=29.4 oven=21.1 toaster=3.6 sink=16.6 refrigerator=30.6 book=3.0 clock=25.7 vase=14.4 scissors=11.3 teddy bear=26.4 hair drier=0.0 toothbrush=3.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.7 [Epoch 49][Batch 99], Speed: 355.530 samples/sec, CrossEntropy=2.797, SmoothL1=1.251 [Epoch 49][Batch 199], Speed: 353.530 samples/sec, CrossEntropy=2.804, SmoothL1=1.243 [Epoch 49][Batch 299], Speed: 351.396 samples/sec, CrossEntropy=2.822, SmoothL1=1.248 [Epoch 49][Batch 399], Speed: 356.871 samples/sec, CrossEntropy=2.816, SmoothL1=1.241 [Epoch 49][Batch 499], Speed: 347.960 samples/sec, CrossEntropy=2.809, SmoothL1=1.245 [Epoch 49][Batch 599], Speed: 352.981 samples/sec, CrossEntropy=2.817, SmoothL1=1.251 [Epoch 49][Batch 699], Speed: 347.473 samples/sec, CrossEntropy=2.819, SmoothL1=1.253 [Epoch 49][Batch 799], Speed: 349.320 samples/sec, CrossEntropy=2.821, SmoothL1=1.251 [Epoch 49][Batch 899], Speed: 361.592 samples/sec, CrossEntropy=2.821, SmoothL1=1.250 [Epoch 49][Batch 999], Speed: 362.591 samples/sec, CrossEntropy=2.820, SmoothL1=1.250 [Epoch 49][Batch 1099], Speed: 352.881 samples/sec, CrossEntropy=2.821, SmoothL1=1.250 [Epoch 49][Batch 1199], Speed: 352.462 samples/sec, CrossEntropy=2.818, SmoothL1=1.251 [Epoch 49][Batch 1299], Speed: 359.191 samples/sec, CrossEntropy=2.812, SmoothL1=1.253 [Epoch 49][Batch 1399], Speed: 350.085 samples/sec, CrossEntropy=2.812, SmoothL1=1.252 [Epoch 49][Batch 1499], Speed: 356.019 samples/sec, CrossEntropy=2.810, SmoothL1=1.251 [Epoch 49][Batch 1599], Speed: 368.264 samples/sec, CrossEntropy=2.811, SmoothL1=1.251 [Epoch 49][Batch 1699], Speed: 352.108 samples/sec, CrossEntropy=2.812, SmoothL1=1.251 [Epoch 49][Batch 1799], Speed: 357.065 samples/sec, CrossEntropy=2.814, SmoothL1=1.253 [Epoch 49] Training cost: 335.473, CrossEntropy=2.816, SmoothL1=1.253 [Epoch 49] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.198 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.359 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.200 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.029 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.206 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.354 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.195 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.281 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.293 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.313 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.509 person=30.0 bicycle=12.7 car=16.1 motorcycle=22.6 airplane=38.1 bus=42.5 train=42.5 truck=16.8 boat=8.0 traffic light=5.4 fire hydrant=35.3 stop sign=39.4 parking meter=23.0 bench=10.8 bird=12.3 cat=45.9 dog=37.5 horse=33.6 sheep=26.1 cow=26.0 elephant=37.2 bear=47.0 zebra=41.4 giraffe=44.7 backpack=2.8 umbrella=18.6 handbag=1.6 tie=9.0 suitcase=12.0 frisbee=21.2 skis=7.8 snowboard=8.5 sports ball=14.3 kite=13.7 baseball bat=7.2 baseball glove=7.9 skateboard=19.0 surfboard=14.1 tennis racket=20.3 bottle=9.8 wine glass=10.0 cup=15.6 fork=7.9 knife=3.1 spoon=2.4 bowl=21.9 banana=10.7 apple=7.3 sandwich=26.9 orange=19.4 broccoli=14.4 carrot=7.7 hot dog=19.4 pizza=33.5 donut=21.9 cake=17.4 chair=10.0 couch=28.7 potted plant=10.3 bed=30.8 dining table=18.9 toilet=37.1 tv=36.3 laptop=38.4 mouse=24.4 remote=4.7 keyboard=27.2 cell phone=12.6 microwave=29.8 oven=18.8 toaster=0.0 sink=18.0 refrigerator=31.5 book=3.3 clock=24.8 vase=12.9 scissors=16.3 teddy bear=26.0 hair drier=0.0 toothbrush=1.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.8 [Epoch 50][Batch 99], Speed: 356.232 samples/sec, CrossEntropy=2.759, SmoothL1=1.222 [Epoch 50][Batch 199], Speed: 349.677 samples/sec, CrossEntropy=2.777, SmoothL1=1.235 [Epoch 50][Batch 299], Speed: 348.102 samples/sec, CrossEntropy=2.787, SmoothL1=1.231 [Epoch 50][Batch 399], Speed: 348.759 samples/sec, CrossEntropy=2.802, SmoothL1=1.238 [Epoch 50][Batch 499], Speed: 355.274 samples/sec, CrossEntropy=2.793, SmoothL1=1.236 [Epoch 50][Batch 599], Speed: 350.491 samples/sec, CrossEntropy=2.797, SmoothL1=1.239 [Epoch 50][Batch 699], Speed: 347.638 samples/sec, CrossEntropy=2.798, SmoothL1=1.241 [Epoch 50][Batch 799], Speed: 355.531 samples/sec, CrossEntropy=2.799, SmoothL1=1.241 [Epoch 50][Batch 899], Speed: 352.834 samples/sec, CrossEntropy=2.800, SmoothL1=1.243 [Epoch 50][Batch 999], Speed: 349.116 samples/sec, CrossEntropy=2.802, SmoothL1=1.248 [Epoch 50][Batch 1099], Speed: 347.990 samples/sec, CrossEntropy=2.805, SmoothL1=1.250 [Epoch 50][Batch 1199], Speed: 357.014 samples/sec, CrossEntropy=2.804, SmoothL1=1.249 [Epoch 50][Batch 1299], Speed: 358.872 samples/sec, CrossEntropy=2.802, SmoothL1=1.251 [Epoch 50][Batch 1399], Speed: 351.837 samples/sec, CrossEntropy=2.802, SmoothL1=1.251 [Epoch 50][Batch 1499], Speed: 344.689 samples/sec, CrossEntropy=2.803, SmoothL1=1.253 [Epoch 50][Batch 1599], Speed: 346.001 samples/sec, CrossEntropy=2.803, SmoothL1=1.253 [Epoch 50][Batch 1699], Speed: 360.535 samples/sec, CrossEntropy=2.803, SmoothL1=1.254 [Epoch 50][Batch 1799], Speed: 355.793 samples/sec, CrossEntropy=2.802, SmoothL1=1.254 [Epoch 50] Training cost: 335.486, CrossEntropy=2.801, SmoothL1=1.254 [Epoch 50] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.202 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.364 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.207 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.030 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.214 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.355 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.199 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.288 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.300 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.055 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.324 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.511 person=29.7 bicycle=13.3 car=16.4 motorcycle=23.5 airplane=38.9 bus=42.8 train=45.0 truck=17.3 boat=8.8 traffic light=5.4 fire hydrant=37.4 stop sign=41.6 parking meter=24.1 bench=10.9 bird=12.0 cat=47.3 dog=38.3 horse=32.0 sheep=26.8 cow=25.8 elephant=39.0 bear=48.9 zebra=42.1 giraffe=44.8 backpack=2.2 umbrella=17.3 handbag=1.6 tie=10.3 suitcase=13.2 frisbee=22.7 skis=7.9 snowboard=9.3 sports ball=15.0 kite=13.5 baseball bat=8.2 baseball glove=7.7 skateboard=20.1 surfboard=15.1 tennis racket=21.0 bottle=9.8 wine glass=10.0 cup=15.1 fork=7.8 knife=3.7 spoon=4.1 bowl=22.3 banana=11.2 apple=7.9 sandwich=25.3 orange=17.3 broccoli=13.2 carrot=7.2 hot dog=19.8 pizza=31.2 donut=23.2 cake=17.2 chair=10.7 couch=28.2 potted plant=10.2 bed=31.1 dining table=18.5 toilet=37.3 tv=37.4 laptop=40.2 mouse=25.1 remote=4.3 keyboard=29.0 cell phone=13.5 microwave=30.1 oven=21.3 toaster=0.0 sink=18.3 refrigerator=32.0 book=3.0 clock=25.3 vase=13.9 scissors=11.1 teddy bear=27.7 hair drier=0.0 toothbrush=3.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.2 [Epoch 51][Batch 99], Speed: 348.910 samples/sec, CrossEntropy=2.808, SmoothL1=1.261 [Epoch 51][Batch 199], Speed: 344.679 samples/sec, CrossEntropy=2.812, SmoothL1=1.263 [Epoch 51][Batch 299], Speed: 361.030 samples/sec, CrossEntropy=2.812, SmoothL1=1.263 [Epoch 51][Batch 399], Speed: 350.380 samples/sec, CrossEntropy=2.810, SmoothL1=1.248 [Epoch 51][Batch 499], Speed: 357.964 samples/sec, CrossEntropy=2.808, SmoothL1=1.242 [Epoch 51][Batch 599], Speed: 354.007 samples/sec, CrossEntropy=2.797, SmoothL1=1.246 [Epoch 51][Batch 699], Speed: 362.743 samples/sec, CrossEntropy=2.798, SmoothL1=1.249 [Epoch 51][Batch 799], Speed: 348.358 samples/sec, CrossEntropy=2.802, SmoothL1=1.252 [Epoch 51][Batch 899], Speed: 357.882 samples/sec, CrossEntropy=2.798, SmoothL1=1.249 [Epoch 51][Batch 999], Speed: 345.696 samples/sec, CrossEntropy=2.804, SmoothL1=1.250 [Epoch 51][Batch 1099], Speed: 351.926 samples/sec, CrossEntropy=2.804, SmoothL1=1.248 [Epoch 51][Batch 1199], Speed: 354.406 samples/sec, CrossEntropy=2.804, SmoothL1=1.249 [Epoch 51][Batch 1299], Speed: 360.566 samples/sec, CrossEntropy=2.803, SmoothL1=1.251 [Epoch 51][Batch 1399], Speed: 350.605 samples/sec, CrossEntropy=2.799, SmoothL1=1.249 [Epoch 51][Batch 1499], Speed: 363.657 samples/sec, CrossEntropy=2.798, SmoothL1=1.251 [Epoch 51][Batch 1599], Speed: 352.584 samples/sec, CrossEntropy=2.797, SmoothL1=1.249 [Epoch 51][Batch 1699], Speed: 346.455 samples/sec, CrossEntropy=2.798, SmoothL1=1.249 [Epoch 51][Batch 1799], Speed: 345.516 samples/sec, CrossEntropy=2.798, SmoothL1=1.249 [Epoch 51] Training cost: 335.157, CrossEntropy=2.797, SmoothL1=1.249 [Epoch 51] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.202 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.362 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.206 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.030 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.360 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.199 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.286 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.298 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.053 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.321 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.518 person=30.3 bicycle=14.1 car=16.5 motorcycle=22.5 airplane=38.2 bus=41.7 train=44.2 truck=17.7 boat=9.2 traffic light=5.3 fire hydrant=36.0 stop sign=40.5 parking meter=24.2 bench=10.6 bird=12.7 cat=47.4 dog=40.4 horse=32.7 sheep=26.2 cow=24.7 elephant=38.3 bear=47.2 zebra=42.9 giraffe=44.2 backpack=2.5 umbrella=17.1 handbag=1.7 tie=8.6 suitcase=13.8 frisbee=22.1 skis=8.8 snowboard=9.2 sports ball=15.4 kite=13.9 baseball bat=8.4 baseball glove=8.7 skateboard=21.7 surfboard=15.2 tennis racket=21.8 bottle=9.8 wine glass=10.3 cup=15.1 fork=8.2 knife=3.4 spoon=2.9 bowl=22.2 banana=10.8 apple=8.6 sandwich=26.5 orange=18.8 broccoli=14.2 carrot=7.0 hot dog=20.1 pizza=33.5 donut=21.2 cake=17.1 chair=9.8 couch=28.1 potted plant=9.5 bed=31.3 dining table=19.0 toilet=36.0 tv=37.7 laptop=38.1 mouse=24.4 remote=4.7 keyboard=28.1 cell phone=14.2 microwave=29.2 oven=21.8 toaster=0.0 sink=17.1 refrigerator=32.4 book=3.2 clock=27.2 vase=11.7 scissors=15.1 teddy bear=27.4 hair drier=0.0 toothbrush=3.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.2 [Epoch 52][Batch 99], Speed: 348.242 samples/sec, CrossEntropy=2.774, SmoothL1=1.248 [Epoch 52][Batch 199], Speed: 359.009 samples/sec, CrossEntropy=2.773, SmoothL1=1.223 [Epoch 52][Batch 299], Speed: 360.354 samples/sec, CrossEntropy=2.782, SmoothL1=1.233 [Epoch 52][Batch 399], Speed: 351.848 samples/sec, CrossEntropy=2.796, SmoothL1=1.245 [Epoch 52][Batch 499], Speed: 357.228 samples/sec, CrossEntropy=2.796, SmoothL1=1.250 [Epoch 52][Batch 599], Speed: 353.501 samples/sec, CrossEntropy=2.798, SmoothL1=1.250 [Epoch 52][Batch 699], Speed: 350.390 samples/sec, CrossEntropy=2.793, SmoothL1=1.248 [Epoch 52][Batch 799], Speed: 361.567 samples/sec, CrossEntropy=2.804, SmoothL1=1.252 [Epoch 52][Batch 899], Speed: 361.444 samples/sec, CrossEntropy=2.803, SmoothL1=1.254 [Epoch 52][Batch 999], Speed: 361.451 samples/sec, CrossEntropy=2.801, SmoothL1=1.252 [Epoch 52][Batch 1099], Speed: 346.217 samples/sec, CrossEntropy=2.796, SmoothL1=1.250 [Epoch 52][Batch 1199], Speed: 355.866 samples/sec, CrossEntropy=2.793, SmoothL1=1.251 [Epoch 52][Batch 1299], Speed: 365.250 samples/sec, CrossEntropy=2.793, SmoothL1=1.250 [Epoch 52][Batch 1399], Speed: 356.763 samples/sec, CrossEntropy=2.792, SmoothL1=1.248 [Epoch 52][Batch 1499], Speed: 348.975 samples/sec, CrossEntropy=2.793, SmoothL1=1.249 [Epoch 52][Batch 1599], Speed: 361.240 samples/sec, CrossEntropy=2.792, SmoothL1=1.250 [Epoch 52][Batch 1699], Speed: 358.032 samples/sec, CrossEntropy=2.790, SmoothL1=1.249 [Epoch 52][Batch 1799], Speed: 360.596 samples/sec, CrossEntropy=2.791, SmoothL1=1.249 [Epoch 52] Training cost: 334.908, CrossEntropy=2.793, SmoothL1=1.250 [Epoch 52] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.199 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.360 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.204 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.032 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.210 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.352 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.198 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.283 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.295 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.058 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.319 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.501 person=30.0 bicycle=14.0 car=16.3 motorcycle=21.8 airplane=37.1 bus=42.1 train=45.3 truck=16.1 boat=8.9 traffic light=5.2 fire hydrant=36.9 stop sign=40.8 parking meter=22.6 bench=10.7 bird=11.8 cat=48.5 dog=37.9 horse=31.7 sheep=26.4 cow=23.8 elephant=38.5 bear=48.7 zebra=41.1 giraffe=44.2 backpack=2.6 umbrella=18.2 handbag=1.6 tie=10.1 suitcase=12.3 frisbee=22.5 skis=8.2 snowboard=7.9 sports ball=13.8 kite=12.9 baseball bat=6.5 baseball glove=8.3 skateboard=19.1 surfboard=14.1 tennis racket=20.1 bottle=8.7 wine glass=9.5 cup=15.7 fork=8.3 knife=2.8 spoon=2.4 bowl=20.6 banana=11.1 apple=7.4 sandwich=25.7 orange=16.6 broccoli=13.3 carrot=7.3 hot dog=17.5 pizza=33.0 donut=21.8 cake=16.8 chair=10.8 couch=26.7 potted plant=9.5 bed=30.6 dining table=19.5 toilet=39.0 tv=36.9 laptop=38.0 mouse=24.5 remote=4.8 keyboard=29.8 cell phone=13.5 microwave=30.0 oven=20.4 toaster=5.9 sink=18.4 refrigerator=31.3 book=3.0 clock=25.8 vase=14.5 scissors=13.5 teddy bear=27.9 hair drier=0.0 toothbrush=4.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.9 [Epoch 53][Batch 99], Speed: 350.239 samples/sec, CrossEntropy=2.807, SmoothL1=1.250 [Epoch 53][Batch 199], Speed: 346.830 samples/sec, CrossEntropy=2.792, SmoothL1=1.247 [Epoch 53][Batch 299], Speed: 357.343 samples/sec, CrossEntropy=2.788, SmoothL1=1.244 [Epoch 53][Batch 399], Speed: 343.218 samples/sec, CrossEntropy=2.780, SmoothL1=1.239 [Epoch 53][Batch 499], Speed: 345.687 samples/sec, CrossEntropy=2.786, SmoothL1=1.247 [Epoch 53][Batch 599], Speed: 356.595 samples/sec, CrossEntropy=2.785, SmoothL1=1.246 [Epoch 53][Batch 699], Speed: 349.966 samples/sec, CrossEntropy=2.787, SmoothL1=1.249 [Epoch 53][Batch 799], Speed: 359.104 samples/sec, CrossEntropy=2.789, SmoothL1=1.250 [Epoch 53][Batch 899], Speed: 354.129 samples/sec, CrossEntropy=2.794, SmoothL1=1.253 [Epoch 53][Batch 999], Speed: 353.560 samples/sec, CrossEntropy=2.788, SmoothL1=1.249 [Epoch 53][Batch 1099], Speed: 360.365 samples/sec, CrossEntropy=2.784, SmoothL1=1.245 [Epoch 53][Batch 1199], Speed: 362.499 samples/sec, CrossEntropy=2.779, SmoothL1=1.243 [Epoch 53][Batch 1299], Speed: 347.075 samples/sec, CrossEntropy=2.777, SmoothL1=1.242 [Epoch 53][Batch 1399], Speed: 353.060 samples/sec, CrossEntropy=2.772, SmoothL1=1.239 [Epoch 53][Batch 1499], Speed: 358.650 samples/sec, CrossEntropy=2.774, SmoothL1=1.239 [Epoch 53][Batch 1599], Speed: 337.391 samples/sec, CrossEntropy=2.776, SmoothL1=1.239 [Epoch 53][Batch 1699], Speed: 351.250 samples/sec, CrossEntropy=2.776, SmoothL1=1.238 [Epoch 53][Batch 1799], Speed: 344.335 samples/sec, CrossEntropy=2.777, SmoothL1=1.239 [Epoch 53] Training cost: 335.485, CrossEntropy=2.779, SmoothL1=1.239 [Epoch 53] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.198 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.360 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.202 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.031 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.204 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.350 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.197 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.282 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.293 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.055 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.311 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.499 person=30.1 bicycle=12.8 car=16.4 motorcycle=22.5 airplane=38.5 bus=43.9 train=45.8 truck=15.9 boat=9.3 traffic light=5.1 fire hydrant=38.1 stop sign=40.0 parking meter=24.8 bench=10.3 bird=11.8 cat=45.2 dog=39.2 horse=32.5 sheep=25.0 cow=26.7 elephant=36.8 bear=45.2 zebra=42.1 giraffe=42.6 backpack=2.8 umbrella=17.3 handbag=1.5 tie=9.9 suitcase=13.4 frisbee=21.1 skis=8.4 snowboard=7.6 sports ball=14.6 kite=12.7 baseball bat=7.9 baseball glove=7.8 skateboard=20.0 surfboard=13.9 tennis racket=20.7 bottle=9.7 wine glass=9.6 cup=15.9 fork=8.5 knife=3.0 spoon=3.4 bowl=21.8 banana=10.9 apple=7.9 sandwich=24.0 orange=17.3 broccoli=11.7 carrot=7.2 hot dog=15.0 pizza=32.4 donut=21.2 cake=15.6 chair=10.5 couch=27.7 potted plant=10.9 bed=32.1 dining table=18.8 toilet=38.8 tv=35.6 laptop=37.8 mouse=23.8 remote=4.5 keyboard=28.4 cell phone=13.2 microwave=28.0 oven=21.6 toaster=0.0 sink=17.0 refrigerator=31.2 book=3.2 clock=25.6 vase=14.4 scissors=15.2 teddy bear=27.3 hair drier=0.0 toothbrush=2.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =19.8 [Epoch 54][Batch 99], Speed: 352.363 samples/sec, CrossEntropy=2.784, SmoothL1=1.265 [Epoch 54][Batch 199], Speed: 354.002 samples/sec, CrossEntropy=2.772, SmoothL1=1.244 [Epoch 54][Batch 299], Speed: 360.690 samples/sec, CrossEntropy=2.771, SmoothL1=1.240 [Epoch 54][Batch 399], Speed: 352.867 samples/sec, CrossEntropy=2.780, SmoothL1=1.245 [Epoch 54][Batch 499], Speed: 356.733 samples/sec, CrossEntropy=2.779, SmoothL1=1.243 [Epoch 54][Batch 599], Speed: 353.326 samples/sec, CrossEntropy=2.777, SmoothL1=1.239 [Epoch 54][Batch 699], Speed: 350.391 samples/sec, CrossEntropy=2.776, SmoothL1=1.239 [Epoch 54][Batch 799], Speed: 353.444 samples/sec, CrossEntropy=2.784, SmoothL1=1.241 [Epoch 54][Batch 899], Speed: 358.836 samples/sec, CrossEntropy=2.786, SmoothL1=1.241 [Epoch 54][Batch 999], Speed: 340.564 samples/sec, CrossEntropy=2.788, SmoothL1=1.240 [Epoch 54][Batch 1099], Speed: 358.975 samples/sec, CrossEntropy=2.786, SmoothL1=1.241 [Epoch 54][Batch 1199], Speed: 359.247 samples/sec, CrossEntropy=2.785, SmoothL1=1.241 [Epoch 54][Batch 1299], Speed: 353.096 samples/sec, CrossEntropy=2.784, SmoothL1=1.241 [Epoch 54][Batch 1399], Speed: 350.773 samples/sec, CrossEntropy=2.783, SmoothL1=1.242 [Epoch 54][Batch 1499], Speed: 355.607 samples/sec, CrossEntropy=2.780, SmoothL1=1.239 [Epoch 54][Batch 1599], Speed: 348.732 samples/sec, CrossEntropy=2.780, SmoothL1=1.239 [Epoch 54][Batch 1699], Speed: 358.215 samples/sec, CrossEntropy=2.779, SmoothL1=1.239 [Epoch 54][Batch 1799], Speed: 359.381 samples/sec, CrossEntropy=2.780, SmoothL1=1.239 [Epoch 54] Training cost: 334.848, CrossEntropy=2.779, SmoothL1=1.239 [Epoch 54] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.202 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.361 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.206 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.030 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.213 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.356 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.200 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.285 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.296 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.054 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.320 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.505 person=29.6 bicycle=13.0 car=16.5 motorcycle=21.8 airplane=38.8 bus=42.9 train=42.5 truck=17.1 boat=8.9 traffic light=5.0 fire hydrant=36.6 stop sign=39.7 parking meter=23.0 bench=10.8 bird=11.4 cat=46.8 dog=38.6 horse=33.5 sheep=26.2 cow=23.8 elephant=38.4 bear=48.7 zebra=43.1 giraffe=44.5 backpack=3.2 umbrella=18.2 handbag=1.7 tie=9.4 suitcase=13.4 frisbee=21.4 skis=8.2 snowboard=8.9 sports ball=15.0 kite=13.6 baseball bat=8.0 baseball glove=9.9 skateboard=19.1 surfboard=14.4 tennis racket=21.8 bottle=9.7 wine glass=9.6 cup=15.5 fork=9.2 knife=3.1 spoon=3.1 bowl=21.7 banana=11.6 apple=8.5 sandwich=25.7 orange=18.6 broccoli=12.2 carrot=8.1 hot dog=16.3 pizza=31.7 donut=22.1 cake=16.2 chair=10.0 couch=29.8 potted plant=10.6 bed=31.8 dining table=18.5 toilet=39.7 tv=37.4 laptop=39.2 mouse=24.4 remote=5.5 keyboard=28.5 cell phone=13.2 microwave=30.0 oven=21.5 toaster=8.3 sink=19.0 refrigerator=30.2 book=3.1 clock=25.6 vase=13.8 scissors=12.3 teddy bear=27.6 hair drier=0.0 toothbrush=3.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.2 [Epoch 55][Batch 99], Speed: 350.167 samples/sec, CrossEntropy=2.771, SmoothL1=1.242 [Epoch 55][Batch 199], Speed: 343.157 samples/sec, CrossEntropy=2.790, SmoothL1=1.255 [Epoch 55][Batch 299], Speed: 358.323 samples/sec, CrossEntropy=2.776, SmoothL1=1.254 [Epoch 55][Batch 399], Speed: 363.733 samples/sec, CrossEntropy=2.773, SmoothL1=1.249 [Epoch 55][Batch 499], Speed: 353.585 samples/sec, CrossEntropy=2.779, SmoothL1=1.246 [Epoch 55][Batch 599], Speed: 354.741 samples/sec, CrossEntropy=2.773, SmoothL1=1.242 [Epoch 55][Batch 699], Speed: 351.828 samples/sec, CrossEntropy=2.771, SmoothL1=1.239 [Epoch 55][Batch 799], Speed: 357.425 samples/sec, CrossEntropy=2.767, SmoothL1=1.239 [Epoch 55][Batch 899], Speed: 358.530 samples/sec, CrossEntropy=2.772, SmoothL1=1.240 [Epoch 55][Batch 999], Speed: 353.445 samples/sec, CrossEntropy=2.773, SmoothL1=1.243 [Epoch 55][Batch 1099], Speed: 354.578 samples/sec, CrossEntropy=2.771, SmoothL1=1.241 [Epoch 55][Batch 1199], Speed: 355.611 samples/sec, CrossEntropy=2.773, SmoothL1=1.240 [Epoch 55][Batch 1299], Speed: 360.375 samples/sec, CrossEntropy=2.773, SmoothL1=1.238 [Epoch 55][Batch 1399], Speed: 359.398 samples/sec, CrossEntropy=2.775, SmoothL1=1.239 [Epoch 55][Batch 1499], Speed: 353.576 samples/sec, CrossEntropy=2.776, SmoothL1=1.238 [Epoch 55][Batch 1599], Speed: 345.676 samples/sec, CrossEntropy=2.773, SmoothL1=1.237 [Epoch 55][Batch 1699], Speed: 344.486 samples/sec, CrossEntropy=2.775, SmoothL1=1.238 [Epoch 55][Batch 1799], Speed: 348.252 samples/sec, CrossEntropy=2.777, SmoothL1=1.239 [Epoch 55] Training cost: 334.704, CrossEntropy=2.776, SmoothL1=1.239 [Epoch 55] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.203 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.363 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.208 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.028 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.213 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.361 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.199 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.284 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.296 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.053 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.321 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.510 person=29.8 bicycle=12.8 car=16.7 motorcycle=21.8 airplane=40.4 bus=42.5 train=46.4 truck=17.6 boat=8.6 traffic light=5.6 fire hydrant=40.1 stop sign=41.7 parking meter=26.1 bench=11.3 bird=12.4 cat=48.4 dog=41.5 horse=33.2 sheep=25.9 cow=26.2 elephant=37.4 bear=49.9 zebra=43.0 giraffe=43.5 backpack=1.9 umbrella=18.0 handbag=2.1 tie=9.9 suitcase=12.7 frisbee=22.7 skis=8.6 snowboard=9.6 sports ball=13.5 kite=13.6 baseball bat=6.8 baseball glove=8.5 skateboard=21.0 surfboard=13.6 tennis racket=21.7 bottle=10.5 wine glass=10.2 cup=16.4 fork=9.4 knife=3.4 spoon=3.0 bowl=20.8 banana=12.2 apple=9.2 sandwich=26.5 orange=17.5 broccoli=12.6 carrot=7.6 hot dog=17.6 pizza=29.5 donut=23.1 cake=16.2 chair=9.9 couch=30.5 potted plant=9.6 bed=30.9 dining table=19.2 toilet=39.6 tv=37.2 laptop=38.6 mouse=24.5 remote=4.9 keyboard=27.6 cell phone=12.2 microwave=28.6 oven=21.1 toaster=0.0 sink=17.7 refrigerator=33.7 book=2.8 clock=26.5 vase=13.4 scissors=14.3 teddy bear=27.9 hair drier=0.0 toothbrush=2.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.3 [Epoch 56][Batch 99], Speed: 353.419 samples/sec, CrossEntropy=2.746, SmoothL1=1.229 [Epoch 56][Batch 199], Speed: 357.417 samples/sec, CrossEntropy=2.770, SmoothL1=1.240 [Epoch 56][Batch 299], Speed: 350.263 samples/sec, CrossEntropy=2.763, SmoothL1=1.231 [Epoch 56][Batch 399], Speed: 357.255 samples/sec, CrossEntropy=2.762, SmoothL1=1.232 [Epoch 56][Batch 499], Speed: 351.520 samples/sec, CrossEntropy=2.760, SmoothL1=1.238 [Epoch 56][Batch 599], Speed: 349.420 samples/sec, CrossEntropy=2.758, SmoothL1=1.237 [Epoch 56][Batch 699], Speed: 345.653 samples/sec, CrossEntropy=2.762, SmoothL1=1.241 [Epoch 56][Batch 799], Speed: 348.288 samples/sec, CrossEntropy=2.768, SmoothL1=1.247 [Epoch 56][Batch 899], Speed: 351.301 samples/sec, CrossEntropy=2.769, SmoothL1=1.242 [Epoch 56][Batch 999], Speed: 347.495 samples/sec, CrossEntropy=2.765, SmoothL1=1.236 [Epoch 56][Batch 1099], Speed: 353.344 samples/sec, CrossEntropy=2.762, SmoothL1=1.235 [Epoch 56][Batch 1199], Speed: 356.128 samples/sec, CrossEntropy=2.765, SmoothL1=1.237 [Epoch 56][Batch 1299], Speed: 347.555 samples/sec, CrossEntropy=2.764, SmoothL1=1.235 [Epoch 56][Batch 1399], Speed: 356.932 samples/sec, CrossEntropy=2.763, SmoothL1=1.236 [Epoch 56][Batch 1499], Speed: 357.299 samples/sec, CrossEntropy=2.763, SmoothL1=1.236 [Epoch 56][Batch 1599], Speed: 344.382 samples/sec, CrossEntropy=2.761, SmoothL1=1.237 [Epoch 56][Batch 1699], Speed: 348.503 samples/sec, CrossEntropy=2.762, SmoothL1=1.237 [Epoch 56][Batch 1799], Speed: 361.240 samples/sec, CrossEntropy=2.761, SmoothL1=1.236 [Epoch 56] Training cost: 335.525, CrossEntropy=2.764, SmoothL1=1.238 [Epoch 56] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.201 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.361 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.205 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.031 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.209 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.357 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.198 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.282 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.295 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.317 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.507 person=30.3 bicycle=13.6 car=16.8 motorcycle=23.7 airplane=39.2 bus=44.5 train=46.6 truck=16.6 boat=8.9 traffic light=5.6 fire hydrant=36.7 stop sign=42.1 parking meter=23.0 bench=10.6 bird=12.1 cat=45.3 dog=40.2 horse=33.1 sheep=27.0 cow=24.6 elephant=38.8 bear=44.5 zebra=43.2 giraffe=44.2 backpack=2.8 umbrella=17.3 handbag=1.6 tie=9.8 suitcase=12.7 frisbee=21.6 skis=8.2 snowboard=9.2 sports ball=15.5 kite=12.2 baseball bat=7.9 baseball glove=9.7 skateboard=20.6 surfboard=15.4 tennis racket=20.8 bottle=10.4 wine glass=10.0 cup=15.5 fork=8.8 knife=3.4 spoon=2.6 bowl=20.3 banana=10.0 apple=8.3 sandwich=24.6 orange=18.5 broccoli=10.8 carrot=7.3 hot dog=16.7 pizza=33.0 donut=20.0 cake=17.4 chair=9.6 couch=30.1 potted plant=9.9 bed=33.2 dining table=19.1 toilet=38.7 tv=36.8 laptop=37.6 mouse=24.0 remote=4.0 keyboard=27.9 cell phone=11.9 microwave=27.4 oven=22.9 toaster=0.0 sink=17.7 refrigerator=31.8 book=2.8 clock=26.3 vase=13.6 scissors=14.6 teddy bear=26.7 hair drier=0.0 toothbrush=3.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.1 [Epoch 57][Batch 99], Speed: 359.086 samples/sec, CrossEntropy=2.786, SmoothL1=1.244 [Epoch 57][Batch 199], Speed: 354.025 samples/sec, CrossEntropy=2.777, SmoothL1=1.235 [Epoch 57][Batch 299], Speed: 352.125 samples/sec, CrossEntropy=2.769, SmoothL1=1.241 [Epoch 57][Batch 399], Speed: 357.497 samples/sec, CrossEntropy=2.770, SmoothL1=1.228 [Epoch 57][Batch 499], Speed: 350.262 samples/sec, CrossEntropy=2.773, SmoothL1=1.222 [Epoch 57][Batch 599], Speed: 349.441 samples/sec, CrossEntropy=2.770, SmoothL1=1.220 [Epoch 57][Batch 699], Speed: 361.291 samples/sec, CrossEntropy=2.765, SmoothL1=1.220 [Epoch 57][Batch 799], Speed: 355.949 samples/sec, CrossEntropy=2.762, SmoothL1=1.219 [Epoch 57][Batch 899], Speed: 348.435 samples/sec, CrossEntropy=2.760, SmoothL1=1.219 [Epoch 57][Batch 999], Speed: 353.257 samples/sec, CrossEntropy=2.758, SmoothL1=1.219 [Epoch 57][Batch 1099], Speed: 360.840 samples/sec, CrossEntropy=2.759, SmoothL1=1.220 [Epoch 57][Batch 1199], Speed: 350.870 samples/sec, CrossEntropy=2.756, SmoothL1=1.221 [Epoch 57][Batch 1299], Speed: 345.418 samples/sec, CrossEntropy=2.756, SmoothL1=1.222 [Epoch 57][Batch 1399], Speed: 348.583 samples/sec, CrossEntropy=2.758, SmoothL1=1.225 [Epoch 57][Batch 1499], Speed: 355.635 samples/sec, CrossEntropy=2.757, SmoothL1=1.226 [Epoch 57][Batch 1599], Speed: 356.243 samples/sec, CrossEntropy=2.755, SmoothL1=1.226 [Epoch 57][Batch 1699], Speed: 363.844 samples/sec, CrossEntropy=2.756, SmoothL1=1.226 [Epoch 57][Batch 1799], Speed: 349.301 samples/sec, CrossEntropy=2.756, SmoothL1=1.227 [Epoch 57] Training cost: 334.630, CrossEntropy=2.757, SmoothL1=1.226 [Epoch 57] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.202 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.362 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.206 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.033 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.217 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.352 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.199 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.287 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.300 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.057 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.330 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.505 person=30.1 bicycle=13.1 car=16.8 motorcycle=21.1 airplane=37.0 bus=42.7 train=43.0 truck=17.5 boat=8.2 traffic light=6.4 fire hydrant=36.7 stop sign=42.2 parking meter=24.3 bench=11.4 bird=13.1 cat=48.7 dog=40.0 horse=33.6 sheep=25.6 cow=26.1 elephant=37.8 bear=49.6 zebra=43.7 giraffe=44.6 backpack=1.9 umbrella=16.7 handbag=1.7 tie=10.3 suitcase=12.4 frisbee=22.1 skis=8.7 snowboard=11.2 sports ball=14.4 kite=13.6 baseball bat=8.9 baseball glove=9.3 skateboard=21.1 surfboard=13.8 tennis racket=20.2 bottle=9.6 wine glass=9.3 cup=16.0 fork=7.8 knife=3.2 spoon=3.0 bowl=21.3 banana=10.5 apple=6.2 sandwich=27.2 orange=18.5 broccoli=13.5 carrot=6.9 hot dog=15.1 pizza=29.7 donut=21.6 cake=17.7 chair=9.4 couch=27.4 potted plant=9.7 bed=30.9 dining table=18.8 toilet=39.9 tv=37.6 laptop=40.4 mouse=24.2 remote=5.5 keyboard=28.4 cell phone=13.9 microwave=29.7 oven=21.0 toaster=7.1 sink=17.1 refrigerator=31.5 book=3.6 clock=25.9 vase=13.4 scissors=12.6 teddy bear=26.5 hair drier=0.0 toothbrush=3.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.2 [Epoch 58][Batch 99], Speed: 360.018 samples/sec, CrossEntropy=2.749, SmoothL1=1.226 [Epoch 58][Batch 199], Speed: 347.900 samples/sec, CrossEntropy=2.769, SmoothL1=1.223 [Epoch 58][Batch 299], Speed: 357.856 samples/sec, CrossEntropy=2.773, SmoothL1=1.228 [Epoch 58][Batch 399], Speed: 354.165 samples/sec, CrossEntropy=2.773, SmoothL1=1.238 [Epoch 58][Batch 499], Speed: 349.040 samples/sec, CrossEntropy=2.772, SmoothL1=1.244 [Epoch 58][Batch 599], Speed: 346.401 samples/sec, CrossEntropy=2.772, SmoothL1=1.242 [Epoch 58][Batch 699], Speed: 359.504 samples/sec, CrossEntropy=2.766, SmoothL1=1.238 [Epoch 58][Batch 799], Speed: 360.942 samples/sec, CrossEntropy=2.767, SmoothL1=1.235 [Epoch 58][Batch 899], Speed: 358.252 samples/sec, CrossEntropy=2.767, SmoothL1=1.229 [Epoch 58][Batch 999], Speed: 352.284 samples/sec, CrossEntropy=2.766, SmoothL1=1.231 [Epoch 58][Batch 1099], Speed: 346.036 samples/sec, CrossEntropy=2.759, SmoothL1=1.227 [Epoch 58][Batch 1199], Speed: 344.936 samples/sec, CrossEntropy=2.755, SmoothL1=1.225 [Epoch 58][Batch 1299], Speed: 353.573 samples/sec, CrossEntropy=2.756, SmoothL1=1.224 [Epoch 58][Batch 1399], Speed: 347.563 samples/sec, CrossEntropy=2.759, SmoothL1=1.225 [Epoch 58][Batch 1499], Speed: 349.393 samples/sec, CrossEntropy=2.762, SmoothL1=1.227 [Epoch 58][Batch 1599], Speed: 347.175 samples/sec, CrossEntropy=2.761, SmoothL1=1.228 [Epoch 58][Batch 1699], Speed: 362.269 samples/sec, CrossEntropy=2.760, SmoothL1=1.228 [Epoch 58][Batch 1799], Speed: 349.970 samples/sec, CrossEntropy=2.762, SmoothL1=1.228 [Epoch 58] Training cost: 335.288, CrossEntropy=2.763, SmoothL1=1.228 [Epoch 58] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.205 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.367 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.209 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.033 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.364 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.203 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.290 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.302 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.057 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.326 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.509 person=30.2 bicycle=14.3 car=17.0 motorcycle=23.3 airplane=38.5 bus=43.8 train=45.9 truck=17.2 boat=8.1 traffic light=6.1 fire hydrant=36.3 stop sign=41.9 parking meter=24.5 bench=11.7 bird=13.1 cat=50.1 dog=42.0 horse=33.2 sheep=27.4 cow=28.4 elephant=36.6 bear=44.9 zebra=41.7 giraffe=45.0 backpack=2.3 umbrella=17.2 handbag=2.1 tie=9.3 suitcase=13.2 frisbee=23.8 skis=7.9 snowboard=10.6 sports ball=15.3 kite=14.1 baseball bat=8.8 baseball glove=10.7 skateboard=19.3 surfboard=13.8 tennis racket=22.1 bottle=9.9 wine glass=10.0 cup=15.6 fork=7.8 knife=3.5 spoon=3.7 bowl=22.2 banana=10.9 apple=7.1 sandwich=26.5 orange=16.2 broccoli=12.7 carrot=7.7 hot dog=16.3 pizza=33.2 donut=22.4 cake=17.1 chair=10.4 couch=29.6 potted plant=10.3 bed=33.0 dining table=19.3 toilet=39.0 tv=37.9 laptop=40.2 mouse=24.1 remote=5.0 keyboard=28.5 cell phone=14.1 microwave=29.6 oven=22.6 toaster=0.0 sink=18.0 refrigerator=31.8 book=2.9 clock=26.9 vase=13.3 scissors=17.6 teddy bear=27.1 hair drier=0.0 toothbrush=4.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.5 [Epoch 59][Batch 99], Speed: 348.412 samples/sec, CrossEntropy=2.718, SmoothL1=1.204 [Epoch 59][Batch 199], Speed: 350.670 samples/sec, CrossEntropy=2.739, SmoothL1=1.225 [Epoch 59][Batch 299], Speed: 344.090 samples/sec, CrossEntropy=2.752, SmoothL1=1.235 [Epoch 59][Batch 399], Speed: 340.499 samples/sec, CrossEntropy=2.753, SmoothL1=1.235 [Epoch 59][Batch 499], Speed: 343.050 samples/sec, CrossEntropy=2.754, SmoothL1=1.236 [Epoch 59][Batch 599], Speed: 356.535 samples/sec, CrossEntropy=2.749, SmoothL1=1.235 [Epoch 59][Batch 699], Speed: 343.772 samples/sec, CrossEntropy=2.754, SmoothL1=1.237 [Epoch 59][Batch 799], Speed: 360.520 samples/sec, CrossEntropy=2.760, SmoothL1=1.235 [Epoch 59][Batch 899], Speed: 359.708 samples/sec, CrossEntropy=2.759, SmoothL1=1.232 [Epoch 59][Batch 999], Speed: 348.712 samples/sec, CrossEntropy=2.759, SmoothL1=1.232 [Epoch 59][Batch 1099], Speed: 344.259 samples/sec, CrossEntropy=2.758, SmoothL1=1.232 [Epoch 59][Batch 1199], Speed: 359.477 samples/sec, CrossEntropy=2.755, SmoothL1=1.229 [Epoch 59][Batch 1299], Speed: 350.474 samples/sec, CrossEntropy=2.752, SmoothL1=1.227 [Epoch 59][Batch 1399], Speed: 359.496 samples/sec, CrossEntropy=2.751, SmoothL1=1.226 [Epoch 59][Batch 1499], Speed: 350.190 samples/sec, CrossEntropy=2.750, SmoothL1=1.225 [Epoch 59][Batch 1599], Speed: 348.473 samples/sec, CrossEntropy=2.748, SmoothL1=1.223 [Epoch 59][Batch 1699], Speed: 347.369 samples/sec, CrossEntropy=2.752, SmoothL1=1.223 [Epoch 59][Batch 1799], Speed: 345.335 samples/sec, CrossEntropy=2.752, SmoothL1=1.225 [Epoch 59] Training cost: 334.632, CrossEntropy=2.752, SmoothL1=1.224 [Epoch 59] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.205 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.367 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.210 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.031 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.217 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.363 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.201 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.289 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.301 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.054 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.326 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.518 person=30.2 bicycle=14.5 car=16.8 motorcycle=23.1 airplane=40.1 bus=41.8 train=47.6 truck=17.5 boat=8.4 traffic light=5.8 fire hydrant=39.6 stop sign=43.0 parking meter=24.9 bench=11.0 bird=12.1 cat=49.0 dog=41.8 horse=34.5 sheep=26.9 cow=28.2 elephant=38.4 bear=48.0 zebra=42.5 giraffe=45.0 backpack=2.1 umbrella=18.3 handbag=2.3 tie=9.3 suitcase=13.7 frisbee=21.5 skis=8.6 snowboard=9.0 sports ball=14.4 kite=12.0 baseball bat=8.0 baseball glove=8.9 skateboard=20.7 surfboard=14.2 tennis racket=21.1 bottle=10.0 wine glass=10.0 cup=16.0 fork=9.5 knife=3.6 spoon=3.6 bowl=21.3 banana=12.3 apple=8.6 sandwich=25.5 orange=14.1 broccoli=12.4 carrot=8.2 hot dog=19.3 pizza=31.9 donut=21.8 cake=17.7 chair=10.4 couch=31.2 potted plant=10.1 bed=30.8 dining table=18.3 toilet=38.9 tv=39.7 laptop=39.9 mouse=23.1 remote=5.6 keyboard=30.6 cell phone=12.9 microwave=29.5 oven=21.7 toaster=0.0 sink=19.0 refrigerator=32.7 book=3.3 clock=25.9 vase=13.4 scissors=16.0 teddy bear=27.1 hair drier=0.0 toothbrush=2.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.5 [Epoch 60][Batch 99], Speed: 353.646 samples/sec, CrossEntropy=2.787, SmoothL1=1.244 [Epoch 60][Batch 199], Speed: 346.748 samples/sec, CrossEntropy=2.776, SmoothL1=1.228 [Epoch 60][Batch 299], Speed: 363.666 samples/sec, CrossEntropy=2.784, SmoothL1=1.228 [Epoch 60][Batch 399], Speed: 357.582 samples/sec, CrossEntropy=2.780, SmoothL1=1.228 [Epoch 60][Batch 499], Speed: 341.787 samples/sec, CrossEntropy=2.776, SmoothL1=1.229 [Epoch 60][Batch 599], Speed: 357.873 samples/sec, CrossEntropy=2.773, SmoothL1=1.228 [Epoch 60][Batch 699], Speed: 346.874 samples/sec, CrossEntropy=2.765, SmoothL1=1.227 [Epoch 60][Batch 799], Speed: 349.872 samples/sec, CrossEntropy=2.766, SmoothL1=1.225 [Epoch 60][Batch 899], Speed: 345.864 samples/sec, CrossEntropy=2.766, SmoothL1=1.226 [Epoch 60][Batch 999], Speed: 362.137 samples/sec, CrossEntropy=2.761, SmoothL1=1.227 [Epoch 60][Batch 1099], Speed: 349.112 samples/sec, CrossEntropy=2.757, SmoothL1=1.226 [Epoch 60][Batch 1199], Speed: 359.890 samples/sec, CrossEntropy=2.753, SmoothL1=1.224 [Epoch 60][Batch 1299], Speed: 366.260 samples/sec, CrossEntropy=2.752, SmoothL1=1.224 [Epoch 60][Batch 1399], Speed: 358.652 samples/sec, CrossEntropy=2.748, SmoothL1=1.221 [Epoch 60][Batch 1499], Speed: 352.522 samples/sec, CrossEntropy=2.746, SmoothL1=1.220 [Epoch 60][Batch 1599], Speed: 347.289 samples/sec, CrossEntropy=2.746, SmoothL1=1.220 [Epoch 60][Batch 1699], Speed: 355.671 samples/sec, CrossEntropy=2.745, SmoothL1=1.218 [Epoch 60][Batch 1799], Speed: 358.583 samples/sec, CrossEntropy=2.745, SmoothL1=1.219 [Epoch 60] Training cost: 334.779, CrossEntropy=2.743, SmoothL1=1.217 [Epoch 60] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.207 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.365 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.212 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.033 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.217 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.369 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.202 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.289 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.300 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.054 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.324 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.520 person=30.5 bicycle=15.3 car=17.0 motorcycle=24.2 airplane=37.8 bus=43.4 train=43.9 truck=18.1 boat=9.1 traffic light=6.2 fire hydrant=38.4 stop sign=41.3 parking meter=23.7 bench=11.2 bird=12.3 cat=47.2 dog=41.3 horse=33.8 sheep=26.6 cow=27.3 elephant=38.8 bear=48.9 zebra=43.9 giraffe=45.6 backpack=2.8 umbrella=19.4 handbag=2.1 tie=9.5 suitcase=11.9 frisbee=23.7 skis=7.9 snowboard=9.2 sports ball=14.2 kite=14.2 baseball bat=7.4 baseball glove=8.3 skateboard=19.6 surfboard=13.9 tennis racket=21.3 bottle=10.2 wine glass=10.6 cup=15.8 fork=8.9 knife=3.0 spoon=3.7 bowl=22.3 banana=11.6 apple=8.6 sandwich=26.0 orange=18.5 broccoli=13.2 carrot=6.8 hot dog=15.8 pizza=33.3 donut=22.1 cake=17.1 chair=10.3 couch=28.5 potted plant=10.7 bed=34.1 dining table=20.5 toilet=41.2 tv=37.7 laptop=40.1 mouse=24.8 remote=5.2 keyboard=28.4 cell phone=14.7 microwave=32.3 oven=22.8 toaster=0.0 sink=18.8 refrigerator=32.7 book=3.4 clock=28.5 vase=13.6 scissors=14.1 teddy bear=27.9 hair drier=0.0 toothbrush=3.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.7 [Epoch 61][Batch 99], Speed: 350.376 samples/sec, CrossEntropy=2.704, SmoothL1=1.190 [Epoch 61][Batch 199], Speed: 353.304 samples/sec, CrossEntropy=2.730, SmoothL1=1.206 [Epoch 61][Batch 299], Speed: 358.953 samples/sec, CrossEntropy=2.729, SmoothL1=1.212 [Epoch 61][Batch 399], Speed: 344.356 samples/sec, CrossEntropy=2.738, SmoothL1=1.218 [Epoch 61][Batch 499], Speed: 344.532 samples/sec, CrossEntropy=2.741, SmoothL1=1.218 [Epoch 61][Batch 599], Speed: 352.301 samples/sec, CrossEntropy=2.740, SmoothL1=1.218 [Epoch 61][Batch 699], Speed: 349.565 samples/sec, CrossEntropy=2.740, SmoothL1=1.222 [Epoch 61][Batch 799], Speed: 351.910 samples/sec, CrossEntropy=2.740, SmoothL1=1.224 [Epoch 61][Batch 899], Speed: 360.218 samples/sec, CrossEntropy=2.738, SmoothL1=1.223 [Epoch 61][Batch 999], Speed: 352.409 samples/sec, CrossEntropy=2.741, SmoothL1=1.220 [Epoch 61][Batch 1099], Speed: 353.408 samples/sec, CrossEntropy=2.736, SmoothL1=1.218 [Epoch 61][Batch 1199], Speed: 348.922 samples/sec, CrossEntropy=2.733, SmoothL1=1.219 [Epoch 61][Batch 1299], Speed: 362.858 samples/sec, CrossEntropy=2.733, SmoothL1=1.218 [Epoch 61][Batch 1399], Speed: 349.081 samples/sec, CrossEntropy=2.731, SmoothL1=1.217 [Epoch 61][Batch 1499], Speed: 364.948 samples/sec, CrossEntropy=2.728, SmoothL1=1.216 [Epoch 61][Batch 1599], Speed: 350.757 samples/sec, CrossEntropy=2.729, SmoothL1=1.216 [Epoch 61][Batch 1699], Speed: 347.623 samples/sec, CrossEntropy=2.731, SmoothL1=1.216 [Epoch 61][Batch 1799], Speed: 353.916 samples/sec, CrossEntropy=2.732, SmoothL1=1.218 [Epoch 61] Training cost: 335.745, CrossEntropy=2.729, SmoothL1=1.217 [Epoch 61] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.204 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.364 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.209 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.032 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.214 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.364 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.201 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.288 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.300 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.055 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.325 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.516 person=30.1 bicycle=14.2 car=17.0 motorcycle=23.4 airplane=38.3 bus=43.5 train=45.2 truck=17.9 boat=8.6 traffic light=6.1 fire hydrant=37.4 stop sign=41.4 parking meter=26.2 bench=11.6 bird=12.0 cat=48.3 dog=40.2 horse=32.5 sheep=24.9 cow=25.6 elephant=35.9 bear=45.6 zebra=43.0 giraffe=44.7 backpack=2.4 umbrella=19.4 handbag=1.9 tie=11.2 suitcase=14.6 frisbee=23.8 skis=7.6 snowboard=6.8 sports ball=14.7 kite=14.2 baseball bat=9.6 baseball glove=9.7 skateboard=21.2 surfboard=13.8 tennis racket=20.8 bottle=9.0 wine glass=9.8 cup=16.1 fork=9.0 knife=3.7 spoon=3.8 bowl=21.7 banana=11.7 apple=8.8 sandwich=27.5 orange=17.9 broccoli=14.3 carrot=8.9 hot dog=19.4 pizza=32.5 donut=22.3 cake=17.1 chair=10.3 couch=28.0 potted plant=10.5 bed=33.7 dining table=19.0 toilet=39.5 tv=38.8 laptop=38.5 mouse=23.6 remote=5.9 keyboard=28.4 cell phone=13.2 microwave=30.3 oven=20.8 toaster=0.0 sink=18.5 refrigerator=31.9 book=3.2 clock=26.1 vase=14.0 scissors=10.0 teddy bear=27.2 hair drier=0.0 toothbrush=4.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.4 [Epoch 62][Batch 99], Speed: 358.331 samples/sec, CrossEntropy=2.712, SmoothL1=1.177 [Epoch 62][Batch 199], Speed: 349.755 samples/sec, CrossEntropy=2.742, SmoothL1=1.189 [Epoch 62][Batch 299], Speed: 352.785 samples/sec, CrossEntropy=2.737, SmoothL1=1.190 [Epoch 62][Batch 399], Speed: 363.221 samples/sec, CrossEntropy=2.737, SmoothL1=1.198 [Epoch 62][Batch 499], Speed: 351.861 samples/sec, CrossEntropy=2.734, SmoothL1=1.203 [Epoch 62][Batch 599], Speed: 349.414 samples/sec, CrossEntropy=2.733, SmoothL1=1.203 [Epoch 62][Batch 699], Speed: 347.093 samples/sec, CrossEntropy=2.737, SmoothL1=1.209 [Epoch 62][Batch 799], Speed: 367.543 samples/sec, CrossEntropy=2.733, SmoothL1=1.206 [Epoch 62][Batch 899], Speed: 351.178 samples/sec, CrossEntropy=2.735, SmoothL1=1.210 [Epoch 62][Batch 999], Speed: 348.471 samples/sec, CrossEntropy=2.734, SmoothL1=1.212 [Epoch 62][Batch 1099], Speed: 347.256 samples/sec, CrossEntropy=2.732, SmoothL1=1.214 [Epoch 62][Batch 1199], Speed: 354.593 samples/sec, CrossEntropy=2.730, SmoothL1=1.214 [Epoch 62][Batch 1299], Speed: 357.203 samples/sec, CrossEntropy=2.733, SmoothL1=1.214 [Epoch 62][Batch 1399], Speed: 357.530 samples/sec, CrossEntropy=2.733, SmoothL1=1.212 [Epoch 62][Batch 1499], Speed: 348.870 samples/sec, CrossEntropy=2.730, SmoothL1=1.209 [Epoch 62][Batch 1599], Speed: 356.816 samples/sec, CrossEntropy=2.730, SmoothL1=1.209 [Epoch 62][Batch 1699], Speed: 357.153 samples/sec, CrossEntropy=2.730, SmoothL1=1.210 [Epoch 62][Batch 1799], Speed: 364.371 samples/sec, CrossEntropy=2.727, SmoothL1=1.209 [Epoch 62] Training cost: 334.831, CrossEntropy=2.727, SmoothL1=1.209 [Epoch 62] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.207 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.369 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.210 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.035 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.360 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.203 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.290 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.302 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.059 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.327 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.508 person=30.0 bicycle=14.7 car=17.2 motorcycle=22.6 airplane=40.3 bus=44.7 train=44.4 truck=18.2 boat=8.9 traffic light=5.7 fire hydrant=37.8 stop sign=42.1 parking meter=23.5 bench=10.9 bird=12.3 cat=46.9 dog=42.4 horse=32.7 sheep=27.7 cow=25.2 elephant=37.7 bear=49.6 zebra=41.5 giraffe=47.0 backpack=2.9 umbrella=17.6 handbag=2.3 tie=9.7 suitcase=12.4 frisbee=23.6 skis=7.6 snowboard=7.4 sports ball=15.8 kite=13.8 baseball bat=7.2 baseball glove=8.4 skateboard=20.6 surfboard=14.7 tennis racket=22.1 bottle=10.3 wine glass=10.1 cup=16.4 fork=9.2 knife=4.2 spoon=3.6 bowl=22.6 banana=10.3 apple=7.7 sandwich=24.6 orange=16.6 broccoli=13.3 carrot=7.8 hot dog=20.8 pizza=32.5 donut=23.4 cake=18.7 chair=10.2 couch=30.3 potted plant=10.6 bed=34.5 dining table=18.5 toilet=41.2 tv=37.7 laptop=41.3 mouse=25.7 remote=5.7 keyboard=28.7 cell phone=14.0 microwave=32.4 oven=21.4 toaster=8.3 sink=17.6 refrigerator=31.8 book=3.5 clock=26.2 vase=14.2 scissors=11.6 teddy bear=27.1 hair drier=0.0 toothbrush=2.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.7 [Epoch 63][Batch 99], Speed: 366.006 samples/sec, CrossEntropy=2.747, SmoothL1=1.224 [Epoch 63][Batch 199], Speed: 345.215 samples/sec, CrossEntropy=2.735, SmoothL1=1.205 [Epoch 63][Batch 299], Speed: 364.509 samples/sec, CrossEntropy=2.747, SmoothL1=1.219 [Epoch 63][Batch 399], Speed: 354.289 samples/sec, CrossEntropy=2.742, SmoothL1=1.221 [Epoch 63][Batch 499], Speed: 353.524 samples/sec, CrossEntropy=2.741, SmoothL1=1.210 [Epoch 63][Batch 599], Speed: 361.015 samples/sec, CrossEntropy=2.746, SmoothL1=1.218 [Epoch 63][Batch 699], Speed: 347.275 samples/sec, CrossEntropy=2.746, SmoothL1=1.220 [Epoch 63][Batch 799], Speed: 359.229 samples/sec, CrossEntropy=2.744, SmoothL1=1.223 [Epoch 63][Batch 899], Speed: 356.666 samples/sec, CrossEntropy=2.741, SmoothL1=1.221 [Epoch 63][Batch 999], Speed: 354.634 samples/sec, CrossEntropy=2.739, SmoothL1=1.219 [Epoch 63][Batch 1099], Speed: 359.736 samples/sec, CrossEntropy=2.742, SmoothL1=1.220 [Epoch 63][Batch 1199], Speed: 345.860 samples/sec, CrossEntropy=2.744, SmoothL1=1.220 [Epoch 63][Batch 1299], Speed: 350.032 samples/sec, CrossEntropy=2.742, SmoothL1=1.220 [Epoch 63][Batch 1399], Speed: 347.094 samples/sec, CrossEntropy=2.741, SmoothL1=1.218 [Epoch 63][Batch 1499], Speed: 347.851 samples/sec, CrossEntropy=2.743, SmoothL1=1.218 [Epoch 63][Batch 1599], Speed: 353.717 samples/sec, CrossEntropy=2.743, SmoothL1=1.217 [Epoch 63][Batch 1699], Speed: 358.882 samples/sec, CrossEntropy=2.742, SmoothL1=1.216 [Epoch 63][Batch 1799], Speed: 355.243 samples/sec, CrossEntropy=2.740, SmoothL1=1.216 [Epoch 63] Training cost: 334.573, CrossEntropy=2.739, SmoothL1=1.215 [Epoch 63] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.206 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.367 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.211 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.033 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.216 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.367 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.201 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.288 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.300 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.054 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.326 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.507 person=30.4 bicycle=13.1 car=16.9 motorcycle=23.4 airplane=39.3 bus=42.9 train=45.3 truck=17.8 boat=9.4 traffic light=6.1 fire hydrant=36.5 stop sign=40.8 parking meter=24.8 bench=11.7 bird=12.7 cat=50.9 dog=40.7 horse=33.2 sheep=27.8 cow=25.5 elephant=37.9 bear=51.4 zebra=42.5 giraffe=44.3 backpack=2.8 umbrella=17.6 handbag=1.8 tie=10.6 suitcase=12.7 frisbee=23.5 skis=8.4 snowboard=7.1 sports ball=15.4 kite=13.7 baseball bat=7.8 baseball glove=9.9 skateboard=21.0 surfboard=13.8 tennis racket=22.2 bottle=10.2 wine glass=10.6 cup=16.3 fork=7.6 knife=3.4 spoon=2.7 bowl=21.7 banana=11.3 apple=7.3 sandwich=25.7 orange=18.5 broccoli=13.5 carrot=8.2 hot dog=19.2 pizza=32.9 donut=22.1 cake=18.2 chair=10.2 couch=29.4 potted plant=10.4 bed=32.2 dining table=20.3 toilet=40.4 tv=39.5 laptop=40.1 mouse=25.1 remote=5.1 keyboard=27.6 cell phone=12.8 microwave=31.0 oven=22.6 toaster=0.0 sink=17.7 refrigerator=33.6 book=3.3 clock=25.7 vase=14.1 scissors=13.3 teddy bear=28.1 hair drier=0.0 toothbrush=2.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.6 [Epoch 64][Batch 99], Speed: 353.516 samples/sec, CrossEntropy=2.690, SmoothL1=1.241 [Epoch 64][Batch 199], Speed: 350.070 samples/sec, CrossEntropy=2.709, SmoothL1=1.223 [Epoch 64][Batch 299], Speed: 347.410 samples/sec, CrossEntropy=2.720, SmoothL1=1.224 [Epoch 64][Batch 399], Speed: 358.420 samples/sec, CrossEntropy=2.722, SmoothL1=1.218 [Epoch 64][Batch 499], Speed: 355.117 samples/sec, CrossEntropy=2.727, SmoothL1=1.222 [Epoch 64][Batch 599], Speed: 355.546 samples/sec, CrossEntropy=2.729, SmoothL1=1.217 [Epoch 64][Batch 699], Speed: 358.353 samples/sec, CrossEntropy=2.728, SmoothL1=1.217 [Epoch 64][Batch 799], Speed: 346.897 samples/sec, CrossEntropy=2.734, SmoothL1=1.219 [Epoch 64][Batch 899], Speed: 348.887 samples/sec, CrossEntropy=2.735, SmoothL1=1.220 [Epoch 64][Batch 999], Speed: 352.990 samples/sec, CrossEntropy=2.731, SmoothL1=1.217 [Epoch 64][Batch 1099], Speed: 345.463 samples/sec, CrossEntropy=2.727, SmoothL1=1.217 [Epoch 64][Batch 1199], Speed: 356.580 samples/sec, CrossEntropy=2.726, SmoothL1=1.215 [Epoch 64][Batch 1299], Speed: 348.541 samples/sec, CrossEntropy=2.727, SmoothL1=1.215 [Epoch 64][Batch 1399], Speed: 359.352 samples/sec, CrossEntropy=2.727, SmoothL1=1.216 [Epoch 64][Batch 1499], Speed: 350.269 samples/sec, CrossEntropy=2.730, SmoothL1=1.218 [Epoch 64][Batch 1599], Speed: 349.463 samples/sec, CrossEntropy=2.731, SmoothL1=1.219 [Epoch 64][Batch 1699], Speed: 360.706 samples/sec, CrossEntropy=2.731, SmoothL1=1.218 [Epoch 64][Batch 1799], Speed: 348.860 samples/sec, CrossEntropy=2.731, SmoothL1=1.218 [Epoch 64] Training cost: 335.638, CrossEntropy=2.730, SmoothL1=1.218 [Epoch 64] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.209 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.371 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.212 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.032 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.220 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.362 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.202 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.290 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.302 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.057 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.329 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.511 person=30.7 bicycle=14.0 car=17.2 motorcycle=23.4 airplane=40.1 bus=43.8 train=45.7 truck=19.7 boat=9.0 traffic light=6.3 fire hydrant=37.4 stop sign=41.9 parking meter=25.4 bench=11.1 bird=13.0 cat=49.4 dog=40.5 horse=35.7 sheep=27.3 cow=26.9 elephant=39.1 bear=46.5 zebra=43.8 giraffe=47.0 backpack=3.0 umbrella=18.9 handbag=2.2 tie=10.6 suitcase=12.1 frisbee=24.2 skis=8.8 snowboard=8.5 sports ball=16.5 kite=14.4 baseball bat=8.4 baseball glove=9.1 skateboard=21.4 surfboard=14.2 tennis racket=21.6 bottle=9.4 wine glass=10.5 cup=16.0 fork=10.7 knife=3.2 spoon=3.2 bowl=21.7 banana=11.1 apple=8.8 sandwich=26.5 orange=19.4 broccoli=13.2 carrot=8.6 hot dog=20.6 pizza=32.1 donut=21.4 cake=17.0 chair=10.5 couch=29.2 potted plant=11.2 bed=31.9 dining table=18.2 toilet=38.2 tv=38.6 laptop=40.7 mouse=24.9 remote=4.4 keyboard=28.7 cell phone=14.8 microwave=29.3 oven=20.9 toaster=7.1 sink=18.1 refrigerator=33.0 book=3.3 clock=26.9 vase=12.9 scissors=13.5 teddy bear=28.8 hair drier=0.0 toothbrush=3.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.9 [Epoch 65][Batch 99], Speed: 356.588 samples/sec, CrossEntropy=2.731, SmoothL1=1.226 [Epoch 65][Batch 199], Speed: 366.066 samples/sec, CrossEntropy=2.736, SmoothL1=1.217 [Epoch 65][Batch 299], Speed: 344.834 samples/sec, CrossEntropy=2.719, SmoothL1=1.207 [Epoch 65][Batch 399], Speed: 344.773 samples/sec, CrossEntropy=2.712, SmoothL1=1.202 [Epoch 65][Batch 499], Speed: 348.081 samples/sec, CrossEntropy=2.708, SmoothL1=1.202 [Epoch 65][Batch 599], Speed: 360.818 samples/sec, CrossEntropy=2.709, SmoothL1=1.204 [Epoch 65][Batch 699], Speed: 356.626 samples/sec, CrossEntropy=2.715, SmoothL1=1.207 [Epoch 65][Batch 799], Speed: 353.031 samples/sec, CrossEntropy=2.721, SmoothL1=1.212 [Epoch 65][Batch 899], Speed: 360.437 samples/sec, CrossEntropy=2.719, SmoothL1=1.212 [Epoch 65][Batch 999], Speed: 350.820 samples/sec, CrossEntropy=2.720, SmoothL1=1.211 [Epoch 65][Batch 1099], Speed: 344.794 samples/sec, CrossEntropy=2.715, SmoothL1=1.211 [Epoch 65][Batch 1199], Speed: 349.040 samples/sec, CrossEntropy=2.716, SmoothL1=1.213 [Epoch 65][Batch 1299], Speed: 358.332 samples/sec, CrossEntropy=2.716, SmoothL1=1.214 [Epoch 65][Batch 1399], Speed: 355.225 samples/sec, CrossEntropy=2.715, SmoothL1=1.214 [Epoch 65][Batch 1499], Speed: 350.027 samples/sec, CrossEntropy=2.714, SmoothL1=1.213 [Epoch 65][Batch 1599], Speed: 359.587 samples/sec, CrossEntropy=2.713, SmoothL1=1.213 [Epoch 65][Batch 1699], Speed: 357.466 samples/sec, CrossEntropy=2.711, SmoothL1=1.211 [Epoch 65][Batch 1799], Speed: 348.030 samples/sec, CrossEntropy=2.713, SmoothL1=1.210 [Epoch 65] Training cost: 335.134, CrossEntropy=2.713, SmoothL1=1.210 [Epoch 65] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.205 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.365 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.208 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.032 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.357 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.203 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.290 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.302 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.056 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.326 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.509 person=30.4 bicycle=13.8 car=16.8 motorcycle=23.4 airplane=42.5 bus=43.0 train=47.8 truck=18.2 boat=9.1 traffic light=5.8 fire hydrant=38.7 stop sign=40.1 parking meter=22.1 bench=11.2 bird=13.2 cat=45.6 dog=39.4 horse=34.6 sheep=24.9 cow=26.4 elephant=39.0 bear=48.1 zebra=42.4 giraffe=45.9 backpack=2.5 umbrella=18.4 handbag=1.5 tie=11.1 suitcase=14.0 frisbee=21.8 skis=8.6 snowboard=11.1 sports ball=15.2 kite=13.7 baseball bat=7.9 baseball glove=9.0 skateboard=21.1 surfboard=14.5 tennis racket=20.5 bottle=9.1 wine glass=10.0 cup=15.6 fork=8.5 knife=3.4 spoon=3.4 bowl=22.0 banana=10.7 apple=8.3 sandwich=24.8 orange=18.1 broccoli=11.1 carrot=7.3 hot dog=17.3 pizza=31.5 donut=21.0 cake=17.7 chair=9.8 couch=28.8 potted plant=9.9 bed=30.6 dining table=20.3 toilet=39.0 tv=37.7 laptop=36.5 mouse=24.7 remote=5.2 keyboard=30.6 cell phone=13.8 microwave=29.2 oven=22.2 toaster=8.3 sink=18.3 refrigerator=31.7 book=3.4 clock=26.1 vase=11.9 scissors=15.7 teddy bear=26.5 hair drier=0.0 toothbrush=3.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.5 [Epoch 66][Batch 99], Speed: 361.534 samples/sec, CrossEntropy=2.694, SmoothL1=1.187 [Epoch 66][Batch 199], Speed: 351.602 samples/sec, CrossEntropy=2.732, SmoothL1=1.200 [Epoch 66][Batch 299], Speed: 353.900 samples/sec, CrossEntropy=2.740, SmoothL1=1.208 [Epoch 66][Batch 399], Speed: 348.460 samples/sec, CrossEntropy=2.729, SmoothL1=1.199 [Epoch 66][Batch 499], Speed: 362.511 samples/sec, CrossEntropy=2.727, SmoothL1=1.204 [Epoch 66][Batch 599], Speed: 345.572 samples/sec, CrossEntropy=2.724, SmoothL1=1.206 [Epoch 66][Batch 699], Speed: 358.275 samples/sec, CrossEntropy=2.727, SmoothL1=1.207 [Epoch 66][Batch 799], Speed: 352.219 samples/sec, CrossEntropy=2.725, SmoothL1=1.206 [Epoch 66][Batch 899], Speed: 344.420 samples/sec, CrossEntropy=2.722, SmoothL1=1.206 [Epoch 66][Batch 999], Speed: 362.666 samples/sec, CrossEntropy=2.720, SmoothL1=1.208 [Epoch 66][Batch 1099], Speed: 353.119 samples/sec, CrossEntropy=2.717, SmoothL1=1.208 [Epoch 66][Batch 1199], Speed: 349.656 samples/sec, CrossEntropy=2.716, SmoothL1=1.207 [Epoch 66][Batch 1299], Speed: 360.625 samples/sec, CrossEntropy=2.718, SmoothL1=1.210 [Epoch 66][Batch 1399], Speed: 360.621 samples/sec, CrossEntropy=2.720, SmoothL1=1.211 [Epoch 66][Batch 1499], Speed: 350.754 samples/sec, CrossEntropy=2.717, SmoothL1=1.209 [Epoch 66][Batch 1599], Speed: 353.904 samples/sec, CrossEntropy=2.714, SmoothL1=1.207 [Epoch 66][Batch 1699], Speed: 344.299 samples/sec, CrossEntropy=2.714, SmoothL1=1.208 [Epoch 66][Batch 1799], Speed: 354.685 samples/sec, CrossEntropy=2.712, SmoothL1=1.206 [Epoch 66] Training cost: 335.696, CrossEntropy=2.712, SmoothL1=1.206 [Epoch 66] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.207 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.369 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.210 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.034 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.220 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.367 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.205 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.292 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.059 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.329 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.514 person=30.1 bicycle=14.0 car=16.6 motorcycle=24.1 airplane=39.0 bus=39.2 train=44.5 truck=17.0 boat=8.9 traffic light=6.6 fire hydrant=38.5 stop sign=42.0 parking meter=27.4 bench=10.8 bird=13.1 cat=49.7 dog=41.6 horse=34.8 sheep=28.3 cow=25.7 elephant=39.1 bear=49.6 zebra=43.2 giraffe=44.9 backpack=2.5 umbrella=19.7 handbag=1.6 tie=10.5 suitcase=13.6 frisbee=24.4 skis=8.7 snowboard=9.4 sports ball=15.6 kite=13.5 baseball bat=7.6 baseball glove=10.0 skateboard=22.4 surfboard=14.7 tennis racket=20.9 bottle=10.2 wine glass=10.2 cup=15.8 fork=7.7 knife=3.5 spoon=2.8 bowl=21.3 banana=11.0 apple=7.7 sandwich=25.8 orange=18.0 broccoli=14.3 carrot=7.9 hot dog=19.0 pizza=30.9 donut=22.6 cake=16.6 chair=10.1 couch=30.6 potted plant=12.0 bed=32.0 dining table=20.1 toilet=39.5 tv=37.3 laptop=39.3 mouse=24.8 remote=5.0 keyboard=29.8 cell phone=14.5 microwave=29.2 oven=20.4 toaster=3.6 sink=17.9 refrigerator=30.5 book=3.2 clock=26.5 vase=13.9 scissors=14.7 teddy bear=29.4 hair drier=0.0 toothbrush=3.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.7 [Epoch 67][Batch 99], Speed: 354.349 samples/sec, CrossEntropy=2.721, SmoothL1=1.223 [Epoch 67][Batch 199], Speed: 353.290 samples/sec, CrossEntropy=2.701, SmoothL1=1.202 [Epoch 67][Batch 299], Speed: 351.089 samples/sec, CrossEntropy=2.691, SmoothL1=1.197 [Epoch 67][Batch 399], Speed: 345.289 samples/sec, CrossEntropy=2.710, SmoothL1=1.205 [Epoch 67][Batch 499], Speed: 352.145 samples/sec, CrossEntropy=2.718, SmoothL1=1.206 [Epoch 67][Batch 599], Speed: 345.407 samples/sec, CrossEntropy=2.723, SmoothL1=1.206 [Epoch 67][Batch 699], Speed: 345.988 samples/sec, CrossEntropy=2.715, SmoothL1=1.200 [Epoch 67][Batch 799], Speed: 357.124 samples/sec, CrossEntropy=2.710, SmoothL1=1.197 [Epoch 67][Batch 899], Speed: 353.192 samples/sec, CrossEntropy=2.713, SmoothL1=1.198 [Epoch 67][Batch 999], Speed: 352.411 samples/sec, CrossEntropy=2.711, SmoothL1=1.200 [Epoch 67][Batch 1099], Speed: 348.816 samples/sec, CrossEntropy=2.707, SmoothL1=1.200 [Epoch 67][Batch 1199], Speed: 360.504 samples/sec, CrossEntropy=2.706, SmoothL1=1.199 [Epoch 67][Batch 1299], Speed: 342.706 samples/sec, CrossEntropy=2.708, SmoothL1=1.201 [Epoch 67][Batch 1399], Speed: 363.206 samples/sec, CrossEntropy=2.708, SmoothL1=1.200 [Epoch 67][Batch 1499], Speed: 362.246 samples/sec, CrossEntropy=2.704, SmoothL1=1.198 [Epoch 67][Batch 1599], Speed: 355.030 samples/sec, CrossEntropy=2.704, SmoothL1=1.199 [Epoch 67][Batch 1699], Speed: 365.098 samples/sec, CrossEntropy=2.704, SmoothL1=1.198 [Epoch 67][Batch 1799], Speed: 357.350 samples/sec, CrossEntropy=2.704, SmoothL1=1.198 [Epoch 67] Training cost: 334.893, CrossEntropy=2.705, SmoothL1=1.198 [Epoch 67] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.206 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.364 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.213 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.033 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.368 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.203 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.291 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.303 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.057 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.330 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.514 person=30.4 bicycle=13.2 car=16.7 motorcycle=22.5 airplane=38.6 bus=44.0 train=46.9 truck=17.9 boat=9.5 traffic light=6.4 fire hydrant=39.0 stop sign=43.4 parking meter=27.2 bench=11.7 bird=12.4 cat=46.7 dog=39.3 horse=32.5 sheep=27.0 cow=24.7 elephant=36.7 bear=45.2 zebra=44.9 giraffe=46.2 backpack=2.5 umbrella=18.2 handbag=2.3 tie=11.2 suitcase=13.2 frisbee=21.1 skis=8.0 snowboard=10.0 sports ball=15.6 kite=13.8 baseball bat=8.1 baseball glove=10.7 skateboard=21.5 surfboard=14.6 tennis racket=22.8 bottle=10.5 wine glass=10.3 cup=16.6 fork=9.5 knife=2.8 spoon=4.0 bowl=21.8 banana=11.6 apple=6.1 sandwich=26.4 orange=17.8 broccoli=11.3 carrot=7.3 hot dog=19.1 pizza=29.9 donut=21.6 cake=17.7 chair=9.6 couch=28.3 potted plant=11.0 bed=33.5 dining table=20.1 toilet=42.0 tv=38.4 laptop=38.5 mouse=25.2 remote=4.9 keyboard=28.3 cell phone=13.9 microwave=32.0 oven=20.3 toaster=5.9 sink=16.8 refrigerator=30.6 book=3.1 clock=26.2 vase=13.2 scissors=13.1 teddy bear=26.9 hair drier=0.0 toothbrush=4.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.6 [Epoch 68][Batch 99], Speed: 357.242 samples/sec, CrossEntropy=2.681, SmoothL1=1.217 [Epoch 68][Batch 199], Speed: 357.919 samples/sec, CrossEntropy=2.686, SmoothL1=1.199 [Epoch 68][Batch 299], Speed: 358.600 samples/sec, CrossEntropy=2.699, SmoothL1=1.207 [Epoch 68][Batch 399], Speed: 353.714 samples/sec, CrossEntropy=2.700, SmoothL1=1.198 [Epoch 68][Batch 499], Speed: 340.631 samples/sec, CrossEntropy=2.705, SmoothL1=1.206 [Epoch 68][Batch 599], Speed: 347.342 samples/sec, CrossEntropy=2.711, SmoothL1=1.203 [Epoch 68][Batch 699], Speed: 350.706 samples/sec, CrossEntropy=2.709, SmoothL1=1.201 [Epoch 68][Batch 799], Speed: 354.176 samples/sec, CrossEntropy=2.706, SmoothL1=1.200 [Epoch 68][Batch 899], Speed: 348.161 samples/sec, CrossEntropy=2.706, SmoothL1=1.198 [Epoch 68][Batch 999], Speed: 351.889 samples/sec, CrossEntropy=2.703, SmoothL1=1.196 [Epoch 68][Batch 1099], Speed: 345.299 samples/sec, CrossEntropy=2.703, SmoothL1=1.198 [Epoch 68][Batch 1199], Speed: 349.890 samples/sec, CrossEntropy=2.701, SmoothL1=1.198 [Epoch 68][Batch 1299], Speed: 346.613 samples/sec, CrossEntropy=2.702, SmoothL1=1.200 [Epoch 68][Batch 1399], Speed: 353.700 samples/sec, CrossEntropy=2.703, SmoothL1=1.199 [Epoch 68][Batch 1499], Speed: 357.640 samples/sec, CrossEntropy=2.699, SmoothL1=1.199 [Epoch 68][Batch 1599], Speed: 350.156 samples/sec, CrossEntropy=2.697, SmoothL1=1.198 [Epoch 68][Batch 1699], Speed: 358.598 samples/sec, CrossEntropy=2.699, SmoothL1=1.199 [Epoch 68][Batch 1799], Speed: 345.457 samples/sec, CrossEntropy=2.699, SmoothL1=1.199 [Epoch 68] Training cost: 335.931, CrossEntropy=2.699, SmoothL1=1.199 [Epoch 68] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.206 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.366 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.211 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.033 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.361 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.204 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.289 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.301 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.058 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.326 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.511 person=30.2 bicycle=13.9 car=17.1 motorcycle=23.5 airplane=39.4 bus=42.2 train=44.9 truck=18.6 boat=8.9 traffic light=6.0 fire hydrant=39.3 stop sign=43.1 parking meter=24.9 bench=10.6 bird=12.6 cat=48.9 dog=37.3 horse=31.6 sheep=26.4 cow=25.3 elephant=39.2 bear=47.6 zebra=44.6 giraffe=43.2 backpack=2.6 umbrella=21.1 handbag=1.9 tie=10.7 suitcase=13.6 frisbee=24.4 skis=8.4 snowboard=9.7 sports ball=15.1 kite=13.5 baseball bat=7.3 baseball glove=8.9 skateboard=19.8 surfboard=13.5 tennis racket=22.3 bottle=8.8 wine glass=10.1 cup=15.4 fork=9.4 knife=3.6 spoon=3.4 bowl=20.4 banana=11.4 apple=8.1 sandwich=25.1 orange=18.8 broccoli=13.2 carrot=7.4 hot dog=18.4 pizza=30.6 donut=21.9 cake=18.3 chair=10.4 couch=30.2 potted plant=10.9 bed=32.6 dining table=19.8 toilet=40.8 tv=37.9 laptop=37.8 mouse=25.9 remote=4.5 keyboard=26.8 cell phone=13.4 microwave=34.3 oven=20.9 toaster=5.9 sink=18.9 refrigerator=32.6 book=2.9 clock=26.6 vase=13.8 scissors=12.8 teddy bear=28.0 hair drier=0.0 toothbrush=2.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.6 [Epoch 69][Batch 99], Speed: 358.091 samples/sec, CrossEntropy=2.727, SmoothL1=1.218 [Epoch 69][Batch 199], Speed: 346.388 samples/sec, CrossEntropy=2.714, SmoothL1=1.215 [Epoch 69][Batch 299], Speed: 356.112 samples/sec, CrossEntropy=2.716, SmoothL1=1.206 [Epoch 69][Batch 399], Speed: 350.091 samples/sec, CrossEntropy=2.714, SmoothL1=1.208 [Epoch 69][Batch 499], Speed: 351.938 samples/sec, CrossEntropy=2.721, SmoothL1=1.212 [Epoch 69][Batch 599], Speed: 351.806 samples/sec, CrossEntropy=2.721, SmoothL1=1.214 [Epoch 69][Batch 699], Speed: 350.654 samples/sec, CrossEntropy=2.717, SmoothL1=1.208 [Epoch 69][Batch 799], Speed: 349.251 samples/sec, CrossEntropy=2.711, SmoothL1=1.207 [Epoch 69][Batch 899], Speed: 341.018 samples/sec, CrossEntropy=2.705, SmoothL1=1.202 [Epoch 69][Batch 999], Speed: 344.220 samples/sec, CrossEntropy=2.702, SmoothL1=1.201 [Epoch 69][Batch 1099], Speed: 350.401 samples/sec, CrossEntropy=2.703, SmoothL1=1.201 [Epoch 69][Batch 1199], Speed: 360.720 samples/sec, CrossEntropy=2.700, SmoothL1=1.200 [Epoch 69][Batch 1299], Speed: 357.486 samples/sec, CrossEntropy=2.700, SmoothL1=1.200 [Epoch 69][Batch 1399], Speed: 353.324 samples/sec, CrossEntropy=2.699, SmoothL1=1.199 [Epoch 69][Batch 1499], Speed: 364.514 samples/sec, CrossEntropy=2.699, SmoothL1=1.200 [Epoch 69][Batch 1599], Speed: 350.550 samples/sec, CrossEntropy=2.701, SmoothL1=1.200 [Epoch 69][Batch 1699], Speed: 349.533 samples/sec, CrossEntropy=2.704, SmoothL1=1.200 [Epoch 69][Batch 1799], Speed: 354.259 samples/sec, CrossEntropy=2.705, SmoothL1=1.200 [Epoch 69] Training cost: 335.319, CrossEntropy=2.705, SmoothL1=1.199 [Epoch 69] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.207 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.367 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.213 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.033 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.220 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.364 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.202 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.289 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.300 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.055 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.321 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.511 person=30.6 bicycle=13.2 car=17.0 motorcycle=21.9 airplane=40.9 bus=43.9 train=48.8 truck=17.2 boat=9.1 traffic light=6.0 fire hydrant=38.6 stop sign=42.3 parking meter=25.9 bench=11.4 bird=12.7 cat=47.1 dog=39.0 horse=34.4 sheep=26.3 cow=24.6 elephant=39.3 bear=51.2 zebra=42.9 giraffe=43.9 backpack=2.6 umbrella=19.8 handbag=1.8 tie=10.9 suitcase=13.1 frisbee=23.7 skis=8.8 snowboard=9.6 sports ball=15.8 kite=13.8 baseball bat=7.1 baseball glove=9.6 skateboard=22.0 surfboard=14.5 tennis racket=20.6 bottle=9.7 wine glass=10.5 cup=16.1 fork=9.0 knife=3.2 spoon=3.2 bowl=22.0 banana=12.5 apple=5.7 sandwich=25.3 orange=17.8 broccoli=13.0 carrot=8.3 hot dog=18.3 pizza=28.7 donut=23.2 cake=17.6 chair=10.4 couch=30.3 potted plant=10.8 bed=31.4 dining table=20.0 toilet=39.4 tv=39.1 laptop=40.1 mouse=25.8 remote=5.3 keyboard=27.5 cell phone=12.3 microwave=31.6 oven=22.1 toaster=5.9 sink=18.0 refrigerator=31.0 book=3.1 clock=26.5 vase=14.4 scissors=14.8 teddy bear=26.9 hair drier=0.0 toothbrush=3.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.7 [Epoch 70][Batch 99], Speed: 361.338 samples/sec, CrossEntropy=2.743, SmoothL1=1.245 [Epoch 70][Batch 199], Speed: 354.323 samples/sec, CrossEntropy=2.730, SmoothL1=1.224 [Epoch 70][Batch 299], Speed: 346.353 samples/sec, CrossEntropy=2.718, SmoothL1=1.219 [Epoch 70][Batch 399], Speed: 350.586 samples/sec, CrossEntropy=2.717, SmoothL1=1.213 [Epoch 70][Batch 499], Speed: 356.366 samples/sec, CrossEntropy=2.717, SmoothL1=1.209 [Epoch 70][Batch 599], Speed: 349.613 samples/sec, CrossEntropy=2.716, SmoothL1=1.211 [Epoch 70][Batch 699], Speed: 354.883 samples/sec, CrossEntropy=2.715, SmoothL1=1.208 [Epoch 70][Batch 799], Speed: 354.611 samples/sec, CrossEntropy=2.712, SmoothL1=1.204 [Epoch 70][Batch 899], Speed: 345.339 samples/sec, CrossEntropy=2.707, SmoothL1=1.200 [Epoch 70][Batch 999], Speed: 353.051 samples/sec, CrossEntropy=2.705, SmoothL1=1.200 [Epoch 70][Batch 1099], Speed: 360.281 samples/sec, CrossEntropy=2.704, SmoothL1=1.200 [Epoch 70][Batch 1199], Speed: 359.203 samples/sec, CrossEntropy=2.708, SmoothL1=1.203 [Epoch 70][Batch 1299], Speed: 354.660 samples/sec, CrossEntropy=2.705, SmoothL1=1.202 [Epoch 70][Batch 1399], Speed: 352.677 samples/sec, CrossEntropy=2.703, SmoothL1=1.201 [Epoch 70][Batch 1499], Speed: 360.856 samples/sec, CrossEntropy=2.703, SmoothL1=1.201 [Epoch 70][Batch 1599], Speed: 355.815 samples/sec, CrossEntropy=2.703, SmoothL1=1.201 [Epoch 70][Batch 1699], Speed: 349.898 samples/sec, CrossEntropy=2.703, SmoothL1=1.200 [Epoch 70][Batch 1799], Speed: 358.743 samples/sec, CrossEntropy=2.705, SmoothL1=1.200 [Epoch 70] Training cost: 334.787, CrossEntropy=2.705, SmoothL1=1.200 [Epoch 70] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.208 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.368 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.210 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.034 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.217 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.367 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.204 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.291 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.059 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.327 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.509 person=30.7 bicycle=13.5 car=17.0 motorcycle=22.6 airplane=38.6 bus=43.2 train=47.4 truck=18.1 boat=9.7 traffic light=5.9 fire hydrant=40.1 stop sign=42.1 parking meter=25.4 bench=11.9 bird=13.5 cat=48.8 dog=40.1 horse=34.0 sheep=25.4 cow=26.5 elephant=37.8 bear=48.6 zebra=43.4 giraffe=46.5 backpack=2.6 umbrella=20.4 handbag=2.1 tie=11.5 suitcase=14.0 frisbee=24.2 skis=7.6 snowboard=8.1 sports ball=15.9 kite=13.2 baseball bat=8.8 baseball glove=9.9 skateboard=22.1 surfboard=13.5 tennis racket=21.5 bottle=10.7 wine glass=10.3 cup=16.2 fork=9.5 knife=3.9 spoon=3.8 bowl=21.3 banana=10.9 apple=8.1 sandwich=21.7 orange=16.2 broccoli=11.8 carrot=8.0 hot dog=20.4 pizza=32.9 donut=22.6 cake=16.7 chair=10.6 couch=28.6 potted plant=9.8 bed=32.7 dining table=19.0 toilet=40.4 tv=38.0 laptop=39.6 mouse=25.1 remote=4.7 keyboard=28.8 cell phone=14.0 microwave=29.2 oven=22.8 toaster=5.9 sink=19.0 refrigerator=32.9 book=2.9 clock=26.2 vase=14.4 scissors=12.2 teddy bear=29.6 hair drier=0.0 toothbrush=4.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.8 [Epoch 71][Batch 99], Speed: 342.027 samples/sec, CrossEntropy=2.732, SmoothL1=1.220 [Epoch 71][Batch 199], Speed: 353.754 samples/sec, CrossEntropy=2.712, SmoothL1=1.219 [Epoch 71][Batch 299], Speed: 352.986 samples/sec, CrossEntropy=2.715, SmoothL1=1.214 [Epoch 71][Batch 399], Speed: 341.943 samples/sec, CrossEntropy=2.714, SmoothL1=1.206 [Epoch 71][Batch 499], Speed: 362.131 samples/sec, CrossEntropy=2.714, SmoothL1=1.206 [Epoch 71][Batch 599], Speed: 351.620 samples/sec, CrossEntropy=2.710, SmoothL1=1.200 [Epoch 71][Batch 699], Speed: 354.058 samples/sec, CrossEntropy=2.714, SmoothL1=1.200 [Epoch 71][Batch 799], Speed: 357.603 samples/sec, CrossEntropy=2.708, SmoothL1=1.198 [Epoch 71][Batch 899], Speed: 359.430 samples/sec, CrossEntropy=2.707, SmoothL1=1.199 [Epoch 71][Batch 999], Speed: 349.032 samples/sec, CrossEntropy=2.706, SmoothL1=1.199 [Epoch 71][Batch 1099], Speed: 345.129 samples/sec, CrossEntropy=2.704, SmoothL1=1.199 [Epoch 71][Batch 1199], Speed: 353.336 samples/sec, CrossEntropy=2.706, SmoothL1=1.198 [Epoch 71][Batch 1299], Speed: 350.399 samples/sec, CrossEntropy=2.704, SmoothL1=1.196 [Epoch 71][Batch 1399], Speed: 355.946 samples/sec, CrossEntropy=2.704, SmoothL1=1.196 [Epoch 71][Batch 1499], Speed: 354.871 samples/sec, CrossEntropy=2.702, SmoothL1=1.193 [Epoch 71][Batch 1599], Speed: 349.947 samples/sec, CrossEntropy=2.704, SmoothL1=1.195 [Epoch 71][Batch 1699], Speed: 344.534 samples/sec, CrossEntropy=2.701, SmoothL1=1.194 [Epoch 71][Batch 1799], Speed: 356.946 samples/sec, CrossEntropy=2.701, SmoothL1=1.195 [Epoch 71] Training cost: 335.919, CrossEntropy=2.701, SmoothL1=1.195 [Epoch 71] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.208 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.372 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.210 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.034 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.223 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.364 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.203 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.291 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.303 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.057 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.334 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.507 person=30.5 bicycle=13.7 car=16.3 motorcycle=22.8 airplane=37.4 bus=44.3 train=45.6 truck=17.4 boat=9.5 traffic light=6.6 fire hydrant=37.7 stop sign=41.4 parking meter=27.3 bench=12.0 bird=12.9 cat=46.6 dog=41.0 horse=33.4 sheep=26.6 cow=26.7 elephant=39.7 bear=49.7 zebra=42.2 giraffe=43.7 backpack=2.1 umbrella=20.4 handbag=2.1 tie=10.8 suitcase=13.4 frisbee=23.8 skis=8.9 snowboard=8.5 sports ball=15.3 kite=13.9 baseball bat=7.8 baseball glove=11.0 skateboard=21.9 surfboard=14.9 tennis racket=22.1 bottle=10.4 wine glass=10.8 cup=15.6 fork=9.2 knife=3.5 spoon=4.3 bowl=22.0 banana=11.0 apple=9.0 sandwich=26.0 orange=18.1 broccoli=12.5 carrot=7.5 hot dog=18.1 pizza=33.7 donut=23.2 cake=18.6 chair=10.5 couch=30.1 potted plant=10.4 bed=31.9 dining table=18.7 toilet=41.5 tv=38.4 laptop=39.8 mouse=25.7 remote=4.5 keyboard=28.0 cell phone=11.8 microwave=28.9 oven=21.5 toaster=5.9 sink=17.2 refrigerator=31.0 book=3.4 clock=25.9 vase=14.1 scissors=15.5 teddy bear=28.1 hair drier=0.0 toothbrush=2.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.8 [Epoch 72][Batch 99], Speed: 348.013 samples/sec, CrossEntropy=2.726, SmoothL1=1.184 [Epoch 72][Batch 199], Speed: 350.833 samples/sec, CrossEntropy=2.714, SmoothL1=1.192 [Epoch 72][Batch 299], Speed: 349.528 samples/sec, CrossEntropy=2.708, SmoothL1=1.193 [Epoch 72][Batch 399], Speed: 360.684 samples/sec, CrossEntropy=2.709, SmoothL1=1.194 [Epoch 72][Batch 499], Speed: 362.457 samples/sec, CrossEntropy=2.703, SmoothL1=1.184 [Epoch 72][Batch 599], Speed: 354.985 samples/sec, CrossEntropy=2.704, SmoothL1=1.186 [Epoch 72][Batch 699], Speed: 358.532 samples/sec, CrossEntropy=2.697, SmoothL1=1.180 [Epoch 72][Batch 799], Speed: 351.873 samples/sec, CrossEntropy=2.695, SmoothL1=1.182 [Epoch 72][Batch 899], Speed: 353.310 samples/sec, CrossEntropy=2.695, SmoothL1=1.186 [Epoch 72][Batch 999], Speed: 352.400 samples/sec, CrossEntropy=2.694, SmoothL1=1.187 [Epoch 72][Batch 1099], Speed: 355.677 samples/sec, CrossEntropy=2.691, SmoothL1=1.187 [Epoch 72][Batch 1199], Speed: 343.148 samples/sec, CrossEntropy=2.694, SmoothL1=1.188 [Epoch 72][Batch 1299], Speed: 343.986 samples/sec, CrossEntropy=2.697, SmoothL1=1.188 [Epoch 72][Batch 1399], Speed: 350.310 samples/sec, CrossEntropy=2.697, SmoothL1=1.189 [Epoch 72][Batch 1499], Speed: 349.128 samples/sec, CrossEntropy=2.696, SmoothL1=1.188 [Epoch 72][Batch 1599], Speed: 353.297 samples/sec, CrossEntropy=2.696, SmoothL1=1.188 [Epoch 72][Batch 1699], Speed: 352.887 samples/sec, CrossEntropy=2.695, SmoothL1=1.188 [Epoch 72][Batch 1799], Speed: 353.676 samples/sec, CrossEntropy=2.695, SmoothL1=1.188 [Epoch 72] Training cost: 334.815, CrossEntropy=2.695, SmoothL1=1.189 [Epoch 72] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.213 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.372 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.033 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.228 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.373 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.207 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.295 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.307 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.058 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.518 person=31.1 bicycle=14.0 car=16.9 motorcycle=23.9 airplane=39.3 bus=45.4 train=46.0 truck=18.2 boat=9.6 traffic light=6.4 fire hydrant=39.4 stop sign=44.5 parking meter=25.9 bench=12.0 bird=12.5 cat=48.5 dog=42.6 horse=34.0 sheep=27.6 cow=27.8 elephant=40.5 bear=50.9 zebra=43.0 giraffe=45.4 backpack=2.8 umbrella=21.2 handbag=2.2 tie=10.5 suitcase=14.6 frisbee=24.6 skis=8.0 snowboard=10.6 sports ball=15.6 kite=13.9 baseball bat=8.6 baseball glove=10.6 skateboard=22.1 surfboard=14.6 tennis racket=22.2 bottle=9.8 wine glass=10.1 cup=16.3 fork=8.9 knife=3.3 spoon=3.1 bowl=22.2 banana=11.9 apple=7.9 sandwich=22.4 orange=19.2 broccoli=12.4 carrot=8.7 hot dog=20.5 pizza=31.9 donut=23.2 cake=17.9 chair=10.4 couch=32.1 potted plant=12.0 bed=34.3 dining table=19.3 toilet=42.2 tv=38.5 laptop=39.9 mouse=26.8 remote=5.7 keyboard=29.5 cell phone=12.9 microwave=32.6 oven=22.0 toaster=5.9 sink=17.3 refrigerator=35.0 book=3.5 clock=26.3 vase=14.0 scissors=12.1 teddy bear=30.7 hair drier=0.0 toothbrush=3.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.3 [Epoch 73][Batch 99], Speed: 361.594 samples/sec, CrossEntropy=2.683, SmoothL1=1.189 [Epoch 73][Batch 199], Speed: 355.883 samples/sec, CrossEntropy=2.679, SmoothL1=1.197 [Epoch 73][Batch 299], Speed: 352.108 samples/sec, CrossEntropy=2.685, SmoothL1=1.191 [Epoch 73][Batch 399], Speed: 346.808 samples/sec, CrossEntropy=2.685, SmoothL1=1.203 [Epoch 73][Batch 499], Speed: 363.040 samples/sec, CrossEntropy=2.678, SmoothL1=1.199 [Epoch 73][Batch 599], Speed: 363.167 samples/sec, CrossEntropy=2.678, SmoothL1=1.195 [Epoch 73][Batch 699], Speed: 356.248 samples/sec, CrossEntropy=2.679, SmoothL1=1.193 [Epoch 73][Batch 799], Speed: 347.550 samples/sec, CrossEntropy=2.682, SmoothL1=1.193 [Epoch 73][Batch 899], Speed: 365.768 samples/sec, CrossEntropy=2.679, SmoothL1=1.188 [Epoch 73][Batch 999], Speed: 357.307 samples/sec, CrossEntropy=2.680, SmoothL1=1.188 [Epoch 73][Batch 1099], Speed: 352.283 samples/sec, CrossEntropy=2.678, SmoothL1=1.188 [Epoch 73][Batch 1199], Speed: 346.658 samples/sec, CrossEntropy=2.678, SmoothL1=1.188 [Epoch 73][Batch 1299], Speed: 353.660 samples/sec, CrossEntropy=2.678, SmoothL1=1.188 [Epoch 73][Batch 1399], Speed: 350.311 samples/sec, CrossEntropy=2.677, SmoothL1=1.188 [Epoch 73][Batch 1499], Speed: 356.631 samples/sec, CrossEntropy=2.676, SmoothL1=1.187 [Epoch 73][Batch 1599], Speed: 350.885 samples/sec, CrossEntropy=2.675, SmoothL1=1.185 [Epoch 73][Batch 1699], Speed: 363.718 samples/sec, CrossEntropy=2.677, SmoothL1=1.186 [Epoch 73][Batch 1799], Speed: 348.880 samples/sec, CrossEntropy=2.675, SmoothL1=1.185 [Epoch 73] Training cost: 335.124, CrossEntropy=2.675, SmoothL1=1.186 [Epoch 73] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.211 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.370 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.217 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.035 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.222 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.375 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.207 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.295 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.307 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.057 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.521 person=30.8 bicycle=13.1 car=17.2 motorcycle=24.6 airplane=41.5 bus=45.1 train=45.6 truck=17.8 boat=9.0 traffic light=6.1 fire hydrant=40.7 stop sign=42.6 parking meter=26.6 bench=11.4 bird=13.3 cat=47.3 dog=39.7 horse=32.7 sheep=27.4 cow=26.7 elephant=40.4 bear=53.0 zebra=44.1 giraffe=45.5 backpack=2.2 umbrella=19.3 handbag=2.2 tie=12.1 suitcase=13.5 frisbee=24.6 skis=7.9 snowboard=9.5 sports ball=16.6 kite=13.7 baseball bat=7.6 baseball glove=10.0 skateboard=23.5 surfboard=14.8 tennis racket=22.8 bottle=10.3 wine glass=11.3 cup=16.2 fork=9.9 knife=3.6 spoon=3.8 bowl=22.3 banana=11.3 apple=7.4 sandwich=23.4 orange=17.8 broccoli=13.3 carrot=8.4 hot dog=20.4 pizza=33.9 donut=22.2 cake=18.4 chair=10.8 couch=29.9 potted plant=11.9 bed=36.5 dining table=19.8 toilet=39.3 tv=37.2 laptop=39.8 mouse=24.8 remote=5.5 keyboard=28.5 cell phone=13.3 microwave=29.4 oven=23.1 toaster=0.0 sink=18.3 refrigerator=31.8 book=3.1 clock=25.8 vase=14.0 scissors=14.4 teddy bear=28.3 hair drier=0.0 toothbrush=4.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.1 [Epoch 74][Batch 99], Speed: 348.239 samples/sec, CrossEntropy=2.704, SmoothL1=1.218 [Epoch 74][Batch 199], Speed: 352.181 samples/sec, CrossEntropy=2.701, SmoothL1=1.221 [Epoch 74][Batch 299], Speed: 345.337 samples/sec, CrossEntropy=2.698, SmoothL1=1.208 [Epoch 74][Batch 399], Speed: 351.059 samples/sec, CrossEntropy=2.693, SmoothL1=1.206 [Epoch 74][Batch 499], Speed: 355.969 samples/sec, CrossEntropy=2.694, SmoothL1=1.202 [Epoch 74][Batch 599], Speed: 346.249 samples/sec, CrossEntropy=2.694, SmoothL1=1.196 [Epoch 74][Batch 699], Speed: 350.777 samples/sec, CrossEntropy=2.686, SmoothL1=1.193 [Epoch 74][Batch 799], Speed: 356.237 samples/sec, CrossEntropy=2.685, SmoothL1=1.190 [Epoch 74][Batch 899], Speed: 336.943 samples/sec, CrossEntropy=2.682, SmoothL1=1.189 [Epoch 74][Batch 999], Speed: 353.606 samples/sec, CrossEntropy=2.677, SmoothL1=1.187 [Epoch 74][Batch 1099], Speed: 346.819 samples/sec, CrossEntropy=2.673, SmoothL1=1.184 [Epoch 74][Batch 1199], Speed: 356.850 samples/sec, CrossEntropy=2.673, SmoothL1=1.181 [Epoch 74][Batch 1299], Speed: 349.876 samples/sec, CrossEntropy=2.672, SmoothL1=1.180 [Epoch 74][Batch 1399], Speed: 354.882 samples/sec, CrossEntropy=2.672, SmoothL1=1.180 [Epoch 74][Batch 1499], Speed: 360.859 samples/sec, CrossEntropy=2.672, SmoothL1=1.179 [Epoch 74][Batch 1599], Speed: 361.635 samples/sec, CrossEntropy=2.670, SmoothL1=1.180 [Epoch 74][Batch 1699], Speed: 358.777 samples/sec, CrossEntropy=2.671, SmoothL1=1.180 [Epoch 74][Batch 1799], Speed: 351.652 samples/sec, CrossEntropy=2.671, SmoothL1=1.182 [Epoch 74] Training cost: 335.210, CrossEntropy=2.670, SmoothL1=1.181 [Epoch 74] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.207 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.365 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.216 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.034 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.369 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.205 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.291 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.059 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.324 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.518 person=30.6 bicycle=13.7 car=17.2 motorcycle=23.5 airplane=40.4 bus=45.1 train=48.6 truck=16.5 boat=9.0 traffic light=6.3 fire hydrant=37.1 stop sign=42.7 parking meter=26.5 bench=11.7 bird=13.0 cat=45.3 dog=38.2 horse=34.5 sheep=26.1 cow=25.5 elephant=39.9 bear=47.4 zebra=44.2 giraffe=46.4 backpack=2.5 umbrella=19.2 handbag=2.1 tie=10.9 suitcase=14.0 frisbee=22.1 skis=7.9 snowboard=9.0 sports ball=15.8 kite=12.9 baseball bat=8.5 baseball glove=9.8 skateboard=21.3 surfboard=14.1 tennis racket=20.6 bottle=10.2 wine glass=10.7 cup=15.2 fork=9.1 knife=4.1 spoon=2.8 bowl=21.4 banana=11.3 apple=8.7 sandwich=24.2 orange=16.7 broccoli=13.9 carrot=7.7 hot dog=18.4 pizza=31.9 donut=24.6 cake=18.0 chair=11.1 couch=30.9 potted plant=10.7 bed=30.1 dining table=20.1 toilet=43.1 tv=38.0 laptop=40.6 mouse=25.2 remote=5.6 keyboard=27.9 cell phone=12.8 microwave=28.9 oven=22.2 toaster=3.6 sink=17.0 refrigerator=32.9 book=3.1 clock=26.5 vase=14.2 scissors=15.3 teddy bear=26.4 hair drier=0.0 toothbrush=3.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.7 [Epoch 75][Batch 99], Speed: 353.010 samples/sec, CrossEntropy=2.651, SmoothL1=1.185 [Epoch 75][Batch 199], Speed: 356.421 samples/sec, CrossEntropy=2.663, SmoothL1=1.189 [Epoch 75][Batch 299], Speed: 363.502 samples/sec, CrossEntropy=2.672, SmoothL1=1.188 [Epoch 75][Batch 399], Speed: 355.177 samples/sec, CrossEntropy=2.678, SmoothL1=1.192 [Epoch 75][Batch 499], Speed: 354.698 samples/sec, CrossEntropy=2.675, SmoothL1=1.188 [Epoch 75][Batch 599], Speed: 346.640 samples/sec, CrossEntropy=2.671, SmoothL1=1.182 [Epoch 75][Batch 699], Speed: 366.091 samples/sec, CrossEntropy=2.669, SmoothL1=1.180 [Epoch 75][Batch 799], Speed: 361.704 samples/sec, CrossEntropy=2.670, SmoothL1=1.183 [Epoch 75][Batch 899], Speed: 353.404 samples/sec, CrossEntropy=2.670, SmoothL1=1.182 [Epoch 75][Batch 999], Speed: 349.336 samples/sec, CrossEntropy=2.673, SmoothL1=1.183 [Epoch 75][Batch 1099], Speed: 355.657 samples/sec, CrossEntropy=2.667, SmoothL1=1.180 [Epoch 75][Batch 1199], Speed: 344.167 samples/sec, CrossEntropy=2.666, SmoothL1=1.181 [Epoch 75][Batch 1299], Speed: 345.648 samples/sec, CrossEntropy=2.664, SmoothL1=1.179 [Epoch 75][Batch 1399], Speed: 357.826 samples/sec, CrossEntropy=2.663, SmoothL1=1.180 [Epoch 75][Batch 1499], Speed: 357.572 samples/sec, CrossEntropy=2.666, SmoothL1=1.181 [Epoch 75][Batch 1599], Speed: 355.957 samples/sec, CrossEntropy=2.667, SmoothL1=1.182 [Epoch 75][Batch 1699], Speed: 347.978 samples/sec, CrossEntropy=2.668, SmoothL1=1.180 [Epoch 75][Batch 1799], Speed: 351.736 samples/sec, CrossEntropy=2.666, SmoothL1=1.180 [Epoch 75] Training cost: 334.699, CrossEntropy=2.669, SmoothL1=1.181 [Epoch 75] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.209 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.371 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.216 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.033 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.366 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.205 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.293 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.305 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.059 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.331 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.518 person=30.5 bicycle=13.0 car=16.8 motorcycle=22.1 airplane=42.2 bus=44.2 train=45.3 truck=17.3 boat=9.5 traffic light=6.1 fire hydrant=40.1 stop sign=39.7 parking meter=23.7 bench=11.7 bird=13.3 cat=48.0 dog=39.5 horse=33.1 sheep=26.6 cow=26.4 elephant=39.9 bear=46.6 zebra=42.4 giraffe=45.8 backpack=2.7 umbrella=19.3 handbag=2.4 tie=11.1 suitcase=13.1 frisbee=22.8 skis=7.9 snowboard=9.5 sports ball=16.1 kite=13.5 baseball bat=9.2 baseball glove=9.7 skateboard=20.3 surfboard=14.8 tennis racket=22.8 bottle=9.8 wine glass=10.9 cup=15.7 fork=10.1 knife=3.4 spoon=3.8 bowl=22.0 banana=12.6 apple=9.0 sandwich=25.6 orange=18.0 broccoli=12.8 carrot=8.5 hot dog=20.8 pizza=32.9 donut=23.6 cake=17.7 chair=9.9 couch=30.2 potted plant=11.4 bed=33.4 dining table=20.3 toilet=40.2 tv=36.6 laptop=38.2 mouse=26.8 remote=5.6 keyboard=28.7 cell phone=13.8 microwave=28.7 oven=22.4 toaster=5.9 sink=17.8 refrigerator=31.7 book=3.1 clock=27.1 vase=14.5 scissors=15.6 teddy bear=28.3 hair drier=0.0 toothbrush=3.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.9 [Epoch 76][Batch 99], Speed: 347.438 samples/sec, CrossEntropy=2.649, SmoothL1=1.167 [Epoch 76][Batch 199], Speed: 361.692 samples/sec, CrossEntropy=2.650, SmoothL1=1.160 [Epoch 76][Batch 299], Speed: 361.523 samples/sec, CrossEntropy=2.654, SmoothL1=1.158 [Epoch 76][Batch 399], Speed: 357.357 samples/sec, CrossEntropy=2.661, SmoothL1=1.164 [Epoch 76][Batch 499], Speed: 363.307 samples/sec, CrossEntropy=2.652, SmoothL1=1.160 [Epoch 76][Batch 599], Speed: 352.000 samples/sec, CrossEntropy=2.653, SmoothL1=1.168 [Epoch 76][Batch 699], Speed: 352.888 samples/sec, CrossEntropy=2.657, SmoothL1=1.172 [Epoch 76][Batch 799], Speed: 350.248 samples/sec, CrossEntropy=2.656, SmoothL1=1.172 [Epoch 76][Batch 899], Speed: 354.557 samples/sec, CrossEntropy=2.657, SmoothL1=1.172 [Epoch 76][Batch 999], Speed: 345.504 samples/sec, CrossEntropy=2.661, SmoothL1=1.175 [Epoch 76][Batch 1099], Speed: 357.649 samples/sec, CrossEntropy=2.666, SmoothL1=1.178 [Epoch 76][Batch 1199], Speed: 343.889 samples/sec, CrossEntropy=2.662, SmoothL1=1.174 [Epoch 76][Batch 1299], Speed: 356.302 samples/sec, CrossEntropy=2.665, SmoothL1=1.175 [Epoch 76][Batch 1399], Speed: 339.670 samples/sec, CrossEntropy=2.666, SmoothL1=1.176 [Epoch 76][Batch 1499], Speed: 351.767 samples/sec, CrossEntropy=2.665, SmoothL1=1.178 [Epoch 76][Batch 1599], Speed: 344.017 samples/sec, CrossEntropy=2.666, SmoothL1=1.178 [Epoch 76][Batch 1699], Speed: 353.028 samples/sec, CrossEntropy=2.666, SmoothL1=1.178 [Epoch 76][Batch 1799], Speed: 355.524 samples/sec, CrossEntropy=2.667, SmoothL1=1.179 [Epoch 76] Training cost: 334.819, CrossEntropy=2.665, SmoothL1=1.178 [Epoch 76] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.211 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.371 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.214 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.034 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.224 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.373 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.208 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.298 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.311 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.059 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.338 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.526 person=30.9 bicycle=13.8 car=17.3 motorcycle=24.4 airplane=39.3 bus=45.1 train=49.2 truck=17.1 boat=9.5 traffic light=5.8 fire hydrant=36.5 stop sign=42.6 parking meter=24.0 bench=11.6 bird=11.9 cat=48.0 dog=40.0 horse=32.8 sheep=27.3 cow=26.5 elephant=39.3 bear=51.9 zebra=42.4 giraffe=46.8 backpack=2.7 umbrella=20.5 handbag=1.8 tie=10.5 suitcase=15.4 frisbee=24.4 skis=8.6 snowboard=7.6 sports ball=15.6 kite=15.0 baseball bat=8.7 baseball glove=9.5 skateboard=22.9 surfboard=14.8 tennis racket=22.7 bottle=10.0 wine glass=11.0 cup=16.2 fork=10.3 knife=4.0 spoon=3.6 bowl=23.2 banana=11.9 apple=8.6 sandwich=25.1 orange=19.2 broccoli=13.7 carrot=9.5 hot dog=20.4 pizza=31.9 donut=22.5 cake=18.2 chair=9.9 couch=29.5 potted plant=10.3 bed=33.4 dining table=20.5 toilet=41.7 tv=37.9 laptop=39.0 mouse=24.0 remote=5.2 keyboard=28.4 cell phone=14.8 microwave=30.1 oven=21.4 toaster=5.9 sink=19.1 refrigerator=32.5 book=3.5 clock=27.4 vase=12.8 scissors=15.6 teddy bear=27.4 hair drier=0.0 toothbrush=3.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.1 [Epoch 77][Batch 99], Speed: 342.545 samples/sec, CrossEntropy=2.656, SmoothL1=1.164 [Epoch 77][Batch 199], Speed: 362.549 samples/sec, CrossEntropy=2.661, SmoothL1=1.180 [Epoch 77][Batch 299], Speed: 341.592 samples/sec, CrossEntropy=2.660, SmoothL1=1.168 [Epoch 77][Batch 399], Speed: 351.799 samples/sec, CrossEntropy=2.659, SmoothL1=1.174 [Epoch 77][Batch 499], Speed: 350.746 samples/sec, CrossEntropy=2.660, SmoothL1=1.177 [Epoch 77][Batch 599], Speed: 359.411 samples/sec, CrossEntropy=2.664, SmoothL1=1.187 [Epoch 77][Batch 699], Speed: 349.675 samples/sec, CrossEntropy=2.658, SmoothL1=1.185 [Epoch 77][Batch 799], Speed: 357.819 samples/sec, CrossEntropy=2.657, SmoothL1=1.182 [Epoch 77][Batch 899], Speed: 354.734 samples/sec, CrossEntropy=2.657, SmoothL1=1.180 [Epoch 77][Batch 999], Speed: 347.702 samples/sec, CrossEntropy=2.656, SmoothL1=1.180 [Epoch 77][Batch 1099], Speed: 348.957 samples/sec, CrossEntropy=2.654, SmoothL1=1.177 [Epoch 77][Batch 1199], Speed: 346.070 samples/sec, CrossEntropy=2.654, SmoothL1=1.177 [Epoch 77][Batch 1299], Speed: 349.754 samples/sec, CrossEntropy=2.659, SmoothL1=1.179 [Epoch 77][Batch 1399], Speed: 342.568 samples/sec, CrossEntropy=2.660, SmoothL1=1.180 [Epoch 77][Batch 1499], Speed: 354.516 samples/sec, CrossEntropy=2.661, SmoothL1=1.180 [Epoch 77][Batch 1599], Speed: 351.981 samples/sec, CrossEntropy=2.663, SmoothL1=1.181 [Epoch 77][Batch 1699], Speed: 352.425 samples/sec, CrossEntropy=2.661, SmoothL1=1.178 [Epoch 77][Batch 1799], Speed: 352.492 samples/sec, CrossEntropy=2.661, SmoothL1=1.179 [Epoch 77] Training cost: 335.291, CrossEntropy=2.662, SmoothL1=1.178 [Epoch 77] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.208 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.374 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.214 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.038 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.368 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.206 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.295 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.308 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.062 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.338 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.523 person=30.4 bicycle=14.7 car=16.9 motorcycle=23.9 airplane=40.2 bus=43.3 train=47.3 truck=15.9 boat=9.8 traffic light=6.5 fire hydrant=40.3 stop sign=41.7 parking meter=22.6 bench=11.1 bird=13.1 cat=46.6 dog=40.2 horse=32.7 sheep=26.8 cow=27.5 elephant=40.0 bear=46.5 zebra=44.4 giraffe=45.6 backpack=2.4 umbrella=19.5 handbag=2.0 tie=10.9 suitcase=12.7 frisbee=23.2 skis=8.4 snowboard=7.4 sports ball=15.8 kite=13.2 baseball bat=7.0 baseball glove=8.2 skateboard=23.3 surfboard=15.1 tennis racket=21.1 bottle=9.8 wine glass=10.7 cup=16.6 fork=10.0 knife=4.3 spoon=3.6 bowl=21.7 banana=11.2 apple=7.6 sandwich=24.5 orange=18.6 broccoli=11.3 carrot=8.2 hot dog=18.9 pizza=34.9 donut=21.8 cake=16.4 chair=10.3 couch=28.6 potted plant=10.8 bed=34.1 dining table=20.2 toilet=40.4 tv=36.8 laptop=40.0 mouse=26.1 remote=5.4 keyboard=29.5 cell phone=13.4 microwave=31.5 oven=23.2 toaster=1.7 sink=18.8 refrigerator=32.8 book=3.1 clock=28.4 vase=13.5 scissors=19.7 teddy bear=26.2 hair drier=0.0 toothbrush=4.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =20.8 [Epoch 78][Batch 99], Speed: 355.956 samples/sec, CrossEntropy=2.721, SmoothL1=1.230 [Epoch 78][Batch 199], Speed: 356.729 samples/sec, CrossEntropy=2.682, SmoothL1=1.195 [Epoch 78][Batch 299], Speed: 353.411 samples/sec, CrossEntropy=2.679, SmoothL1=1.183 [Epoch 78][Batch 399], Speed: 346.083 samples/sec, CrossEntropy=2.672, SmoothL1=1.180 [Epoch 78][Batch 499], Speed: 353.186 samples/sec, CrossEntropy=2.669, SmoothL1=1.174 [Epoch 78][Batch 599], Speed: 349.953 samples/sec, CrossEntropy=2.668, SmoothL1=1.173 [Epoch 78][Batch 699], Speed: 349.605 samples/sec, CrossEntropy=2.668, SmoothL1=1.174 [Epoch 78][Batch 799], Speed: 363.926 samples/sec, CrossEntropy=2.664, SmoothL1=1.171 [Epoch 78][Batch 899], Speed: 357.141 samples/sec, CrossEntropy=2.662, SmoothL1=1.173 [Epoch 78][Batch 999], Speed: 350.102 samples/sec, CrossEntropy=2.659, SmoothL1=1.173 [Epoch 78][Batch 1099], Speed: 349.030 samples/sec, CrossEntropy=2.658, SmoothL1=1.172 [Epoch 78][Batch 1199], Speed: 357.497 samples/sec, CrossEntropy=2.656, SmoothL1=1.170 [Epoch 78][Batch 1299], Speed: 360.724 samples/sec, CrossEntropy=2.658, SmoothL1=1.171 [Epoch 78][Batch 1399], Speed: 360.351 samples/sec, CrossEntropy=2.658, SmoothL1=1.170 [Epoch 78][Batch 1499], Speed: 355.634 samples/sec, CrossEntropy=2.660, SmoothL1=1.173 [Epoch 78][Batch 1599], Speed: 359.921 samples/sec, CrossEntropy=2.665, SmoothL1=1.173 [Epoch 78][Batch 1699], Speed: 344.507 samples/sec, CrossEntropy=2.664, SmoothL1=1.173 [Epoch 78][Batch 1799], Speed: 348.951 samples/sec, CrossEntropy=2.663, SmoothL1=1.173 [Epoch 78] Training cost: 334.903, CrossEntropy=2.663, SmoothL1=1.173 [Epoch 78] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.212 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.373 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.035 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.226 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.371 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.208 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.297 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.309 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.059 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.336 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.515 person=31.1 bicycle=14.7 car=17.4 motorcycle=24.0 airplane=38.9 bus=44.5 train=47.3 truck=16.8 boat=9.3 traffic light=6.0 fire hydrant=39.1 stop sign=42.4 parking meter=26.8 bench=11.5 bird=13.3 cat=47.0 dog=42.1 horse=33.8 sheep=26.2 cow=28.0 elephant=41.4 bear=52.1 zebra=43.7 giraffe=46.4 backpack=2.6 umbrella=21.1 handbag=2.2 tie=11.6 suitcase=14.3 frisbee=25.3 skis=7.7 snowboard=7.7 sports ball=17.2 kite=12.4 baseball bat=8.8 baseball glove=8.6 skateboard=20.4 surfboard=13.9 tennis racket=23.0 bottle=10.4 wine glass=10.3 cup=15.7 fork=9.8 knife=4.0 spoon=3.6 bowl=21.7 banana=11.6 apple=8.9 sandwich=27.4 orange=17.2 broccoli=13.5 carrot=8.0 hot dog=19.0 pizza=33.8 donut=23.3 cake=16.4 chair=11.2 couch=29.4 potted plant=10.8 bed=30.4 dining table=20.2 toilet=41.6 tv=39.5 laptop=40.1 mouse=27.8 remote=4.6 keyboard=31.9 cell phone=14.0 microwave=27.7 oven=23.4 toaster=3.0 sink=18.7 refrigerator=31.0 book=3.0 clock=27.1 vase=15.1 scissors=19.5 teddy bear=29.2 hair drier=0.0 toothbrush=2.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.2 [Epoch 79][Batch 99], Speed: 360.601 samples/sec, CrossEntropy=2.682, SmoothL1=1.176 [Epoch 79][Batch 199], Speed: 350.262 samples/sec, CrossEntropy=2.657, SmoothL1=1.168 [Epoch 79][Batch 299], Speed: 354.328 samples/sec, CrossEntropy=2.662, SmoothL1=1.172 [Epoch 79][Batch 399], Speed: 356.640 samples/sec, CrossEntropy=2.651, SmoothL1=1.169 [Epoch 79][Batch 499], Speed: 349.462 samples/sec, CrossEntropy=2.656, SmoothL1=1.170 [Epoch 79][Batch 599], Speed: 361.795 samples/sec, CrossEntropy=2.659, SmoothL1=1.168 [Epoch 79][Batch 699], Speed: 357.891 samples/sec, CrossEntropy=2.648, SmoothL1=1.162 [Epoch 79][Batch 799], Speed: 346.992 samples/sec, CrossEntropy=2.642, SmoothL1=1.161 [Epoch 79][Batch 899], Speed: 355.746 samples/sec, CrossEntropy=2.642, SmoothL1=1.161 [Epoch 79][Batch 999], Speed: 352.277 samples/sec, CrossEntropy=2.638, SmoothL1=1.160 [Epoch 79][Batch 1099], Speed: 341.187 samples/sec, CrossEntropy=2.638, SmoothL1=1.164 [Epoch 79][Batch 1199], Speed: 352.016 samples/sec, CrossEntropy=2.643, SmoothL1=1.166 [Epoch 79][Batch 1299], Speed: 353.870 samples/sec, CrossEntropy=2.645, SmoothL1=1.168 [Epoch 79][Batch 1399], Speed: 350.993 samples/sec, CrossEntropy=2.644, SmoothL1=1.166 [Epoch 79][Batch 1499], Speed: 347.370 samples/sec, CrossEntropy=2.642, SmoothL1=1.166 [Epoch 79][Batch 1599], Speed: 358.575 samples/sec, CrossEntropy=2.644, SmoothL1=1.166 [Epoch 79][Batch 1699], Speed: 348.072 samples/sec, CrossEntropy=2.646, SmoothL1=1.169 [Epoch 79][Batch 1799], Speed: 352.464 samples/sec, CrossEntropy=2.649, SmoothL1=1.169 [Epoch 79] Training cost: 335.671, CrossEntropy=2.648, SmoothL1=1.169 [Epoch 79] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.212 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.374 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.036 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.224 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.375 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.207 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.295 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.308 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.060 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.339 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.517 person=31.3 bicycle=14.3 car=17.1 motorcycle=23.1 airplane=39.4 bus=44.8 train=46.6 truck=18.1 boat=9.2 traffic light=6.1 fire hydrant=40.1 stop sign=41.3 parking meter=26.7 bench=11.6 bird=12.9 cat=48.6 dog=42.7 horse=33.3 sheep=27.4 cow=26.5 elephant=40.3 bear=44.4 zebra=42.8 giraffe=44.5 backpack=2.3 umbrella=19.1 handbag=2.4 tie=11.3 suitcase=15.4 frisbee=25.6 skis=8.4 snowboard=8.1 sports ball=16.3 kite=12.7 baseball bat=9.7 baseball glove=9.1 skateboard=21.4 surfboard=14.7 tennis racket=22.0 bottle=10.3 wine glass=10.5 cup=16.7 fork=9.6 knife=4.1 spoon=3.4 bowl=21.9 banana=12.0 apple=8.9 sandwich=24.0 orange=18.0 broccoli=13.9 carrot=8.0 hot dog=19.7 pizza=33.9 donut=24.0 cake=18.1 chair=11.0 couch=31.9 potted plant=10.6 bed=36.0 dining table=20.3 toilet=40.9 tv=39.2 laptop=40.6 mouse=27.4 remote=6.0 keyboard=27.1 cell phone=14.8 microwave=29.1 oven=23.3 toaster=3.6 sink=17.8 refrigerator=31.7 book=3.3 clock=27.3 vase=14.1 scissors=18.7 teddy bear=28.4 hair drier=0.0 toothbrush=3.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.2 [Epoch 80][Batch 99], Speed: 351.379 samples/sec, CrossEntropy=2.659, SmoothL1=1.171 [Epoch 80][Batch 199], Speed: 354.978 samples/sec, CrossEntropy=2.688, SmoothL1=1.184 [Epoch 80][Batch 299], Speed: 357.107 samples/sec, CrossEntropy=2.663, SmoothL1=1.175 [Epoch 80][Batch 399], Speed: 346.944 samples/sec, CrossEntropy=2.673, SmoothL1=1.180 [Epoch 80][Batch 499], Speed: 368.292 samples/sec, CrossEntropy=2.675, SmoothL1=1.181 [Epoch 80][Batch 599], Speed: 366.327 samples/sec, CrossEntropy=2.676, SmoothL1=1.182 [Epoch 80][Batch 699], Speed: 359.263 samples/sec, CrossEntropy=2.670, SmoothL1=1.180 [Epoch 80][Batch 799], Speed: 351.267 samples/sec, CrossEntropy=2.664, SmoothL1=1.174 [Epoch 80][Batch 899], Speed: 350.587 samples/sec, CrossEntropy=2.660, SmoothL1=1.172 [Epoch 80][Batch 999], Speed: 345.808 samples/sec, CrossEntropy=2.657, SmoothL1=1.168 [Epoch 80][Batch 1099], Speed: 355.195 samples/sec, CrossEntropy=2.654, SmoothL1=1.166 [Epoch 80][Batch 1199], Speed: 349.661 samples/sec, CrossEntropy=2.653, SmoothL1=1.167 [Epoch 80][Batch 1299], Speed: 350.452 samples/sec, CrossEntropy=2.653, SmoothL1=1.170 [Epoch 80][Batch 1399], Speed: 356.213 samples/sec, CrossEntropy=2.654, SmoothL1=1.170 [Epoch 80][Batch 1499], Speed: 353.900 samples/sec, CrossEntropy=2.656, SmoothL1=1.173 [Epoch 80][Batch 1599], Speed: 347.535 samples/sec, CrossEntropy=2.654, SmoothL1=1.171 [Epoch 80][Batch 1699], Speed: 348.509 samples/sec, CrossEntropy=2.651, SmoothL1=1.169 [Epoch 80][Batch 1799], Speed: 358.834 samples/sec, CrossEntropy=2.654, SmoothL1=1.170 [Epoch 80] Training cost: 335.457, CrossEntropy=2.654, SmoothL1=1.171 [Epoch 80] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.212 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.373 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.034 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.222 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.378 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.207 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.292 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.057 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.326 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.526 person=31.1 bicycle=15.3 car=17.1 motorcycle=24.2 airplane=42.5 bus=44.2 train=46.8 truck=17.1 boat=9.2 traffic light=5.9 fire hydrant=37.2 stop sign=42.9 parking meter=23.3 bench=11.8 bird=14.0 cat=51.1 dog=41.8 horse=34.6 sheep=26.7 cow=27.4 elephant=39.9 bear=47.4 zebra=41.7 giraffe=45.7 backpack=2.5 umbrella=20.9 handbag=2.0 tie=11.5 suitcase=14.7 frisbee=23.9 skis=9.0 snowboard=8.8 sports ball=15.3 kite=14.3 baseball bat=9.1 baseball glove=10.0 skateboard=22.5 surfboard=16.0 tennis racket=22.4 bottle=10.4 wine glass=11.0 cup=16.1 fork=10.3 knife=3.6 spoon=3.7 bowl=20.6 banana=11.5 apple=9.1 sandwich=24.2 orange=17.2 broccoli=12.2 carrot=6.5 hot dog=19.3 pizza=32.0 donut=22.3 cake=17.8 chair=10.9 couch=30.2 potted plant=9.5 bed=32.9 dining table=19.3 toilet=41.3 tv=40.4 laptop=41.4 mouse=25.4 remote=5.1 keyboard=28.6 cell phone=14.6 microwave=30.8 oven=23.2 toaster=8.3 sink=16.9 refrigerator=33.3 book=3.9 clock=25.1 vase=13.6 scissors=17.3 teddy bear=28.8 hair drier=0.0 toothbrush=4.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.2 [Epoch 81][Batch 99], Speed: 355.968 samples/sec, CrossEntropy=2.684, SmoothL1=1.167 [Epoch 81][Batch 199], Speed: 349.153 samples/sec, CrossEntropy=2.666, SmoothL1=1.169 [Epoch 81][Batch 299], Speed: 356.486 samples/sec, CrossEntropy=2.652, SmoothL1=1.162 [Epoch 81][Batch 399], Speed: 344.112 samples/sec, CrossEntropy=2.660, SmoothL1=1.168 [Epoch 81][Batch 499], Speed: 362.613 samples/sec, CrossEntropy=2.672, SmoothL1=1.172 [Epoch 81][Batch 599], Speed: 353.173 samples/sec, CrossEntropy=2.674, SmoothL1=1.174 [Epoch 81][Batch 699], Speed: 363.056 samples/sec, CrossEntropy=2.670, SmoothL1=1.176 [Epoch 81][Batch 799], Speed: 359.709 samples/sec, CrossEntropy=2.666, SmoothL1=1.172 [Epoch 81][Batch 899], Speed: 344.649 samples/sec, CrossEntropy=2.667, SmoothL1=1.174 [Epoch 81][Batch 999], Speed: 345.340 samples/sec, CrossEntropy=2.663, SmoothL1=1.173 [Epoch 81][Batch 1099], Speed: 357.817 samples/sec, CrossEntropy=2.659, SmoothL1=1.171 [Epoch 81][Batch 1199], Speed: 344.020 samples/sec, CrossEntropy=2.658, SmoothL1=1.173 [Epoch 81][Batch 1299], Speed: 345.357 samples/sec, CrossEntropy=2.658, SmoothL1=1.174 [Epoch 81][Batch 1399], Speed: 365.079 samples/sec, CrossEntropy=2.659, SmoothL1=1.173 [Epoch 81][Batch 1499], Speed: 346.371 samples/sec, CrossEntropy=2.659, SmoothL1=1.173 [Epoch 81][Batch 1599], Speed: 352.082 samples/sec, CrossEntropy=2.658, SmoothL1=1.171 [Epoch 81][Batch 1699], Speed: 363.079 samples/sec, CrossEntropy=2.658, SmoothL1=1.171 [Epoch 81][Batch 1799], Speed: 356.382 samples/sec, CrossEntropy=2.659, SmoothL1=1.172 [Epoch 81] Training cost: 335.695, CrossEntropy=2.658, SmoothL1=1.170 [Epoch 81] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.212 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.371 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.220 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.035 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.383 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.207 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.295 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.308 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.061 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.330 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.529 person=30.8 bicycle=14.3 car=17.7 motorcycle=24.6 airplane=38.1 bus=44.9 train=47.3 truck=17.6 boat=8.6 traffic light=5.8 fire hydrant=39.7 stop sign=41.4 parking meter=28.5 bench=11.4 bird=14.0 cat=48.1 dog=41.0 horse=32.9 sheep=26.5 cow=27.0 elephant=39.0 bear=51.6 zebra=42.2 giraffe=44.9 backpack=3.1 umbrella=20.6 handbag=2.3 tie=11.1 suitcase=13.0 frisbee=24.4 skis=8.1 snowboard=8.2 sports ball=15.5 kite=14.1 baseball bat=7.9 baseball glove=10.9 skateboard=21.3 surfboard=14.4 tennis racket=23.0 bottle=10.4 wine glass=10.8 cup=15.7 fork=9.6 knife=4.3 spoon=4.0 bowl=21.2 banana=12.3 apple=9.6 sandwich=24.0 orange=19.3 broccoli=11.6 carrot=7.5 hot dog=19.3 pizza=35.0 donut=21.3 cake=18.4 chair=10.4 couch=30.1 potted plant=10.7 bed=32.4 dining table=18.5 toilet=39.0 tv=40.2 laptop=38.8 mouse=27.2 remote=5.3 keyboard=27.3 cell phone=15.1 microwave=31.6 oven=21.1 toaster=7.1 sink=18.2 refrigerator=34.9 book=3.6 clock=27.3 vase=14.8 scissors=16.1 teddy bear=29.3 hair drier=0.0 toothbrush=4.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.2 [Epoch 82][Batch 99], Speed: 356.699 samples/sec, CrossEntropy=2.692, SmoothL1=1.193 [Epoch 82][Batch 199], Speed: 343.996 samples/sec, CrossEntropy=2.658, SmoothL1=1.181 [Epoch 82][Batch 299], Speed: 351.066 samples/sec, CrossEntropy=2.661, SmoothL1=1.179 [Epoch 82][Batch 399], Speed: 359.806 samples/sec, CrossEntropy=2.645, SmoothL1=1.174 [Epoch 82][Batch 499], Speed: 350.307 samples/sec, CrossEntropy=2.652, SmoothL1=1.172 [Epoch 82][Batch 599], Speed: 358.499 samples/sec, CrossEntropy=2.650, SmoothL1=1.169 [Epoch 82][Batch 699], Speed: 351.507 samples/sec, CrossEntropy=2.651, SmoothL1=1.168 [Epoch 82][Batch 799], Speed: 352.742 samples/sec, CrossEntropy=2.645, SmoothL1=1.164 [Epoch 82][Batch 899], Speed: 356.240 samples/sec, CrossEntropy=2.647, SmoothL1=1.164 [Epoch 82][Batch 999], Speed: 353.603 samples/sec, CrossEntropy=2.649, SmoothL1=1.169 [Epoch 82][Batch 1099], Speed: 355.977 samples/sec, CrossEntropy=2.652, SmoothL1=1.168 [Epoch 82][Batch 1199], Speed: 340.918 samples/sec, CrossEntropy=2.650, SmoothL1=1.167 [Epoch 82][Batch 1299], Speed: 351.603 samples/sec, CrossEntropy=2.649, SmoothL1=1.165 [Epoch 82][Batch 1399], Speed: 343.461 samples/sec, CrossEntropy=2.652, SmoothL1=1.166 [Epoch 82][Batch 1499], Speed: 356.755 samples/sec, CrossEntropy=2.655, SmoothL1=1.166 [Epoch 82][Batch 1599], Speed: 356.700 samples/sec, CrossEntropy=2.655, SmoothL1=1.166 [Epoch 82][Batch 1699], Speed: 349.762 samples/sec, CrossEntropy=2.653, SmoothL1=1.164 [Epoch 82][Batch 1799], Speed: 352.563 samples/sec, CrossEntropy=2.653, SmoothL1=1.164 [Epoch 82] Training cost: 335.369, CrossEntropy=2.653, SmoothL1=1.165 [Epoch 82] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.214 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.376 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.222 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.036 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.378 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.210 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.298 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.311 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.060 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.341 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.520 person=31.1 bicycle=13.3 car=17.7 motorcycle=23.8 airplane=41.3 bus=44.9 train=48.1 truck=16.5 boat=9.7 traffic light=6.0 fire hydrant=37.5 stop sign=42.2 parking meter=23.1 bench=10.9 bird=12.7 cat=51.4 dog=44.4 horse=36.6 sheep=27.7 cow=28.3 elephant=40.8 bear=51.7 zebra=43.8 giraffe=47.3 backpack=3.0 umbrella=20.3 handbag=2.6 tie=11.0 suitcase=13.9 frisbee=24.3 skis=7.8 snowboard=7.9 sports ball=15.7 kite=13.5 baseball bat=9.4 baseball glove=9.6 skateboard=23.0 surfboard=14.6 tennis racket=21.5 bottle=10.5 wine glass=10.8 cup=16.5 fork=10.4 knife=3.8 spoon=4.2 bowl=21.0 banana=12.0 apple=9.2 sandwich=26.3 orange=17.3 broccoli=12.8 carrot=8.4 hot dog=19.2 pizza=34.0 donut=23.2 cake=16.8 chair=10.0 couch=30.4 potted plant=10.5 bed=33.2 dining table=19.0 toilet=41.0 tv=38.8 laptop=39.9 mouse=25.0 remote=5.1 keyboard=29.6 cell phone=14.2 microwave=30.8 oven=21.8 toaster=7.1 sink=17.5 refrigerator=33.5 book=3.4 clock=27.2 vase=14.0 scissors=17.9 teddy bear=28.7 hair drier=0.0 toothbrush=4.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.4 [Epoch 83][Batch 99], Speed: 352.158 samples/sec, CrossEntropy=2.683, SmoothL1=1.148 [Epoch 83][Batch 199], Speed: 358.482 samples/sec, CrossEntropy=2.675, SmoothL1=1.149 [Epoch 83][Batch 299], Speed: 347.318 samples/sec, CrossEntropy=2.667, SmoothL1=1.153 [Epoch 83][Batch 399], Speed: 356.794 samples/sec, CrossEntropy=2.672, SmoothL1=1.155 [Epoch 83][Batch 499], Speed: 347.644 samples/sec, CrossEntropy=2.671, SmoothL1=1.160 [Epoch 83][Batch 599], Speed: 346.754 samples/sec, CrossEntropy=2.665, SmoothL1=1.163 [Epoch 83][Batch 699], Speed: 347.104 samples/sec, CrossEntropy=2.659, SmoothL1=1.163 [Epoch 83][Batch 799], Speed: 346.279 samples/sec, CrossEntropy=2.653, SmoothL1=1.159 [Epoch 83][Batch 899], Speed: 347.801 samples/sec, CrossEntropy=2.649, SmoothL1=1.155 [Epoch 83][Batch 999], Speed: 351.562 samples/sec, CrossEntropy=2.646, SmoothL1=1.157 [Epoch 83][Batch 1099], Speed: 360.578 samples/sec, CrossEntropy=2.645, SmoothL1=1.159 [Epoch 83][Batch 1199], Speed: 357.877 samples/sec, CrossEntropy=2.644, SmoothL1=1.157 [Epoch 83][Batch 1299], Speed: 351.397 samples/sec, CrossEntropy=2.640, SmoothL1=1.155 [Epoch 83][Batch 1399], Speed: 358.982 samples/sec, CrossEntropy=2.642, SmoothL1=1.157 [Epoch 83][Batch 1499], Speed: 354.182 samples/sec, CrossEntropy=2.641, SmoothL1=1.156 [Epoch 83][Batch 1599], Speed: 348.061 samples/sec, CrossEntropy=2.640, SmoothL1=1.156 [Epoch 83][Batch 1699], Speed: 351.830 samples/sec, CrossEntropy=2.639, SmoothL1=1.156 [Epoch 83][Batch 1799], Speed: 362.032 samples/sec, CrossEntropy=2.640, SmoothL1=1.157 [Epoch 83] Training cost: 335.515, CrossEntropy=2.640, SmoothL1=1.156 [Epoch 83] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.212 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.371 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.223 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.035 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.375 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.208 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.298 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.310 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.061 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.338 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.527 person=30.9 bicycle=14.6 car=17.6 motorcycle=24.0 airplane=38.5 bus=43.5 train=46.8 truck=17.1 boat=9.4 traffic light=6.2 fire hydrant=40.0 stop sign=42.1 parking meter=24.9 bench=11.5 bird=12.4 cat=49.9 dog=40.4 horse=35.5 sheep=28.2 cow=28.7 elephant=39.2 bear=49.8 zebra=44.3 giraffe=48.2 backpack=2.6 umbrella=19.7 handbag=2.2 tie=10.8 suitcase=13.7 frisbee=23.5 skis=9.1 snowboard=8.2 sports ball=15.4 kite=14.1 baseball bat=9.4 baseball glove=10.6 skateboard=22.3 surfboard=15.2 tennis racket=22.2 bottle=10.7 wine glass=10.5 cup=16.8 fork=9.7 knife=3.7 spoon=4.3 bowl=21.7 banana=10.8 apple=9.0 sandwich=24.7 orange=19.7 broccoli=12.2 carrot=7.9 hot dog=20.2 pizza=32.7 donut=23.9 cake=18.6 chair=10.5 couch=30.2 potted plant=11.2 bed=32.8 dining table=18.5 toilet=41.4 tv=37.7 laptop=39.1 mouse=27.7 remote=5.3 keyboard=28.6 cell phone=14.2 microwave=30.1 oven=21.9 toaster=2.0 sink=17.5 refrigerator=34.7 book=3.6 clock=27.7 vase=14.0 scissors=16.2 teddy bear=29.1 hair drier=0.0 toothbrush=5.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.2 [Epoch 84][Batch 99], Speed: 355.817 samples/sec, CrossEntropy=2.671, SmoothL1=1.160 [Epoch 84][Batch 199], Speed: 346.193 samples/sec, CrossEntropy=2.647, SmoothL1=1.154 [Epoch 84][Batch 299], Speed: 344.455 samples/sec, CrossEntropy=2.641, SmoothL1=1.152 [Epoch 84][Batch 399], Speed: 349.462 samples/sec, CrossEntropy=2.646, SmoothL1=1.154 [Epoch 84][Batch 499], Speed: 355.447 samples/sec, CrossEntropy=2.653, SmoothL1=1.161 [Epoch 84][Batch 599], Speed: 348.136 samples/sec, CrossEntropy=2.648, SmoothL1=1.157 [Epoch 84][Batch 699], Speed: 349.723 samples/sec, CrossEntropy=2.637, SmoothL1=1.152 [Epoch 84][Batch 799], Speed: 346.533 samples/sec, CrossEntropy=2.633, SmoothL1=1.154 [Epoch 84][Batch 899], Speed: 360.685 samples/sec, CrossEntropy=2.635, SmoothL1=1.153 [Epoch 84][Batch 999], Speed: 357.373 samples/sec, CrossEntropy=2.635, SmoothL1=1.153 [Epoch 84][Batch 1099], Speed: 354.879 samples/sec, CrossEntropy=2.635, SmoothL1=1.152 [Epoch 84][Batch 1199], Speed: 345.838 samples/sec, CrossEntropy=2.636, SmoothL1=1.155 [Epoch 84][Batch 1299], Speed: 347.552 samples/sec, CrossEntropy=2.638, SmoothL1=1.157 [Epoch 84][Batch 1399], Speed: 345.846 samples/sec, CrossEntropy=2.638, SmoothL1=1.156 [Epoch 84][Batch 1499], Speed: 346.332 samples/sec, CrossEntropy=2.640, SmoothL1=1.157 [Epoch 84][Batch 1599], Speed: 351.515 samples/sec, CrossEntropy=2.642, SmoothL1=1.158 [Epoch 84][Batch 1699], Speed: 362.506 samples/sec, CrossEntropy=2.644, SmoothL1=1.158 [Epoch 84][Batch 1799], Speed: 355.775 samples/sec, CrossEntropy=2.645, SmoothL1=1.159 [Epoch 84] Training cost: 334.794, CrossEntropy=2.646, SmoothL1=1.160 [Epoch 84] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.215 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.377 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.224 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.037 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.209 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.300 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.313 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.064 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.528 person=31.0 bicycle=15.0 car=17.6 motorcycle=23.0 airplane=42.3 bus=44.8 train=46.3 truck=17.0 boat=10.0 traffic light=6.4 fire hydrant=39.2 stop sign=44.1 parking meter=27.1 bench=11.1 bird=13.5 cat=48.6 dog=40.7 horse=34.3 sheep=28.4 cow=27.1 elephant=40.9 bear=52.3 zebra=44.5 giraffe=47.1 backpack=2.1 umbrella=19.4 handbag=2.6 tie=11.6 suitcase=13.7 frisbee=23.2 skis=9.1 snowboard=9.3 sports ball=13.9 kite=13.9 baseball bat=9.4 baseball glove=9.3 skateboard=21.6 surfboard=14.4 tennis racket=22.2 bottle=10.9 wine glass=10.2 cup=16.7 fork=9.4 knife=4.0 spoon=4.1 bowl=21.5 banana=12.5 apple=7.8 sandwich=24.7 orange=19.5 broccoli=13.0 carrot=7.3 hot dog=20.7 pizza=32.6 donut=24.3 cake=16.5 chair=10.3 couch=31.6 potted plant=10.5 bed=34.5 dining table=19.9 toilet=42.1 tv=40.6 laptop=40.1 mouse=28.6 remote=6.4 keyboard=29.0 cell phone=15.2 microwave=34.8 oven=24.6 toaster=7.1 sink=18.7 refrigerator=35.0 book=3.1 clock=27.8 vase=13.8 scissors=14.6 teddy bear=28.6 hair drier=0.0 toothbrush=3.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.5 [Epoch 85][Batch 99], Speed: 358.317 samples/sec, CrossEntropy=2.668, SmoothL1=1.190 [Epoch 85][Batch 199], Speed: 346.658 samples/sec, CrossEntropy=2.650, SmoothL1=1.174 [Epoch 85][Batch 299], Speed: 350.300 samples/sec, CrossEntropy=2.661, SmoothL1=1.176 [Epoch 85][Batch 399], Speed: 348.642 samples/sec, CrossEntropy=2.665, SmoothL1=1.173 [Epoch 85][Batch 499], Speed: 359.702 samples/sec, CrossEntropy=2.665, SmoothL1=1.173 [Epoch 85][Batch 599], Speed: 359.917 samples/sec, CrossEntropy=2.649, SmoothL1=1.170 [Epoch 85][Batch 699], Speed: 355.263 samples/sec, CrossEntropy=2.646, SmoothL1=1.171 [Epoch 85][Batch 799], Speed: 355.673 samples/sec, CrossEntropy=2.643, SmoothL1=1.170 [Epoch 85][Batch 899], Speed: 350.457 samples/sec, CrossEntropy=2.643, SmoothL1=1.168 [Epoch 85][Batch 999], Speed: 356.536 samples/sec, CrossEntropy=2.644, SmoothL1=1.166 [Epoch 85][Batch 1099], Speed: 357.585 samples/sec, CrossEntropy=2.642, SmoothL1=1.168 [Epoch 85][Batch 1199], Speed: 357.780 samples/sec, CrossEntropy=2.643, SmoothL1=1.166 [Epoch 85][Batch 1299], Speed: 351.827 samples/sec, CrossEntropy=2.642, SmoothL1=1.164 [Epoch 85][Batch 1399], Speed: 349.475 samples/sec, CrossEntropy=2.642, SmoothL1=1.164 [Epoch 85][Batch 1499], Speed: 351.912 samples/sec, CrossEntropy=2.642, SmoothL1=1.166 [Epoch 85][Batch 1599], Speed: 352.326 samples/sec, CrossEntropy=2.639, SmoothL1=1.166 [Epoch 85][Batch 1699], Speed: 352.435 samples/sec, CrossEntropy=2.638, SmoothL1=1.165 [Epoch 85][Batch 1799], Speed: 351.204 samples/sec, CrossEntropy=2.639, SmoothL1=1.165 [Epoch 85] Training cost: 335.733, CrossEntropy=2.639, SmoothL1=1.164 [Epoch 85] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.213 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.375 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.034 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.377 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.208 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.297 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.309 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.060 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.527 person=31.4 bicycle=13.0 car=16.8 motorcycle=23.8 airplane=42.7 bus=44.2 train=46.9 truck=18.0 boat=9.9 traffic light=5.9 fire hydrant=39.0 stop sign=43.7 parking meter=20.7 bench=11.2 bird=13.3 cat=46.8 dog=41.6 horse=35.6 sheep=28.5 cow=28.7 elephant=39.8 bear=51.6 zebra=42.6 giraffe=46.9 backpack=2.7 umbrella=19.2 handbag=2.4 tie=12.3 suitcase=13.8 frisbee=24.8 skis=8.7 snowboard=8.2 sports ball=16.1 kite=14.2 baseball bat=7.8 baseball glove=10.1 skateboard=22.4 surfboard=14.6 tennis racket=22.2 bottle=10.9 wine glass=11.5 cup=16.0 fork=9.8 knife=3.9 spoon=4.3 bowl=21.1 banana=11.5 apple=9.0 sandwich=24.7 orange=19.5 broccoli=12.3 carrot=8.2 hot dog=19.6 pizza=32.1 donut=23.5 cake=18.4 chair=10.7 couch=30.8 potted plant=11.2 bed=34.4 dining table=20.2 toilet=41.1 tv=37.4 laptop=39.3 mouse=27.9 remote=6.0 keyboard=28.8 cell phone=12.8 microwave=34.2 oven=23.3 toaster=0.0 sink=18.2 refrigerator=33.9 book=4.2 clock=26.8 vase=13.8 scissors=14.2 teddy bear=29.6 hair drier=0.0 toothbrush=3.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.3 [Epoch 86][Batch 99], Speed: 359.291 samples/sec, CrossEntropy=2.645, SmoothL1=1.163 [Epoch 86][Batch 199], Speed: 360.709 samples/sec, CrossEntropy=2.671, SmoothL1=1.167 [Epoch 86][Batch 299], Speed: 349.493 samples/sec, CrossEntropy=2.661, SmoothL1=1.164 [Epoch 86][Batch 399], Speed: 360.619 samples/sec, CrossEntropy=2.661, SmoothL1=1.162 [Epoch 86][Batch 499], Speed: 357.348 samples/sec, CrossEntropy=2.661, SmoothL1=1.159 [Epoch 86][Batch 599], Speed: 355.246 samples/sec, CrossEntropy=2.652, SmoothL1=1.156 [Epoch 86][Batch 699], Speed: 354.901 samples/sec, CrossEntropy=2.639, SmoothL1=1.153 [Epoch 86][Batch 799], Speed: 357.316 samples/sec, CrossEntropy=2.631, SmoothL1=1.153 [Epoch 86][Batch 899], Speed: 342.984 samples/sec, CrossEntropy=2.632, SmoothL1=1.157 [Epoch 86][Batch 999], Speed: 362.684 samples/sec, CrossEntropy=2.632, SmoothL1=1.156 [Epoch 86][Batch 1099], Speed: 352.600 samples/sec, CrossEntropy=2.632, SmoothL1=1.159 [Epoch 86][Batch 1199], Speed: 359.232 samples/sec, CrossEntropy=2.634, SmoothL1=1.160 [Epoch 86][Batch 1299], Speed: 355.718 samples/sec, CrossEntropy=2.633, SmoothL1=1.159 [Epoch 86][Batch 1399], Speed: 350.349 samples/sec, CrossEntropy=2.634, SmoothL1=1.160 [Epoch 86][Batch 1499], Speed: 355.901 samples/sec, CrossEntropy=2.635, SmoothL1=1.159 [Epoch 86][Batch 1599], Speed: 348.475 samples/sec, CrossEntropy=2.634, SmoothL1=1.159 [Epoch 86][Batch 1699], Speed: 351.030 samples/sec, CrossEntropy=2.633, SmoothL1=1.159 [Epoch 86][Batch 1799], Speed: 358.308 samples/sec, CrossEntropy=2.635, SmoothL1=1.160 [Epoch 86] Training cost: 335.310, CrossEntropy=2.634, SmoothL1=1.159 [Epoch 86] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.217 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.377 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.223 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.035 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.384 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.210 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.297 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.310 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.058 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.335 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.521 person=31.5 bicycle=14.2 car=17.0 motorcycle=24.2 airplane=42.1 bus=43.7 train=47.3 truck=18.8 boat=8.9 traffic light=6.0 fire hydrant=39.8 stop sign=43.8 parking meter=24.2 bench=11.5 bird=13.2 cat=49.4 dog=42.7 horse=36.8 sheep=28.7 cow=28.3 elephant=39.8 bear=50.7 zebra=44.4 giraffe=46.0 backpack=2.3 umbrella=19.2 handbag=2.6 tie=10.8 suitcase=13.2 frisbee=26.8 skis=8.9 snowboard=10.4 sports ball=16.8 kite=14.3 baseball bat=9.0 baseball glove=10.0 skateboard=22.4 surfboard=15.9 tennis racket=23.3 bottle=9.0 wine glass=9.7 cup=17.0 fork=9.6 knife=3.9 spoon=3.9 bowl=21.9 banana=12.7 apple=8.9 sandwich=26.7 orange=20.0 broccoli=13.4 carrot=8.6 hot dog=20.8 pizza=34.0 donut=23.8 cake=18.5 chair=10.8 couch=31.2 potted plant=9.5 bed=35.1 dining table=19.9 toilet=42.2 tv=38.7 laptop=40.3 mouse=28.1 remote=5.9 keyboard=29.0 cell phone=14.8 microwave=32.2 oven=23.7 toaster=5.9 sink=19.0 refrigerator=33.2 book=3.6 clock=27.6 vase=13.4 scissors=17.2 teddy bear=30.0 hair drier=0.0 toothbrush=4.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.7 [Epoch 87][Batch 99], Speed: 354.698 samples/sec, CrossEntropy=2.633, SmoothL1=1.127 [Epoch 87][Batch 199], Speed: 356.715 samples/sec, CrossEntropy=2.659, SmoothL1=1.147 [Epoch 87][Batch 299], Speed: 352.162 samples/sec, CrossEntropy=2.647, SmoothL1=1.154 [Epoch 87][Batch 399], Speed: 351.081 samples/sec, CrossEntropy=2.650, SmoothL1=1.155 [Epoch 87][Batch 499], Speed: 345.934 samples/sec, CrossEntropy=2.640, SmoothL1=1.152 [Epoch 87][Batch 599], Speed: 341.861 samples/sec, CrossEntropy=2.637, SmoothL1=1.154 [Epoch 87][Batch 699], Speed: 348.487 samples/sec, CrossEntropy=2.639, SmoothL1=1.160 [Epoch 87][Batch 799], Speed: 348.847 samples/sec, CrossEntropy=2.639, SmoothL1=1.159 [Epoch 87][Batch 899], Speed: 359.113 samples/sec, CrossEntropy=2.634, SmoothL1=1.157 [Epoch 87][Batch 999], Speed: 352.224 samples/sec, CrossEntropy=2.629, SmoothL1=1.154 [Epoch 87][Batch 1099], Speed: 352.464 samples/sec, CrossEntropy=2.631, SmoothL1=1.156 [Epoch 87][Batch 1199], Speed: 359.240 samples/sec, CrossEntropy=2.631, SmoothL1=1.157 [Epoch 87][Batch 1299], Speed: 347.704 samples/sec, CrossEntropy=2.634, SmoothL1=1.159 [Epoch 87][Batch 1399], Speed: 354.251 samples/sec, CrossEntropy=2.631, SmoothL1=1.159 [Epoch 87][Batch 1499], Speed: 344.665 samples/sec, CrossEntropy=2.629, SmoothL1=1.157 [Epoch 87][Batch 1599], Speed: 345.073 samples/sec, CrossEntropy=2.629, SmoothL1=1.158 [Epoch 87][Batch 1699], Speed: 349.414 samples/sec, CrossEntropy=2.630, SmoothL1=1.159 [Epoch 87][Batch 1799], Speed: 357.608 samples/sec, CrossEntropy=2.630, SmoothL1=1.157 [Epoch 87] Training cost: 335.421, CrossEntropy=2.628, SmoothL1=1.157 [Epoch 87] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.215 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.380 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.033 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.233 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.209 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.299 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.312 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.061 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.340 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.531 person=31.2 bicycle=14.5 car=17.2 motorcycle=24.8 airplane=40.9 bus=43.6 train=47.2 truck=17.1 boat=9.4 traffic light=5.9 fire hydrant=37.7 stop sign=41.1 parking meter=26.1 bench=10.8 bird=13.3 cat=50.0 dog=42.5 horse=35.1 sheep=27.7 cow=28.4 elephant=40.6 bear=47.9 zebra=45.2 giraffe=46.9 backpack=3.1 umbrella=20.1 handbag=2.8 tie=12.3 suitcase=15.8 frisbee=26.3 skis=9.1 snowboard=12.0 sports ball=16.7 kite=14.2 baseball bat=9.3 baseball glove=10.8 skateboard=22.2 surfboard=15.3 tennis racket=23.4 bottle=10.6 wine glass=11.1 cup=16.4 fork=10.5 knife=4.2 spoon=4.2 bowl=22.7 banana=12.6 apple=8.0 sandwich=26.0 orange=18.9 broccoli=12.6 carrot=8.2 hot dog=18.6 pizza=33.9 donut=24.6 cake=19.7 chair=11.0 couch=29.6 potted plant=11.9 bed=30.8 dining table=20.7 toilet=37.6 tv=37.5 laptop=38.7 mouse=26.6 remote=5.3 keyboard=29.3 cell phone=14.2 microwave=32.3 oven=22.6 toaster=5.9 sink=19.1 refrigerator=32.3 book=3.2 clock=26.9 vase=13.4 scissors=18.7 teddy bear=30.7 hair drier=0.0 toothbrush=4.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.5 [Epoch 88][Batch 99], Speed: 352.122 samples/sec, CrossEntropy=2.649, SmoothL1=1.195 [Epoch 88][Batch 199], Speed: 345.711 samples/sec, CrossEntropy=2.635, SmoothL1=1.181 [Epoch 88][Batch 299], Speed: 355.347 samples/sec, CrossEntropy=2.642, SmoothL1=1.169 [Epoch 88][Batch 399], Speed: 354.658 samples/sec, CrossEntropy=2.637, SmoothL1=1.171 [Epoch 88][Batch 499], Speed: 354.652 samples/sec, CrossEntropy=2.631, SmoothL1=1.168 [Epoch 88][Batch 599], Speed: 361.524 samples/sec, CrossEntropy=2.638, SmoothL1=1.165 [Epoch 88][Batch 699], Speed: 361.907 samples/sec, CrossEntropy=2.634, SmoothL1=1.162 [Epoch 88][Batch 799], Speed: 364.115 samples/sec, CrossEntropy=2.633, SmoothL1=1.160 [Epoch 88][Batch 899], Speed: 363.417 samples/sec, CrossEntropy=2.628, SmoothL1=1.161 [Epoch 88][Batch 999], Speed: 359.556 samples/sec, CrossEntropy=2.628, SmoothL1=1.159 [Epoch 88][Batch 1099], Speed: 359.151 samples/sec, CrossEntropy=2.625, SmoothL1=1.159 [Epoch 88][Batch 1199], Speed: 353.166 samples/sec, CrossEntropy=2.626, SmoothL1=1.159 [Epoch 88][Batch 1299], Speed: 350.993 samples/sec, CrossEntropy=2.625, SmoothL1=1.160 [Epoch 88][Batch 1399], Speed: 355.033 samples/sec, CrossEntropy=2.627, SmoothL1=1.161 [Epoch 88][Batch 1499], Speed: 347.411 samples/sec, CrossEntropy=2.629, SmoothL1=1.162 [Epoch 88][Batch 1599], Speed: 360.751 samples/sec, CrossEntropy=2.628, SmoothL1=1.162 [Epoch 88][Batch 1699], Speed: 355.147 samples/sec, CrossEntropy=2.628, SmoothL1=1.164 [Epoch 88][Batch 1799], Speed: 355.671 samples/sec, CrossEntropy=2.625, SmoothL1=1.161 [Epoch 88] Training cost: 334.427, CrossEntropy=2.627, SmoothL1=1.161 [Epoch 88] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.213 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.375 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.036 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.370 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.207 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.297 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.309 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.058 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.341 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.514 person=31.7 bicycle=14.6 car=17.5 motorcycle=22.7 airplane=38.6 bus=44.8 train=47.0 truck=18.6 boat=9.8 traffic light=6.3 fire hydrant=40.0 stop sign=42.1 parking meter=29.0 bench=10.2 bird=12.5 cat=46.5 dog=40.6 horse=35.1 sheep=25.4 cow=28.1 elephant=40.8 bear=50.2 zebra=43.5 giraffe=48.1 backpack=2.5 umbrella=20.5 handbag=2.4 tie=11.1 suitcase=13.9 frisbee=26.5 skis=8.6 snowboard=10.5 sports ball=16.6 kite=14.3 baseball bat=8.3 baseball glove=9.7 skateboard=21.2 surfboard=15.6 tennis racket=22.7 bottle=10.9 wine glass=11.1 cup=16.0 fork=10.5 knife=3.3 spoon=3.7 bowl=21.9 banana=12.4 apple=9.0 sandwich=22.3 orange=17.7 broccoli=12.8 carrot=7.5 hot dog=17.4 pizza=33.3 donut=23.1 cake=17.5 chair=10.8 couch=30.9 potted plant=10.6 bed=31.4 dining table=20.4 toilet=38.7 tv=39.9 laptop=40.1 mouse=27.3 remote=5.9 keyboard=27.9 cell phone=13.6 microwave=32.6 oven=24.2 toaster=5.9 sink=19.0 refrigerator=32.4 book=3.8 clock=27.0 vase=14.5 scissors=14.7 teddy bear=28.4 hair drier=0.0 toothbrush=5.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.3 [Epoch 89][Batch 99], Speed: 351.968 samples/sec, CrossEntropy=2.670, SmoothL1=1.179 [Epoch 89][Batch 199], Speed: 354.692 samples/sec, CrossEntropy=2.666, SmoothL1=1.174 [Epoch 89][Batch 299], Speed: 351.567 samples/sec, CrossEntropy=2.665, SmoothL1=1.172 [Epoch 89][Batch 399], Speed: 351.024 samples/sec, CrossEntropy=2.653, SmoothL1=1.165 [Epoch 89][Batch 499], Speed: 357.976 samples/sec, CrossEntropy=2.645, SmoothL1=1.165 [Epoch 89][Batch 599], Speed: 360.142 samples/sec, CrossEntropy=2.641, SmoothL1=1.163 [Epoch 89][Batch 699], Speed: 352.885 samples/sec, CrossEntropy=2.634, SmoothL1=1.163 [Epoch 89][Batch 799], Speed: 362.313 samples/sec, CrossEntropy=2.636, SmoothL1=1.163 [Epoch 89][Batch 899], Speed: 350.796 samples/sec, CrossEntropy=2.629, SmoothL1=1.157 [Epoch 89][Batch 999], Speed: 350.123 samples/sec, CrossEntropy=2.627, SmoothL1=1.156 [Epoch 89][Batch 1099], Speed: 356.382 samples/sec, CrossEntropy=2.630, SmoothL1=1.155 [Epoch 89][Batch 1199], Speed: 363.839 samples/sec, CrossEntropy=2.628, SmoothL1=1.155 [Epoch 89][Batch 1299], Speed: 351.677 samples/sec, CrossEntropy=2.626, SmoothL1=1.154 [Epoch 89][Batch 1399], Speed: 346.029 samples/sec, CrossEntropy=2.627, SmoothL1=1.153 [Epoch 89][Batch 1499], Speed: 349.799 samples/sec, CrossEntropy=2.628, SmoothL1=1.153 [Epoch 89][Batch 1599], Speed: 360.849 samples/sec, CrossEntropy=2.629, SmoothL1=1.154 [Epoch 89][Batch 1699], Speed: 352.968 samples/sec, CrossEntropy=2.628, SmoothL1=1.153 [Epoch 89][Batch 1799], Speed: 359.543 samples/sec, CrossEntropy=2.628, SmoothL1=1.154 [Epoch 89] Training cost: 334.880, CrossEntropy=2.630, SmoothL1=1.155 [Epoch 89] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.214 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.376 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.036 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.208 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.294 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.306 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.061 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.325 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.521 person=31.4 bicycle=13.4 car=17.2 motorcycle=24.9 airplane=43.2 bus=45.3 train=43.4 truck=17.8 boat=8.9 traffic light=6.2 fire hydrant=38.8 stop sign=42.1 parking meter=24.0 bench=11.2 bird=14.1 cat=50.1 dog=42.6 horse=35.6 sheep=27.6 cow=29.2 elephant=40.5 bear=49.8 zebra=44.3 giraffe=46.8 backpack=3.2 umbrella=18.8 handbag=2.3 tie=10.8 suitcase=14.1 frisbee=27.6 skis=9.4 snowboard=9.3 sports ball=16.2 kite=14.0 baseball bat=8.8 baseball glove=10.9 skateboard=21.3 surfboard=14.1 tennis racket=22.5 bottle=10.1 wine glass=10.8 cup=16.0 fork=10.9 knife=3.9 spoon=4.1 bowl=21.2 banana=11.9 apple=8.3 sandwich=26.6 orange=19.6 broccoli=12.7 carrot=8.5 hot dog=20.1 pizza=32.6 donut=23.6 cake=17.2 chair=10.6 couch=29.0 potted plant=10.5 bed=35.3 dining table=19.3 toilet=39.3 tv=38.5 laptop=39.3 mouse=26.1 remote=5.3 keyboard=29.3 cell phone=14.5 microwave=32.1 oven=23.2 toaster=5.9 sink=16.1 refrigerator=32.8 book=3.4 clock=25.8 vase=13.3 scissors=17.9 teddy bear=28.2 hair drier=0.0 toothbrush=4.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.4 [Epoch 90][Batch 99], Speed: 362.017 samples/sec, CrossEntropy=2.634, SmoothL1=1.165 [Epoch 90][Batch 199], Speed: 351.492 samples/sec, CrossEntropy=2.652, SmoothL1=1.161 [Epoch 90][Batch 299], Speed: 352.331 samples/sec, CrossEntropy=2.648, SmoothL1=1.158 [Epoch 90][Batch 399], Speed: 359.919 samples/sec, CrossEntropy=2.644, SmoothL1=1.166 [Epoch 90][Batch 499], Speed: 357.552 samples/sec, CrossEntropy=2.627, SmoothL1=1.160 [Epoch 90][Batch 599], Speed: 348.707 samples/sec, CrossEntropy=2.625, SmoothL1=1.160 [Epoch 90][Batch 699], Speed: 348.979 samples/sec, CrossEntropy=2.625, SmoothL1=1.162 [Epoch 90][Batch 799], Speed: 355.008 samples/sec, CrossEntropy=2.624, SmoothL1=1.159 [Epoch 90][Batch 899], Speed: 348.886 samples/sec, CrossEntropy=2.623, SmoothL1=1.157 [Epoch 90][Batch 999], Speed: 359.620 samples/sec, CrossEntropy=2.622, SmoothL1=1.155 [Epoch 90][Batch 1099], Speed: 360.500 samples/sec, CrossEntropy=2.623, SmoothL1=1.156 [Epoch 90][Batch 1199], Speed: 357.806 samples/sec, CrossEntropy=2.626, SmoothL1=1.157 [Epoch 90][Batch 1299], Speed: 345.731 samples/sec, CrossEntropy=2.626, SmoothL1=1.157 [Epoch 90][Batch 1399], Speed: 354.660 samples/sec, CrossEntropy=2.626, SmoothL1=1.156 [Epoch 90][Batch 1499], Speed: 361.442 samples/sec, CrossEntropy=2.624, SmoothL1=1.153 [Epoch 90][Batch 1599], Speed: 351.839 samples/sec, CrossEntropy=2.623, SmoothL1=1.152 [Epoch 90][Batch 1699], Speed: 350.972 samples/sec, CrossEntropy=2.624, SmoothL1=1.151 [Epoch 90][Batch 1799], Speed: 360.221 samples/sec, CrossEntropy=2.623, SmoothL1=1.152 [Epoch 90] Training cost: 335.102, CrossEntropy=2.624, SmoothL1=1.153 [Epoch 90] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.220 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.382 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.039 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.232 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.388 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.212 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.303 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.316 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.061 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.535 person=31.4 bicycle=15.0 car=18.0 motorcycle=25.1 airplane=41.9 bus=44.8 train=46.9 truck=17.9 boat=8.5 traffic light=6.2 fire hydrant=39.0 stop sign=42.9 parking meter=27.4 bench=12.0 bird=14.5 cat=51.6 dog=43.6 horse=35.7 sheep=29.4 cow=28.3 elephant=41.9 bear=53.3 zebra=45.3 giraffe=45.1 backpack=2.9 umbrella=20.7 handbag=2.4 tie=12.2 suitcase=14.3 frisbee=25.0 skis=9.7 snowboard=8.4 sports ball=16.4 kite=13.5 baseball bat=9.6 baseball glove=10.0 skateboard=21.0 surfboard=14.9 tennis racket=22.3 bottle=10.4 wine glass=10.5 cup=16.7 fork=11.5 knife=4.0 spoon=3.7 bowl=22.2 banana=12.8 apple=9.2 sandwich=26.0 orange=18.9 broccoli=12.5 carrot=8.9 hot dog=18.7 pizza=33.9 donut=23.9 cake=19.1 chair=11.4 couch=31.5 potted plant=10.4 bed=32.9 dining table=20.1 toilet=41.6 tv=38.7 laptop=41.3 mouse=29.0 remote=6.0 keyboard=29.9 cell phone=15.9 microwave=34.9 oven=22.9 toaster=5.9 sink=19.5 refrigerator=35.4 book=3.7 clock=27.6 vase=14.2 scissors=21.1 teddy bear=28.8 hair drier=0.0 toothbrush=4.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.0 [Epoch 91][Batch 99], Speed: 353.896 samples/sec, CrossEntropy=2.574, SmoothL1=1.116 [Epoch 91][Batch 199], Speed: 356.697 samples/sec, CrossEntropy=2.613, SmoothL1=1.152 [Epoch 91][Batch 299], Speed: 356.982 samples/sec, CrossEntropy=2.617, SmoothL1=1.152 [Epoch 91][Batch 399], Speed: 354.467 samples/sec, CrossEntropy=2.626, SmoothL1=1.157 [Epoch 91][Batch 499], Speed: 346.063 samples/sec, CrossEntropy=2.623, SmoothL1=1.157 [Epoch 91][Batch 599], Speed: 359.109 samples/sec, CrossEntropy=2.620, SmoothL1=1.152 [Epoch 91][Batch 699], Speed: 355.513 samples/sec, CrossEntropy=2.617, SmoothL1=1.150 [Epoch 91][Batch 799], Speed: 354.228 samples/sec, CrossEntropy=2.617, SmoothL1=1.150 [Epoch 91][Batch 899], Speed: 364.516 samples/sec, CrossEntropy=2.619, SmoothL1=1.153 [Epoch 91][Batch 999], Speed: 363.618 samples/sec, CrossEntropy=2.616, SmoothL1=1.150 [Epoch 91][Batch 1099], Speed: 349.483 samples/sec, CrossEntropy=2.614, SmoothL1=1.148 [Epoch 91][Batch 1199], Speed: 344.092 samples/sec, CrossEntropy=2.613, SmoothL1=1.146 [Epoch 91][Batch 1299], Speed: 350.693 samples/sec, CrossEntropy=2.615, SmoothL1=1.147 [Epoch 91][Batch 1399], Speed: 343.705 samples/sec, CrossEntropy=2.615, SmoothL1=1.148 [Epoch 91][Batch 1499], Speed: 343.616 samples/sec, CrossEntropy=2.615, SmoothL1=1.147 [Epoch 91][Batch 1599], Speed: 345.731 samples/sec, CrossEntropy=2.616, SmoothL1=1.148 [Epoch 91][Batch 1699], Speed: 348.669 samples/sec, CrossEntropy=2.615, SmoothL1=1.149 [Epoch 91][Batch 1799], Speed: 346.326 samples/sec, CrossEntropy=2.614, SmoothL1=1.146 [Epoch 91] Training cost: 335.690, CrossEntropy=2.615, SmoothL1=1.146 [Epoch 91] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.214 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.374 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.035 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.377 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.209 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.298 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.309 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.061 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.337 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.526 person=30.9 bicycle=13.6 car=18.0 motorcycle=25.0 airplane=41.1 bus=45.7 train=47.4 truck=17.2 boat=10.0 traffic light=6.5 fire hydrant=39.4 stop sign=41.1 parking meter=26.9 bench=10.5 bird=13.2 cat=49.7 dog=40.4 horse=35.2 sheep=26.0 cow=28.3 elephant=39.1 bear=52.8 zebra=42.8 giraffe=45.9 backpack=2.3 umbrella=20.9 handbag=2.3 tie=11.1 suitcase=14.2 frisbee=26.0 skis=8.7 snowboard=8.7 sports ball=16.0 kite=13.6 baseball bat=9.8 baseball glove=10.5 skateboard=21.6 surfboard=14.6 tennis racket=23.6 bottle=10.7 wine glass=10.4 cup=16.8 fork=11.7 knife=4.4 spoon=3.9 bowl=22.4 banana=12.4 apple=8.5 sandwich=24.0 orange=19.5 broccoli=13.1 carrot=9.5 hot dog=18.7 pizza=34.1 donut=23.7 cake=17.5 chair=11.1 couch=28.0 potted plant=10.9 bed=32.7 dining table=20.8 toilet=39.8 tv=39.6 laptop=41.2 mouse=27.0 remote=5.8 keyboard=29.6 cell phone=13.8 microwave=29.8 oven=23.5 toaster=3.0 sink=20.0 refrigerator=32.8 book=3.4 clock=26.3 vase=12.3 scissors=16.7 teddy bear=29.0 hair drier=0.0 toothbrush=3.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.4 [Epoch 92][Batch 99], Speed: 347.087 samples/sec, CrossEntropy=2.688, SmoothL1=1.195 [Epoch 92][Batch 199], Speed: 359.290 samples/sec, CrossEntropy=2.653, SmoothL1=1.163 [Epoch 92][Batch 299], Speed: 350.077 samples/sec, CrossEntropy=2.650, SmoothL1=1.162 [Epoch 92][Batch 399], Speed: 361.206 samples/sec, CrossEntropy=2.644, SmoothL1=1.157 [Epoch 92][Batch 499], Speed: 361.142 samples/sec, CrossEntropy=2.634, SmoothL1=1.155 [Epoch 92][Batch 599], Speed: 355.345 samples/sec, CrossEntropy=2.625, SmoothL1=1.149 [Epoch 92][Batch 699], Speed: 355.662 samples/sec, CrossEntropy=2.617, SmoothL1=1.146 [Epoch 92][Batch 799], Speed: 361.463 samples/sec, CrossEntropy=2.616, SmoothL1=1.149 [Epoch 92][Batch 899], Speed: 357.353 samples/sec, CrossEntropy=2.612, SmoothL1=1.149 [Epoch 92][Batch 999], Speed: 360.843 samples/sec, CrossEntropy=2.608, SmoothL1=1.145 [Epoch 92][Batch 1099], Speed: 347.795 samples/sec, CrossEntropy=2.610, SmoothL1=1.147 [Epoch 92][Batch 1199], Speed: 345.128 samples/sec, CrossEntropy=2.611, SmoothL1=1.148 [Epoch 92][Batch 1299], Speed: 358.419 samples/sec, CrossEntropy=2.608, SmoothL1=1.147 [Epoch 92][Batch 1399], Speed: 354.219 samples/sec, CrossEntropy=2.609, SmoothL1=1.149 [Epoch 92][Batch 1499], Speed: 363.368 samples/sec, CrossEntropy=2.612, SmoothL1=1.148 [Epoch 92][Batch 1599], Speed: 349.454 samples/sec, CrossEntropy=2.609, SmoothL1=1.146 [Epoch 92][Batch 1699], Speed: 348.711 samples/sec, CrossEntropy=2.611, SmoothL1=1.148 [Epoch 92][Batch 1799], Speed: 352.770 samples/sec, CrossEntropy=2.611, SmoothL1=1.147 [Epoch 92] Training cost: 335.178, CrossEntropy=2.610, SmoothL1=1.147 [Epoch 92] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.213 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.374 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.038 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.226 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.208 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.298 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.310 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.060 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.341 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.530 person=30.9 bicycle=15.3 car=17.4 motorcycle=23.4 airplane=41.1 bus=43.1 train=47.7 truck=18.4 boat=9.7 traffic light=6.9 fire hydrant=38.5 stop sign=41.6 parking meter=26.2 bench=11.0 bird=13.8 cat=49.2 dog=40.9 horse=35.2 sheep=28.0 cow=26.3 elephant=40.1 bear=50.1 zebra=42.8 giraffe=47.2 backpack=2.7 umbrella=19.6 handbag=2.6 tie=11.5 suitcase=13.6 frisbee=23.3 skis=10.1 snowboard=9.2 sports ball=15.9 kite=14.5 baseball bat=8.2 baseball glove=10.6 skateboard=22.3 surfboard=15.0 tennis racket=23.0 bottle=10.4 wine glass=9.7 cup=16.2 fork=10.6 knife=4.5 spoon=3.9 bowl=22.6 banana=13.4 apple=8.2 sandwich=25.0 orange=18.0 broccoli=12.4 carrot=8.1 hot dog=19.7 pizza=32.6 donut=24.3 cake=17.7 chair=11.4 couch=30.5 potted plant=10.9 bed=32.8 dining table=20.2 toilet=40.3 tv=37.5 laptop=38.9 mouse=25.1 remote=5.1 keyboard=27.8 cell phone=13.8 microwave=32.2 oven=24.6 toaster=1.5 sink=19.3 refrigerator=32.4 book=4.2 clock=27.0 vase=13.7 scissors=19.3 teddy bear=30.2 hair drier=0.0 toothbrush=3.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.3 [Epoch 93][Batch 99], Speed: 351.533 samples/sec, CrossEntropy=2.656, SmoothL1=1.137 [Epoch 93][Batch 199], Speed: 349.449 samples/sec, CrossEntropy=2.639, SmoothL1=1.135 [Epoch 93][Batch 299], Speed: 345.912 samples/sec, CrossEntropy=2.654, SmoothL1=1.150 [Epoch 93][Batch 399], Speed: 344.824 samples/sec, CrossEntropy=2.631, SmoothL1=1.138 [Epoch 93][Batch 499], Speed: 356.894 samples/sec, CrossEntropy=2.621, SmoothL1=1.133 [Epoch 93][Batch 599], Speed: 348.658 samples/sec, CrossEntropy=2.617, SmoothL1=1.134 [Epoch 93][Batch 699], Speed: 362.644 samples/sec, CrossEntropy=2.618, SmoothL1=1.136 [Epoch 93][Batch 799], Speed: 347.645 samples/sec, CrossEntropy=2.616, SmoothL1=1.139 [Epoch 93][Batch 899], Speed: 363.107 samples/sec, CrossEntropy=2.615, SmoothL1=1.142 [Epoch 93][Batch 999], Speed: 360.733 samples/sec, CrossEntropy=2.614, SmoothL1=1.143 [Epoch 93][Batch 1099], Speed: 353.375 samples/sec, CrossEntropy=2.614, SmoothL1=1.144 [Epoch 93][Batch 1199], Speed: 361.541 samples/sec, CrossEntropy=2.615, SmoothL1=1.144 [Epoch 93][Batch 1299], Speed: 354.218 samples/sec, CrossEntropy=2.613, SmoothL1=1.145 [Epoch 93][Batch 1399], Speed: 352.287 samples/sec, CrossEntropy=2.611, SmoothL1=1.145 [Epoch 93][Batch 1499], Speed: 354.661 samples/sec, CrossEntropy=2.612, SmoothL1=1.146 [Epoch 93][Batch 1599], Speed: 343.403 samples/sec, CrossEntropy=2.613, SmoothL1=1.146 [Epoch 93][Batch 1699], Speed: 346.291 samples/sec, CrossEntropy=2.613, SmoothL1=1.146 [Epoch 93][Batch 1799], Speed: 358.689 samples/sec, CrossEntropy=2.613, SmoothL1=1.146 [Epoch 93] Training cost: 335.336, CrossEntropy=2.614, SmoothL1=1.147 [Epoch 93] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.216 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.377 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.223 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.037 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.224 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.384 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.209 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.300 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.312 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.064 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.338 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.530 person=31.3 bicycle=15.6 car=17.6 motorcycle=23.3 airplane=42.4 bus=46.6 train=47.6 truck=18.8 boat=9.4 traffic light=5.8 fire hydrant=39.8 stop sign=44.5 parking meter=28.1 bench=11.7 bird=13.4 cat=48.2 dog=40.2 horse=34.7 sheep=26.5 cow=27.4 elephant=39.4 bear=52.2 zebra=44.0 giraffe=45.4 backpack=3.0 umbrella=20.1 handbag=2.5 tie=9.8 suitcase=16.0 frisbee=26.0 skis=9.6 snowboard=10.4 sports ball=16.0 kite=14.2 baseball bat=8.9 baseball glove=10.6 skateboard=22.0 surfboard=15.1 tennis racket=23.0 bottle=11.2 wine glass=10.3 cup=15.6 fork=11.0 knife=3.7 spoon=3.4 bowl=21.0 banana=12.3 apple=7.1 sandwich=24.8 orange=17.6 broccoli=12.7 carrot=8.4 hot dog=20.1 pizza=34.0 donut=25.1 cake=18.2 chair=10.9 couch=29.2 potted plant=11.1 bed=32.1 dining table=19.3 toilet=39.8 tv=38.6 laptop=39.9 mouse=28.7 remote=6.0 keyboard=28.3 cell phone=14.8 microwave=32.4 oven=23.8 toaster=4.8 sink=20.2 refrigerator=32.3 book=3.2 clock=28.5 vase=14.2 scissors=14.3 teddy bear=29.2 hair drier=0.0 toothbrush=4.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.6 [Epoch 94][Batch 99], Speed: 361.762 samples/sec, CrossEntropy=2.656, SmoothL1=1.158 [Epoch 94][Batch 199], Speed: 352.216 samples/sec, CrossEntropy=2.605, SmoothL1=1.140 [Epoch 94][Batch 299], Speed: 351.287 samples/sec, CrossEntropy=2.620, SmoothL1=1.144 [Epoch 94][Batch 399], Speed: 347.453 samples/sec, CrossEntropy=2.616, SmoothL1=1.149 [Epoch 94][Batch 499], Speed: 362.975 samples/sec, CrossEntropy=2.612, SmoothL1=1.148 [Epoch 94][Batch 599], Speed: 354.190 samples/sec, CrossEntropy=2.614, SmoothL1=1.151 [Epoch 94][Batch 699], Speed: 360.610 samples/sec, CrossEntropy=2.620, SmoothL1=1.153 [Epoch 94][Batch 799], Speed: 358.302 samples/sec, CrossEntropy=2.612, SmoothL1=1.148 [Epoch 94][Batch 899], Speed: 359.443 samples/sec, CrossEntropy=2.608, SmoothL1=1.144 [Epoch 94][Batch 999], Speed: 347.393 samples/sec, CrossEntropy=2.604, SmoothL1=1.143 [Epoch 94][Batch 1099], Speed: 347.383 samples/sec, CrossEntropy=2.601, SmoothL1=1.142 [Epoch 94][Batch 1199], Speed: 346.264 samples/sec, CrossEntropy=2.602, SmoothL1=1.142 [Epoch 94][Batch 1299], Speed: 358.330 samples/sec, CrossEntropy=2.605, SmoothL1=1.142 [Epoch 94][Batch 1399], Speed: 358.419 samples/sec, CrossEntropy=2.606, SmoothL1=1.139 [Epoch 94][Batch 1499], Speed: 349.338 samples/sec, CrossEntropy=2.604, SmoothL1=1.138 [Epoch 94][Batch 1599], Speed: 347.678 samples/sec, CrossEntropy=2.608, SmoothL1=1.141 [Epoch 94][Batch 1699], Speed: 365.282 samples/sec, CrossEntropy=2.609, SmoothL1=1.142 [Epoch 94][Batch 1799], Speed: 348.606 samples/sec, CrossEntropy=2.611, SmoothL1=1.143 [Epoch 94] Training cost: 335.158, CrossEntropy=2.612, SmoothL1=1.143 [Epoch 94] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.377 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.037 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.385 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.210 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.300 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.313 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.063 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.340 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.525 person=31.7 bicycle=14.7 car=18.2 motorcycle=24.1 airplane=43.0 bus=46.8 train=47.4 truck=18.8 boat=8.4 traffic light=6.9 fire hydrant=40.8 stop sign=43.2 parking meter=23.0 bench=12.1 bird=13.6 cat=47.8 dog=42.5 horse=34.5 sheep=27.6 cow=27.6 elephant=41.0 bear=49.7 zebra=44.5 giraffe=47.6 backpack=2.2 umbrella=21.9 handbag=2.2 tie=12.0 suitcase=14.5 frisbee=24.6 skis=8.9 snowboard=6.9 sports ball=15.3 kite=13.0 baseball bat=9.1 baseball glove=11.1 skateboard=22.4 surfboard=15.0 tennis racket=22.5 bottle=11.0 wine glass=11.6 cup=16.7 fork=11.6 knife=3.7 spoon=2.8 bowl=22.8 banana=13.2 apple=8.4 sandwich=25.6 orange=19.5 broccoli=12.8 carrot=9.4 hot dog=21.7 pizza=34.6 donut=23.4 cake=18.7 chair=11.0 couch=31.8 potted plant=11.1 bed=32.2 dining table=19.9 toilet=39.9 tv=38.0 laptop=40.2 mouse=28.5 remote=5.1 keyboard=28.8 cell phone=14.1 microwave=32.6 oven=25.3 toaster=7.1 sink=19.9 refrigerator=34.6 book=3.7 clock=27.4 vase=14.5 scissors=15.9 teddy bear=30.2 hair drier=0.0 toothbrush=4.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.8 [Epoch 95][Batch 99], Speed: 361.805 samples/sec, CrossEntropy=2.615, SmoothL1=1.134 [Epoch 95][Batch 199], Speed: 353.544 samples/sec, CrossEntropy=2.625, SmoothL1=1.158 [Epoch 95][Batch 299], Speed: 360.058 samples/sec, CrossEntropy=2.617, SmoothL1=1.159 [Epoch 95][Batch 399], Speed: 352.149 samples/sec, CrossEntropy=2.616, SmoothL1=1.163 [Epoch 95][Batch 499], Speed: 354.236 samples/sec, CrossEntropy=2.608, SmoothL1=1.154 [Epoch 95][Batch 599], Speed: 363.933 samples/sec, CrossEntropy=2.606, SmoothL1=1.151 [Epoch 95][Batch 699], Speed: 346.813 samples/sec, CrossEntropy=2.598, SmoothL1=1.145 [Epoch 95][Batch 799], Speed: 364.695 samples/sec, CrossEntropy=2.596, SmoothL1=1.141 [Epoch 95][Batch 899], Speed: 352.170 samples/sec, CrossEntropy=2.602, SmoothL1=1.139 [Epoch 95][Batch 999], Speed: 349.469 samples/sec, CrossEntropy=2.605, SmoothL1=1.141 [Epoch 95][Batch 1099], Speed: 357.805 samples/sec, CrossEntropy=2.602, SmoothL1=1.139 [Epoch 95][Batch 1199], Speed: 350.810 samples/sec, CrossEntropy=2.603, SmoothL1=1.142 [Epoch 95][Batch 1299], Speed: 363.296 samples/sec, CrossEntropy=2.603, SmoothL1=1.141 [Epoch 95][Batch 1399], Speed: 348.804 samples/sec, CrossEntropy=2.606, SmoothL1=1.142 [Epoch 95][Batch 1499], Speed: 348.358 samples/sec, CrossEntropy=2.612, SmoothL1=1.146 [Epoch 95][Batch 1599], Speed: 348.645 samples/sec, CrossEntropy=2.611, SmoothL1=1.146 [Epoch 95][Batch 1699], Speed: 352.683 samples/sec, CrossEntropy=2.610, SmoothL1=1.145 [Epoch 95][Batch 1799], Speed: 359.276 samples/sec, CrossEntropy=2.612, SmoothL1=1.146 [Epoch 95] Training cost: 335.474, CrossEntropy=2.611, SmoothL1=1.145 [Epoch 95] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.214 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.373 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.220 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.036 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.232 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.378 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.208 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.298 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.312 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.063 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.341 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.521 person=31.1 bicycle=14.6 car=18.0 motorcycle=25.5 airplane=42.8 bus=46.1 train=46.1 truck=19.5 boat=9.5 traffic light=6.6 fire hydrant=36.8 stop sign=41.9 parking meter=23.7 bench=11.0 bird=13.2 cat=48.7 dog=40.0 horse=34.5 sheep=29.5 cow=27.5 elephant=43.8 bear=46.9 zebra=45.3 giraffe=48.5 backpack=2.5 umbrella=19.4 handbag=2.2 tie=11.1 suitcase=12.9 frisbee=25.1 skis=9.5 snowboard=9.1 sports ball=16.2 kite=13.9 baseball bat=9.0 baseball glove=10.2 skateboard=20.5 surfboard=16.4 tennis racket=22.9 bottle=10.6 wine glass=11.2 cup=16.6 fork=9.6 knife=4.3 spoon=3.3 bowl=21.7 banana=12.3 apple=8.6 sandwich=22.5 orange=18.1 broccoli=13.0 carrot=8.5 hot dog=18.2 pizza=32.1 donut=23.2 cake=17.7 chair=10.4 couch=29.4 potted plant=11.0 bed=28.0 dining table=18.6 toilet=42.3 tv=39.1 laptop=39.4 mouse=27.3 remote=6.1 keyboard=30.6 cell phone=14.0 microwave=31.6 oven=23.4 toaster=7.1 sink=18.9 refrigerator=35.0 book=3.8 clock=28.4 vase=13.8 scissors=14.6 teddy bear=30.0 hair drier=0.0 toothbrush=4.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.4 [Epoch 96][Batch 99], Speed: 361.185 samples/sec, CrossEntropy=2.576, SmoothL1=1.114 [Epoch 96][Batch 199], Speed: 352.857 samples/sec, CrossEntropy=2.608, SmoothL1=1.137 [Epoch 96][Batch 299], Speed: 340.236 samples/sec, CrossEntropy=2.609, SmoothL1=1.142 [Epoch 96][Batch 399], Speed: 363.564 samples/sec, CrossEntropy=2.590, SmoothL1=1.138 [Epoch 96][Batch 499], Speed: 349.639 samples/sec, CrossEntropy=2.587, SmoothL1=1.137 [Epoch 96][Batch 599], Speed: 350.846 samples/sec, CrossEntropy=2.586, SmoothL1=1.139 [Epoch 96][Batch 699], Speed: 354.901 samples/sec, CrossEntropy=2.590, SmoothL1=1.146 [Epoch 96][Batch 799], Speed: 362.631 samples/sec, CrossEntropy=2.593, SmoothL1=1.147 [Epoch 96][Batch 899], Speed: 351.618 samples/sec, CrossEntropy=2.590, SmoothL1=1.142 [Epoch 96][Batch 999], Speed: 354.853 samples/sec, CrossEntropy=2.588, SmoothL1=1.139 [Epoch 96][Batch 1099], Speed: 356.014 samples/sec, CrossEntropy=2.587, SmoothL1=1.138 [Epoch 96][Batch 1199], Speed: 354.379 samples/sec, CrossEntropy=2.592, SmoothL1=1.140 [Epoch 96][Batch 1299], Speed: 362.624 samples/sec, CrossEntropy=2.593, SmoothL1=1.138 [Epoch 96][Batch 1399], Speed: 364.039 samples/sec, CrossEntropy=2.596, SmoothL1=1.138 [Epoch 96][Batch 1499], Speed: 342.317 samples/sec, CrossEntropy=2.597, SmoothL1=1.139 [Epoch 96][Batch 1599], Speed: 351.859 samples/sec, CrossEntropy=2.595, SmoothL1=1.136 [Epoch 96][Batch 1699], Speed: 362.090 samples/sec, CrossEntropy=2.595, SmoothL1=1.136 [Epoch 96][Batch 1799], Speed: 347.699 samples/sec, CrossEntropy=2.593, SmoothL1=1.135 [Epoch 96] Training cost: 335.034, CrossEntropy=2.593, SmoothL1=1.135 [Epoch 96] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.379 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.228 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.038 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.231 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.390 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.212 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.317 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.063 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.534 person=32.2 bicycle=15.5 car=17.9 motorcycle=24.8 airplane=42.7 bus=46.2 train=46.2 truck=18.6 boat=10.4 traffic light=6.7 fire hydrant=39.9 stop sign=42.9 parking meter=26.1 bench=12.5 bird=13.3 cat=51.0 dog=43.0 horse=36.7 sheep=28.1 cow=27.5 elephant=41.8 bear=51.0 zebra=44.8 giraffe=46.7 backpack=2.9 umbrella=20.2 handbag=2.2 tie=12.4 suitcase=15.2 frisbee=27.1 skis=9.1 snowboard=9.0 sports ball=15.6 kite=14.4 baseball bat=8.4 baseball glove=10.9 skateboard=21.6 surfboard=15.6 tennis racket=22.4 bottle=11.0 wine glass=10.5 cup=17.2 fork=10.2 knife=4.3 spoon=4.3 bowl=22.7 banana=12.8 apple=8.4 sandwich=26.6 orange=18.3 broccoli=13.9 carrot=8.9 hot dog=20.0 pizza=31.6 donut=22.7 cake=16.9 chair=11.2 couch=30.7 potted plant=11.8 bed=34.2 dining table=21.5 toilet=41.9 tv=40.0 laptop=41.0 mouse=29.6 remote=6.1 keyboard=29.4 cell phone=14.7 microwave=33.9 oven=25.4 toaster=2.0 sink=18.9 refrigerator=34.4 book=2.9 clock=27.9 vase=15.2 scissors=14.5 teddy bear=30.0 hair drier=0.0 toothbrush=3.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.9 [Epoch 97][Batch 99], Speed: 353.653 samples/sec, CrossEntropy=2.661, SmoothL1=1.157 [Epoch 97][Batch 199], Speed: 361.471 samples/sec, CrossEntropy=2.644, SmoothL1=1.159 [Epoch 97][Batch 299], Speed: 349.920 samples/sec, CrossEntropy=2.625, SmoothL1=1.151 [Epoch 97][Batch 399], Speed: 355.837 samples/sec, CrossEntropy=2.614, SmoothL1=1.138 [Epoch 97][Batch 499], Speed: 362.262 samples/sec, CrossEntropy=2.603, SmoothL1=1.135 [Epoch 97][Batch 599], Speed: 350.949 samples/sec, CrossEntropy=2.603, SmoothL1=1.134 [Epoch 97][Batch 699], Speed: 343.073 samples/sec, CrossEntropy=2.599, SmoothL1=1.137 [Epoch 97][Batch 799], Speed: 340.749 samples/sec, CrossEntropy=2.598, SmoothL1=1.137 [Epoch 97][Batch 899], Speed: 360.917 samples/sec, CrossEntropy=2.596, SmoothL1=1.137 [Epoch 97][Batch 999], Speed: 358.722 samples/sec, CrossEntropy=2.602, SmoothL1=1.140 [Epoch 97][Batch 1099], Speed: 345.126 samples/sec, CrossEntropy=2.599, SmoothL1=1.140 [Epoch 97][Batch 1199], Speed: 351.098 samples/sec, CrossEntropy=2.603, SmoothL1=1.141 [Epoch 97][Batch 1299], Speed: 363.063 samples/sec, CrossEntropy=2.605, SmoothL1=1.142 [Epoch 97][Batch 1399], Speed: 343.995 samples/sec, CrossEntropy=2.610, SmoothL1=1.142 [Epoch 97][Batch 1499], Speed: 353.996 samples/sec, CrossEntropy=2.610, SmoothL1=1.140 [Epoch 97][Batch 1599], Speed: 357.000 samples/sec, CrossEntropy=2.613, SmoothL1=1.142 [Epoch 97][Batch 1699], Speed: 353.469 samples/sec, CrossEntropy=2.613, SmoothL1=1.142 [Epoch 97][Batch 1799], Speed: 356.512 samples/sec, CrossEntropy=2.611, SmoothL1=1.141 [Epoch 97] Training cost: 335.124, CrossEntropy=2.611, SmoothL1=1.142 [Epoch 97] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.379 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.037 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.226 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.390 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.212 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.301 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.314 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.064 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.338 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.534 person=31.8 bicycle=14.7 car=18.2 motorcycle=23.9 airplane=39.2 bus=45.7 train=47.9 truck=18.5 boat=9.5 traffic light=6.0 fire hydrant=41.7 stop sign=44.7 parking meter=25.5 bench=11.1 bird=13.6 cat=50.7 dog=42.2 horse=36.9 sheep=27.8 cow=28.1 elephant=41.3 bear=49.8 zebra=43.8 giraffe=48.4 backpack=2.0 umbrella=21.0 handbag=2.7 tie=12.0 suitcase=14.1 frisbee=26.2 skis=8.7 snowboard=10.6 sports ball=16.5 kite=13.9 baseball bat=8.9 baseball glove=11.2 skateboard=22.9 surfboard=15.1 tennis racket=23.5 bottle=11.2 wine glass=11.4 cup=16.2 fork=11.5 knife=4.7 spoon=4.7 bowl=21.2 banana=13.3 apple=8.1 sandwich=24.4 orange=18.5 broccoli=13.4 carrot=8.9 hot dog=18.9 pizza=31.7 donut=22.9 cake=17.8 chair=11.3 couch=32.0 potted plant=10.9 bed=32.3 dining table=21.4 toilet=40.7 tv=38.6 laptop=40.6 mouse=26.3 remote=5.7 keyboard=27.8 cell phone=14.6 microwave=34.3 oven=23.6 toaster=5.9 sink=19.6 refrigerator=35.4 book=3.2 clock=25.8 vase=16.5 scissors=19.7 teddy bear=29.3 hair drier=0.0 toothbrush=5.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.9 [Epoch 98][Batch 99], Speed: 349.793 samples/sec, CrossEntropy=2.615, SmoothL1=1.132 [Epoch 98][Batch 199], Speed: 359.757 samples/sec, CrossEntropy=2.600, SmoothL1=1.125 [Epoch 98][Batch 299], Speed: 347.420 samples/sec, CrossEntropy=2.607, SmoothL1=1.140 [Epoch 98][Batch 399], Speed: 362.066 samples/sec, CrossEntropy=2.589, SmoothL1=1.132 [Epoch 98][Batch 499], Speed: 347.601 samples/sec, CrossEntropy=2.591, SmoothL1=1.140 [Epoch 98][Batch 599], Speed: 357.246 samples/sec, CrossEntropy=2.593, SmoothL1=1.139 [Epoch 98][Batch 699], Speed: 357.371 samples/sec, CrossEntropy=2.592, SmoothL1=1.134 [Epoch 98][Batch 799], Speed: 361.918 samples/sec, CrossEntropy=2.594, SmoothL1=1.137 [Epoch 98][Batch 899], Speed: 359.810 samples/sec, CrossEntropy=2.595, SmoothL1=1.136 [Epoch 98][Batch 999], Speed: 346.199 samples/sec, CrossEntropy=2.592, SmoothL1=1.135 [Epoch 98][Batch 1099], Speed: 362.170 samples/sec, CrossEntropy=2.591, SmoothL1=1.135 [Epoch 98][Batch 1199], Speed: 355.994 samples/sec, CrossEntropy=2.590, SmoothL1=1.135 [Epoch 98][Batch 1299], Speed: 361.613 samples/sec, CrossEntropy=2.595, SmoothL1=1.136 [Epoch 98][Batch 1399], Speed: 360.109 samples/sec, CrossEntropy=2.593, SmoothL1=1.134 [Epoch 98][Batch 1499], Speed: 350.070 samples/sec, CrossEntropy=2.594, SmoothL1=1.135 [Epoch 98][Batch 1599], Speed: 352.180 samples/sec, CrossEntropy=2.597, SmoothL1=1.138 [Epoch 98][Batch 1699], Speed: 348.565 samples/sec, CrossEntropy=2.598, SmoothL1=1.137 [Epoch 98][Batch 1799], Speed: 352.179 samples/sec, CrossEntropy=2.598, SmoothL1=1.138 [Epoch 98] Training cost: 335.206, CrossEntropy=2.598, SmoothL1=1.139 [Epoch 98] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.217 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.380 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.233 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.374 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.211 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.317 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.347 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.523 person=31.3 bicycle=14.8 car=18.1 motorcycle=25.1 airplane=42.7 bus=46.1 train=47.5 truck=19.3 boat=9.4 traffic light=6.2 fire hydrant=39.6 stop sign=40.7 parking meter=26.0 bench=11.9 bird=13.9 cat=48.5 dog=41.6 horse=35.4 sheep=28.3 cow=29.0 elephant=40.1 bear=51.1 zebra=43.5 giraffe=45.8 backpack=2.6 umbrella=20.4 handbag=2.5 tie=12.4 suitcase=15.7 frisbee=26.3 skis=9.3 snowboard=8.6 sports ball=15.7 kite=14.9 baseball bat=8.5 baseball glove=11.9 skateboard=23.5 surfboard=15.4 tennis racket=22.3 bottle=11.0 wine glass=10.4 cup=16.9 fork=10.3 knife=3.7 spoon=4.1 bowl=21.3 banana=12.8 apple=8.6 sandwich=26.3 orange=18.7 broccoli=13.9 carrot=9.7 hot dog=19.1 pizza=33.5 donut=24.0 cake=17.2 chair=11.7 couch=31.0 potted plant=10.8 bed=33.4 dining table=20.4 toilet=41.9 tv=36.9 laptop=38.3 mouse=26.5 remote=5.6 keyboard=28.5 cell phone=14.2 microwave=30.9 oven=23.5 toaster=2.4 sink=21.0 refrigerator=34.8 book=3.8 clock=26.9 vase=14.9 scissors=14.8 teddy bear=28.3 hair drier=0.0 toothbrush=4.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.7 [Epoch 99][Batch 99], Speed: 364.346 samples/sec, CrossEntropy=2.614, SmoothL1=1.109 [Epoch 99][Batch 199], Speed: 344.751 samples/sec, CrossEntropy=2.610, SmoothL1=1.123 [Epoch 99][Batch 299], Speed: 353.053 samples/sec, CrossEntropy=2.596, SmoothL1=1.118 [Epoch 99][Batch 399], Speed: 349.700 samples/sec, CrossEntropy=2.593, SmoothL1=1.125 [Epoch 99][Batch 499], Speed: 364.655 samples/sec, CrossEntropy=2.594, SmoothL1=1.134 [Epoch 99][Batch 599], Speed: 347.079 samples/sec, CrossEntropy=2.588, SmoothL1=1.131 [Epoch 99][Batch 699], Speed: 365.894 samples/sec, CrossEntropy=2.580, SmoothL1=1.127 [Epoch 99][Batch 799], Speed: 361.236 samples/sec, CrossEntropy=2.586, SmoothL1=1.129 [Epoch 99][Batch 899], Speed: 356.465 samples/sec, CrossEntropy=2.589, SmoothL1=1.131 [Epoch 99][Batch 999], Speed: 346.913 samples/sec, CrossEntropy=2.582, SmoothL1=1.129 [Epoch 99][Batch 1099], Speed: 354.840 samples/sec, CrossEntropy=2.586, SmoothL1=1.129 [Epoch 99][Batch 1199], Speed: 347.649 samples/sec, CrossEntropy=2.587, SmoothL1=1.127 [Epoch 99][Batch 1299], Speed: 358.156 samples/sec, CrossEntropy=2.590, SmoothL1=1.128 [Epoch 99][Batch 1399], Speed: 345.644 samples/sec, CrossEntropy=2.589, SmoothL1=1.127 [Epoch 99][Batch 1499], Speed: 352.738 samples/sec, CrossEntropy=2.589, SmoothL1=1.128 [Epoch 99][Batch 1599], Speed: 354.980 samples/sec, CrossEntropy=2.588, SmoothL1=1.129 [Epoch 99][Batch 1699], Speed: 353.317 samples/sec, CrossEntropy=2.588, SmoothL1=1.129 [Epoch 99][Batch 1799], Speed: 355.928 samples/sec, CrossEntropy=2.591, SmoothL1=1.131 [Epoch 99] Training cost: 334.759, CrossEntropy=2.593, SmoothL1=1.131 [Epoch 99] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.216 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.378 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.222 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.036 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.228 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.209 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.299 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.311 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.061 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.337 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.531 person=31.4 bicycle=14.5 car=17.5 motorcycle=23.0 airplane=40.3 bus=43.2 train=46.9 truck=19.2 boat=9.6 traffic light=5.9 fire hydrant=39.2 stop sign=39.3 parking meter=24.9 bench=11.9 bird=12.9 cat=49.9 dog=44.5 horse=36.3 sheep=28.3 cow=28.1 elephant=40.6 bear=53.8 zebra=43.9 giraffe=47.9 backpack=3.1 umbrella=21.1 handbag=2.5 tie=13.3 suitcase=15.6 frisbee=27.5 skis=8.5 snowboard=7.5 sports ball=16.2 kite=13.8 baseball bat=8.1 baseball glove=9.1 skateboard=21.7 surfboard=14.9 tennis racket=23.2 bottle=10.3 wine glass=10.1 cup=16.8 fork=11.3 knife=5.0 spoon=4.3 bowl=22.1 banana=12.7 apple=6.8 sandwich=24.7 orange=18.3 broccoli=12.5 carrot=8.0 hot dog=17.8 pizza=33.9 donut=21.3 cake=17.1 chair=11.6 couch=31.0 potted plant=10.7 bed=30.3 dining table=20.8 toilet=43.6 tv=39.1 laptop=38.9 mouse=30.9 remote=5.8 keyboard=29.6 cell phone=13.2 microwave=30.4 oven=24.3 toaster=3.0 sink=19.5 refrigerator=34.1 book=3.7 clock=27.4 vase=14.7 scissors=17.5 teddy bear=29.2 hair drier=0.0 toothbrush=4.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.6 [Epoch 100][Batch 99], Speed: 351.719 samples/sec, CrossEntropy=2.590, SmoothL1=1.124 [Epoch 100][Batch 199], Speed: 353.242 samples/sec, CrossEntropy=2.615, SmoothL1=1.143 [Epoch 100][Batch 299], Speed: 347.678 samples/sec, CrossEntropy=2.599, SmoothL1=1.135 [Epoch 100][Batch 399], Speed: 361.565 samples/sec, CrossEntropy=2.593, SmoothL1=1.126 [Epoch 100][Batch 499], Speed: 355.926 samples/sec, CrossEntropy=2.595, SmoothL1=1.127 [Epoch 100][Batch 599], Speed: 355.935 samples/sec, CrossEntropy=2.592, SmoothL1=1.128 [Epoch 100][Batch 699], Speed: 340.975 samples/sec, CrossEntropy=2.589, SmoothL1=1.127 [Epoch 100][Batch 799], Speed: 349.385 samples/sec, CrossEntropy=2.593, SmoothL1=1.131 [Epoch 100][Batch 899], Speed: 352.188 samples/sec, CrossEntropy=2.589, SmoothL1=1.131 [Epoch 100][Batch 999], Speed: 338.024 samples/sec, CrossEntropy=2.586, SmoothL1=1.131 [Epoch 100][Batch 1099], Speed: 345.674 samples/sec, CrossEntropy=2.586, SmoothL1=1.130 [Epoch 100][Batch 1199], Speed: 346.858 samples/sec, CrossEntropy=2.584, SmoothL1=1.131 [Epoch 100][Batch 1299], Speed: 356.313 samples/sec, CrossEntropy=2.586, SmoothL1=1.132 [Epoch 100][Batch 1399], Speed: 364.430 samples/sec, CrossEntropy=2.589, SmoothL1=1.134 [Epoch 100][Batch 1499], Speed: 349.665 samples/sec, CrossEntropy=2.590, SmoothL1=1.132 [Epoch 100][Batch 1599], Speed: 360.410 samples/sec, CrossEntropy=2.589, SmoothL1=1.132 [Epoch 100][Batch 1699], Speed: 350.039 samples/sec, CrossEntropy=2.591, SmoothL1=1.133 [Epoch 100][Batch 1799], Speed: 347.354 samples/sec, CrossEntropy=2.591, SmoothL1=1.132 [Epoch 100] Training cost: 334.567, CrossEntropy=2.591, SmoothL1=1.132 [Epoch 100] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.217 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.377 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.037 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.234 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.210 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.300 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.312 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.065 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.340 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.525 person=31.8 bicycle=14.6 car=17.6 motorcycle=22.8 airplane=41.1 bus=44.7 train=45.2 truck=18.4 boat=10.5 traffic light=6.3 fire hydrant=40.3 stop sign=41.2 parking meter=21.5 bench=10.9 bird=13.7 cat=49.2 dog=43.0 horse=36.9 sheep=27.4 cow=28.6 elephant=40.6 bear=48.3 zebra=44.5 giraffe=45.9 backpack=2.8 umbrella=20.7 handbag=3.0 tie=11.3 suitcase=14.0 frisbee=28.3 skis=9.8 snowboard=9.3 sports ball=16.8 kite=15.0 baseball bat=9.1 baseball glove=11.2 skateboard=23.1 surfboard=16.0 tennis racket=22.6 bottle=10.4 wine glass=11.7 cup=16.6 fork=11.2 knife=4.4 spoon=4.6 bowl=22.2 banana=13.0 apple=9.0 sandwich=25.9 orange=17.9 broccoli=14.1 carrot=8.9 hot dog=21.0 pizza=34.3 donut=23.1 cake=18.7 chair=11.1 couch=30.3 potted plant=10.9 bed=30.5 dining table=21.0 toilet=41.1 tv=39.2 laptop=40.2 mouse=28.1 remote=6.2 keyboard=29.9 cell phone=14.9 microwave=31.4 oven=24.0 toaster=7.1 sink=21.2 refrigerator=34.2 book=3.7 clock=27.4 vase=15.1 scissors=13.0 teddy bear=28.1 hair drier=0.0 toothbrush=5.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.7 [Epoch 101][Batch 99], Speed: 349.683 samples/sec, CrossEntropy=2.610, SmoothL1=1.147 [Epoch 101][Batch 199], Speed: 343.592 samples/sec, CrossEntropy=2.609, SmoothL1=1.128 [Epoch 101][Batch 299], Speed: 345.117 samples/sec, CrossEntropy=2.601, SmoothL1=1.127 [Epoch 101][Batch 399], Speed: 361.769 samples/sec, CrossEntropy=2.599, SmoothL1=1.121 [Epoch 101][Batch 499], Speed: 347.439 samples/sec, CrossEntropy=2.600, SmoothL1=1.119 [Epoch 101][Batch 599], Speed: 358.233 samples/sec, CrossEntropy=2.593, SmoothL1=1.126 [Epoch 101][Batch 699], Speed: 352.270 samples/sec, CrossEntropy=2.592, SmoothL1=1.124 [Epoch 101][Batch 799], Speed: 358.846 samples/sec, CrossEntropy=2.586, SmoothL1=1.120 [Epoch 101][Batch 899], Speed: 344.882 samples/sec, CrossEntropy=2.589, SmoothL1=1.124 [Epoch 101][Batch 999], Speed: 358.864 samples/sec, CrossEntropy=2.584, SmoothL1=1.124 [Epoch 101][Batch 1099], Speed: 358.166 samples/sec, CrossEntropy=2.583, SmoothL1=1.128 [Epoch 101][Batch 1199], Speed: 348.786 samples/sec, CrossEntropy=2.586, SmoothL1=1.127 [Epoch 101][Batch 1299], Speed: 349.564 samples/sec, CrossEntropy=2.587, SmoothL1=1.128 [Epoch 101][Batch 1399], Speed: 346.475 samples/sec, CrossEntropy=2.585, SmoothL1=1.128 [Epoch 101][Batch 1499], Speed: 348.597 samples/sec, CrossEntropy=2.585, SmoothL1=1.129 [Epoch 101][Batch 1599], Speed: 353.539 samples/sec, CrossEntropy=2.582, SmoothL1=1.128 [Epoch 101][Batch 1699], Speed: 361.501 samples/sec, CrossEntropy=2.583, SmoothL1=1.130 [Epoch 101][Batch 1799], Speed: 342.590 samples/sec, CrossEntropy=2.587, SmoothL1=1.130 [Epoch 101] Training cost: 335.495, CrossEntropy=2.586, SmoothL1=1.131 [Epoch 101] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.380 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.228 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.039 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.237 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.390 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.306 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.318 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.066 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.537 person=31.5 bicycle=14.8 car=18.0 motorcycle=25.2 airplane=44.0 bus=46.2 train=48.5 truck=18.6 boat=9.4 traffic light=7.0 fire hydrant=39.7 stop sign=43.2 parking meter=27.6 bench=12.1 bird=14.0 cat=49.5 dog=41.6 horse=37.0 sheep=25.9 cow=27.6 elephant=42.3 bear=48.9 zebra=45.8 giraffe=47.0 backpack=2.7 umbrella=21.9 handbag=2.6 tie=11.3 suitcase=14.6 frisbee=27.9 skis=9.4 snowboard=12.0 sports ball=16.7 kite=13.3 baseball bat=9.4 baseball glove=12.8 skateboard=23.6 surfboard=16.3 tennis racket=24.2 bottle=11.7 wine glass=11.9 cup=17.2 fork=10.6 knife=3.9 spoon=4.1 bowl=23.9 banana=11.8 apple=9.7 sandwich=26.4 orange=18.8 broccoli=12.3 carrot=8.9 hot dog=20.8 pizza=34.4 donut=23.7 cake=17.7 chair=11.5 couch=31.0 potted plant=10.9 bed=31.0 dining table=21.9 toilet=40.0 tv=39.9 laptop=40.5 mouse=28.1 remote=6.0 keyboard=28.7 cell phone=14.0 microwave=32.1 oven=23.6 toaster=2.0 sink=19.9 refrigerator=33.7 book=3.5 clock=27.4 vase=16.0 scissors=20.0 teddy bear=28.2 hair drier=0.0 toothbrush=5.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.1 [Epoch 102][Batch 99], Speed: 360.803 samples/sec, CrossEntropy=2.606, SmoothL1=1.123 [Epoch 102][Batch 199], Speed: 351.317 samples/sec, CrossEntropy=2.592, SmoothL1=1.126 [Epoch 102][Batch 299], Speed: 360.593 samples/sec, CrossEntropy=2.593, SmoothL1=1.132 [Epoch 102][Batch 399], Speed: 357.375 samples/sec, CrossEntropy=2.585, SmoothL1=1.136 [Epoch 102][Batch 499], Speed: 352.831 samples/sec, CrossEntropy=2.579, SmoothL1=1.135 [Epoch 102][Batch 599], Speed: 346.104 samples/sec, CrossEntropy=2.578, SmoothL1=1.134 [Epoch 102][Batch 699], Speed: 348.347 samples/sec, CrossEntropy=2.574, SmoothL1=1.127 [Epoch 102][Batch 799], Speed: 345.352 samples/sec, CrossEntropy=2.573, SmoothL1=1.125 [Epoch 102][Batch 899], Speed: 339.130 samples/sec, CrossEntropy=2.579, SmoothL1=1.128 [Epoch 102][Batch 999], Speed: 354.313 samples/sec, CrossEntropy=2.577, SmoothL1=1.129 [Epoch 102][Batch 1099], Speed: 353.488 samples/sec, CrossEntropy=2.580, SmoothL1=1.131 [Epoch 102][Batch 1199], Speed: 351.017 samples/sec, CrossEntropy=2.582, SmoothL1=1.131 [Epoch 102][Batch 1299], Speed: 354.622 samples/sec, CrossEntropy=2.583, SmoothL1=1.131 [Epoch 102][Batch 1399], Speed: 360.339 samples/sec, CrossEntropy=2.586, SmoothL1=1.131 [Epoch 102][Batch 1499], Speed: 347.930 samples/sec, CrossEntropy=2.588, SmoothL1=1.132 [Epoch 102][Batch 1599], Speed: 365.058 samples/sec, CrossEntropy=2.588, SmoothL1=1.133 [Epoch 102][Batch 1699], Speed: 352.171 samples/sec, CrossEntropy=2.589, SmoothL1=1.133 [Epoch 102][Batch 1799], Speed: 359.409 samples/sec, CrossEntropy=2.587, SmoothL1=1.133 [Epoch 102] Training cost: 334.496, CrossEntropy=2.586, SmoothL1=1.133 [Epoch 102] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.216 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.375 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.226 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.038 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.226 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.387 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.209 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.300 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.311 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.064 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.341 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.528 person=32.4 bicycle=14.3 car=17.8 motorcycle=25.5 airplane=43.3 bus=44.8 train=48.6 truck=18.4 boat=9.5 traffic light=6.5 fire hydrant=38.0 stop sign=40.4 parking meter=27.9 bench=11.6 bird=14.5 cat=49.7 dog=43.4 horse=34.6 sheep=27.7 cow=28.4 elephant=42.0 bear=42.7 zebra=45.1 giraffe=45.7 backpack=2.9 umbrella=19.9 handbag=3.1 tie=11.7 suitcase=17.0 frisbee=27.1 skis=9.9 snowboard=7.1 sports ball=15.4 kite=12.3 baseball bat=9.4 baseball glove=11.1 skateboard=23.1 surfboard=16.1 tennis racket=23.7 bottle=10.3 wine glass=11.0 cup=16.8 fork=11.1 knife=4.3 spoon=4.8 bowl=22.5 banana=13.1 apple=8.5 sandwich=26.4 orange=17.9 broccoli=13.3 carrot=9.0 hot dog=21.2 pizza=32.9 donut=22.8 cake=18.7 chair=11.3 couch=30.6 potted plant=11.4 bed=32.3 dining table=20.8 toilet=43.4 tv=39.9 laptop=40.2 mouse=25.1 remote=6.2 keyboard=29.3 cell phone=13.9 microwave=32.8 oven=23.8 toaster=0.0 sink=19.5 refrigerator=32.2 book=3.6 clock=26.0 vase=15.4 scissors=12.0 teddy bear=28.0 hair drier=0.0 toothbrush=4.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.6 [Epoch 103][Batch 99], Speed: 363.030 samples/sec, CrossEntropy=2.622, SmoothL1=1.138 [Epoch 103][Batch 199], Speed: 349.432 samples/sec, CrossEntropy=2.598, SmoothL1=1.121 [Epoch 103][Batch 299], Speed: 355.859 samples/sec, CrossEntropy=2.590, SmoothL1=1.132 [Epoch 103][Batch 399], Speed: 352.707 samples/sec, CrossEntropy=2.574, SmoothL1=1.130 [Epoch 103][Batch 499], Speed: 356.727 samples/sec, CrossEntropy=2.571, SmoothL1=1.130 [Epoch 103][Batch 599], Speed: 354.732 samples/sec, CrossEntropy=2.568, SmoothL1=1.130 [Epoch 103][Batch 699], Speed: 358.616 samples/sec, CrossEntropy=2.563, SmoothL1=1.126 [Epoch 103][Batch 799], Speed: 354.124 samples/sec, CrossEntropy=2.568, SmoothL1=1.124 [Epoch 103][Batch 899], Speed: 354.594 samples/sec, CrossEntropy=2.569, SmoothL1=1.124 [Epoch 103][Batch 999], Speed: 351.135 samples/sec, CrossEntropy=2.567, SmoothL1=1.124 [Epoch 103][Batch 1099], Speed: 350.261 samples/sec, CrossEntropy=2.566, SmoothL1=1.121 [Epoch 103][Batch 1199], Speed: 355.565 samples/sec, CrossEntropy=2.568, SmoothL1=1.121 [Epoch 103][Batch 1299], Speed: 351.205 samples/sec, CrossEntropy=2.570, SmoothL1=1.124 [Epoch 103][Batch 1399], Speed: 352.928 samples/sec, CrossEntropy=2.573, SmoothL1=1.125 [Epoch 103][Batch 1499], Speed: 355.754 samples/sec, CrossEntropy=2.572, SmoothL1=1.123 [Epoch 103][Batch 1599], Speed: 358.887 samples/sec, CrossEntropy=2.569, SmoothL1=1.122 [Epoch 103][Batch 1699], Speed: 353.937 samples/sec, CrossEntropy=2.572, SmoothL1=1.123 [Epoch 103][Batch 1799], Speed: 357.760 samples/sec, CrossEntropy=2.575, SmoothL1=1.124 [Epoch 103] Training cost: 335.264, CrossEntropy=2.578, SmoothL1=1.124 [Epoch 103] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.380 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.037 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.233 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.385 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.211 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.303 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.314 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.062 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.343 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.538 person=31.6 bicycle=14.9 car=18.1 motorcycle=24.1 airplane=41.5 bus=45.6 train=47.6 truck=18.0 boat=9.3 traffic light=6.8 fire hydrant=40.4 stop sign=44.9 parking meter=22.7 bench=11.8 bird=13.5 cat=48.6 dog=38.8 horse=35.0 sheep=29.7 cow=27.4 elephant=42.6 bear=50.2 zebra=44.5 giraffe=45.7 backpack=2.6 umbrella=20.5 handbag=2.5 tie=12.2 suitcase=15.7 frisbee=24.7 skis=9.3 snowboard=10.2 sports ball=15.7 kite=13.2 baseball bat=9.1 baseball glove=11.1 skateboard=24.0 surfboard=15.4 tennis racket=22.6 bottle=10.7 wine glass=11.6 cup=16.8 fork=11.9 knife=4.5 spoon=3.5 bowl=22.2 banana=12.1 apple=9.6 sandwich=26.0 orange=15.7 broccoli=13.7 carrot=9.0 hot dog=19.3 pizza=33.4 donut=23.7 cake=16.9 chair=11.3 couch=31.1 potted plant=10.9 bed=35.7 dining table=20.4 toilet=40.9 tv=40.1 laptop=40.9 mouse=27.2 remote=6.4 keyboard=29.8 cell phone=14.0 microwave=33.2 oven=24.2 toaster=7.1 sink=18.3 refrigerator=33.4 book=3.8 clock=28.2 vase=15.8 scissors=16.2 teddy bear=27.9 hair drier=0.0 toothbrush=6.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.8 [Epoch 104][Batch 99], Speed: 365.221 samples/sec, CrossEntropy=2.610, SmoothL1=1.106 [Epoch 104][Batch 199], Speed: 355.571 samples/sec, CrossEntropy=2.595, SmoothL1=1.112 [Epoch 104][Batch 299], Speed: 359.449 samples/sec, CrossEntropy=2.578, SmoothL1=1.116 [Epoch 104][Batch 399], Speed: 361.258 samples/sec, CrossEntropy=2.576, SmoothL1=1.111 [Epoch 104][Batch 499], Speed: 361.392 samples/sec, CrossEntropy=2.578, SmoothL1=1.109 [Epoch 104][Batch 599], Speed: 349.685 samples/sec, CrossEntropy=2.572, SmoothL1=1.110 [Epoch 104][Batch 699], Speed: 350.510 samples/sec, CrossEntropy=2.569, SmoothL1=1.109 [Epoch 104][Batch 799], Speed: 357.528 samples/sec, CrossEntropy=2.566, SmoothL1=1.110 [Epoch 104][Batch 899], Speed: 357.561 samples/sec, CrossEntropy=2.562, SmoothL1=1.113 [Epoch 104][Batch 999], Speed: 355.444 samples/sec, CrossEntropy=2.564, SmoothL1=1.113 [Epoch 104][Batch 1099], Speed: 348.182 samples/sec, CrossEntropy=2.568, SmoothL1=1.115 [Epoch 104][Batch 1199], Speed: 348.765 samples/sec, CrossEntropy=2.572, SmoothL1=1.116 [Epoch 104][Batch 1299], Speed: 350.082 samples/sec, CrossEntropy=2.573, SmoothL1=1.116 [Epoch 104][Batch 1399], Speed: 357.493 samples/sec, CrossEntropy=2.573, SmoothL1=1.115 [Epoch 104][Batch 1499], Speed: 365.066 samples/sec, CrossEntropy=2.576, SmoothL1=1.116 [Epoch 104][Batch 1599], Speed: 362.861 samples/sec, CrossEntropy=2.577, SmoothL1=1.119 [Epoch 104][Batch 1699], Speed: 356.702 samples/sec, CrossEntropy=2.580, SmoothL1=1.122 [Epoch 104][Batch 1799], Speed: 348.999 samples/sec, CrossEntropy=2.579, SmoothL1=1.121 [Epoch 104] Training cost: 334.805, CrossEntropy=2.579, SmoothL1=1.121 [Epoch 104] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.217 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.378 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.038 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.229 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.383 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.212 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.303 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.316 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.065 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.342 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.526 person=31.3 bicycle=14.8 car=17.9 motorcycle=24.8 airplane=42.7 bus=46.3 train=48.2 truck=18.7 boat=9.7 traffic light=7.0 fire hydrant=38.7 stop sign=40.6 parking meter=27.2 bench=11.2 bird=13.0 cat=48.2 dog=43.4 horse=36.9 sheep=27.6 cow=28.8 elephant=42.8 bear=48.1 zebra=47.5 giraffe=47.3 backpack=2.2 umbrella=19.8 handbag=2.6 tie=11.7 suitcase=17.5 frisbee=26.0 skis=9.2 snowboard=9.5 sports ball=17.1 kite=14.9 baseball bat=9.3 baseball glove=11.2 skateboard=21.0 surfboard=16.0 tennis racket=22.6 bottle=9.2 wine glass=10.3 cup=16.7 fork=10.8 knife=3.6 spoon=4.3 bowl=24.0 banana=12.5 apple=7.2 sandwich=26.2 orange=18.7 broccoli=13.7 carrot=9.1 hot dog=20.4 pizza=31.3 donut=22.5 cake=19.7 chair=11.7 couch=29.2 potted plant=12.2 bed=31.3 dining table=20.9 toilet=40.8 tv=38.0 laptop=39.0 mouse=28.8 remote=6.4 keyboard=25.5 cell phone=13.9 microwave=31.9 oven=23.7 toaster=1.0 sink=20.4 refrigerator=35.1 book=3.3 clock=26.3 vase=14.6 scissors=15.7 teddy bear=28.4 hair drier=0.0 toothbrush=6.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.7 [Epoch 105][Batch 99], Speed: 355.182 samples/sec, CrossEntropy=2.584, SmoothL1=1.146 [Epoch 105][Batch 199], Speed: 353.835 samples/sec, CrossEntropy=2.596, SmoothL1=1.157 [Epoch 105][Batch 299], Speed: 348.686 samples/sec, CrossEntropy=2.577, SmoothL1=1.134 [Epoch 105][Batch 399], Speed: 356.624 samples/sec, CrossEntropy=2.573, SmoothL1=1.129 [Epoch 105][Batch 499], Speed: 348.523 samples/sec, CrossEntropy=2.574, SmoothL1=1.129 [Epoch 105][Batch 599], Speed: 355.694 samples/sec, CrossEntropy=2.567, SmoothL1=1.129 [Epoch 105][Batch 699], Speed: 358.789 samples/sec, CrossEntropy=2.572, SmoothL1=1.131 [Epoch 105][Batch 799], Speed: 364.582 samples/sec, CrossEntropy=2.573, SmoothL1=1.134 [Epoch 105][Batch 899], Speed: 345.084 samples/sec, CrossEntropy=2.571, SmoothL1=1.127 [Epoch 105][Batch 999], Speed: 357.321 samples/sec, CrossEntropy=2.569, SmoothL1=1.123 [Epoch 105][Batch 1099], Speed: 356.746 samples/sec, CrossEntropy=2.567, SmoothL1=1.125 [Epoch 105][Batch 1199], Speed: 344.244 samples/sec, CrossEntropy=2.565, SmoothL1=1.126 [Epoch 105][Batch 1299], Speed: 354.454 samples/sec, CrossEntropy=2.568, SmoothL1=1.124 [Epoch 105][Batch 1399], Speed: 347.298 samples/sec, CrossEntropy=2.571, SmoothL1=1.127 [Epoch 105][Batch 1499], Speed: 351.494 samples/sec, CrossEntropy=2.571, SmoothL1=1.128 [Epoch 105][Batch 1599], Speed: 351.697 samples/sec, CrossEntropy=2.574, SmoothL1=1.128 [Epoch 105][Batch 1699], Speed: 346.148 samples/sec, CrossEntropy=2.573, SmoothL1=1.126 [Epoch 105][Batch 1799], Speed: 357.693 samples/sec, CrossEntropy=2.572, SmoothL1=1.126 [Epoch 105] Training cost: 335.041, CrossEntropy=2.572, SmoothL1=1.127 [Epoch 105] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.377 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.229 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.388 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.212 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.302 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.315 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.340 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.537 person=31.6 bicycle=15.0 car=18.0 motorcycle=25.0 airplane=38.8 bus=46.0 train=49.0 truck=17.9 boat=10.3 traffic light=6.0 fire hydrant=39.8 stop sign=43.8 parking meter=26.1 bench=11.8 bird=13.4 cat=49.2 dog=43.7 horse=35.8 sheep=28.5 cow=28.0 elephant=41.4 bear=49.3 zebra=43.7 giraffe=47.5 backpack=2.9 umbrella=19.0 handbag=2.5 tie=12.3 suitcase=16.1 frisbee=26.3 skis=10.4 snowboard=8.4 sports ball=16.5 kite=14.2 baseball bat=8.5 baseball glove=12.2 skateboard=22.0 surfboard=16.3 tennis racket=22.7 bottle=10.5 wine glass=11.3 cup=16.1 fork=10.4 knife=4.4 spoon=3.4 bowl=22.1 banana=12.0 apple=7.9 sandwich=25.5 orange=18.4 broccoli=13.5 carrot=9.5 hot dog=20.0 pizza=32.6 donut=23.1 cake=18.3 chair=10.6 couch=30.5 potted plant=11.1 bed=32.4 dining table=20.4 toilet=42.0 tv=39.0 laptop=40.3 mouse=28.2 remote=6.1 keyboard=30.9 cell phone=14.4 microwave=31.4 oven=25.3 toaster=1.2 sink=19.5 refrigerator=32.3 book=2.9 clock=29.0 vase=15.9 scissors=15.1 teddy bear=29.7 hair drier=0.0 toothbrush=3.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.8 [Epoch 106][Batch 99], Speed: 341.141 samples/sec, CrossEntropy=2.580, SmoothL1=1.121 [Epoch 106][Batch 199], Speed: 351.047 samples/sec, CrossEntropy=2.582, SmoothL1=1.139 [Epoch 106][Batch 299], Speed: 345.186 samples/sec, CrossEntropy=2.579, SmoothL1=1.132 [Epoch 106][Batch 399], Speed: 356.523 samples/sec, CrossEntropy=2.578, SmoothL1=1.124 [Epoch 106][Batch 499], Speed: 352.275 samples/sec, CrossEntropy=2.575, SmoothL1=1.128 [Epoch 106][Batch 599], Speed: 349.042 samples/sec, CrossEntropy=2.577, SmoothL1=1.130 [Epoch 106][Batch 699], Speed: 345.365 samples/sec, CrossEntropy=2.575, SmoothL1=1.127 [Epoch 106][Batch 799], Speed: 357.501 samples/sec, CrossEntropy=2.578, SmoothL1=1.129 [Epoch 106][Batch 899], Speed: 352.364 samples/sec, CrossEntropy=2.576, SmoothL1=1.130 [Epoch 106][Batch 999], Speed: 348.010 samples/sec, CrossEntropy=2.576, SmoothL1=1.130 [Epoch 106][Batch 1099], Speed: 357.340 samples/sec, CrossEntropy=2.573, SmoothL1=1.128 [Epoch 106][Batch 1199], Speed: 344.612 samples/sec, CrossEntropy=2.573, SmoothL1=1.127 [Epoch 106][Batch 1299], Speed: 364.225 samples/sec, CrossEntropy=2.576, SmoothL1=1.130 [Epoch 106][Batch 1399], Speed: 355.622 samples/sec, CrossEntropy=2.574, SmoothL1=1.128 [Epoch 106][Batch 1499], Speed: 354.612 samples/sec, CrossEntropy=2.574, SmoothL1=1.129 [Epoch 106][Batch 1599], Speed: 362.513 samples/sec, CrossEntropy=2.574, SmoothL1=1.130 [Epoch 106][Batch 1699], Speed: 364.078 samples/sec, CrossEntropy=2.574, SmoothL1=1.133 [Epoch 106][Batch 1799], Speed: 354.310 samples/sec, CrossEntropy=2.576, SmoothL1=1.131 [Epoch 106] Training cost: 334.884, CrossEntropy=2.576, SmoothL1=1.131 [Epoch 106] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.378 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.041 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.383 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.213 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.317 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.069 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.342 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.529 person=31.6 bicycle=15.3 car=17.6 motorcycle=24.3 airplane=43.0 bus=46.7 train=49.2 truck=18.4 boat=9.0 traffic light=7.1 fire hydrant=40.9 stop sign=43.6 parking meter=26.2 bench=11.6 bird=13.6 cat=49.7 dog=45.1 horse=35.8 sheep=26.5 cow=26.8 elephant=38.5 bear=46.9 zebra=46.6 giraffe=47.4 backpack=2.5 umbrella=19.5 handbag=2.6 tie=11.4 suitcase=12.7 frisbee=23.8 skis=9.8 snowboard=7.5 sports ball=15.2 kite=14.3 baseball bat=9.0 baseball glove=11.7 skateboard=21.9 surfboard=15.8 tennis racket=23.4 bottle=10.7 wine glass=11.2 cup=16.8 fork=11.3 knife=4.2 spoon=5.0 bowl=22.6 banana=11.8 apple=9.1 sandwich=25.9 orange=14.0 broccoli=13.7 carrot=9.7 hot dog=19.1 pizza=35.1 donut=23.8 cake=17.1 chair=11.3 couch=29.7 potted plant=10.4 bed=34.1 dining table=20.8 toilet=44.2 tv=40.1 laptop=39.6 mouse=29.0 remote=5.6 keyboard=29.4 cell phone=14.5 microwave=31.1 oven=24.6 toaster=3.6 sink=20.9 refrigerator=35.0 book=3.2 clock=27.3 vase=15.5 scissors=15.5 teddy bear=29.6 hair drier=0.0 toothbrush=5.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.8 [Epoch 107][Batch 99], Speed: 360.099 samples/sec, CrossEntropy=2.594, SmoothL1=1.158 [Epoch 107][Batch 199], Speed: 360.738 samples/sec, CrossEntropy=2.609, SmoothL1=1.166 [Epoch 107][Batch 299], Speed: 360.452 samples/sec, CrossEntropy=2.586, SmoothL1=1.154 [Epoch 107][Batch 399], Speed: 351.283 samples/sec, CrossEntropy=2.587, SmoothL1=1.153 [Epoch 107][Batch 499], Speed: 345.799 samples/sec, CrossEntropy=2.581, SmoothL1=1.143 [Epoch 107][Batch 599], Speed: 347.498 samples/sec, CrossEntropy=2.581, SmoothL1=1.137 [Epoch 107][Batch 699], Speed: 361.748 samples/sec, CrossEntropy=2.586, SmoothL1=1.133 [Epoch 107][Batch 799], Speed: 357.296 samples/sec, CrossEntropy=2.585, SmoothL1=1.131 [Epoch 107][Batch 899], Speed: 359.125 samples/sec, CrossEntropy=2.580, SmoothL1=1.130 [Epoch 107][Batch 999], Speed: 356.116 samples/sec, CrossEntropy=2.580, SmoothL1=1.131 [Epoch 107][Batch 1099], Speed: 342.845 samples/sec, CrossEntropy=2.579, SmoothL1=1.133 [Epoch 107][Batch 1199], Speed: 361.449 samples/sec, CrossEntropy=2.579, SmoothL1=1.134 [Epoch 107][Batch 1299], Speed: 363.935 samples/sec, CrossEntropy=2.579, SmoothL1=1.132 [Epoch 107][Batch 1399], Speed: 350.942 samples/sec, CrossEntropy=2.576, SmoothL1=1.130 [Epoch 107][Batch 1499], Speed: 356.646 samples/sec, CrossEntropy=2.575, SmoothL1=1.128 [Epoch 107][Batch 1599], Speed: 349.223 samples/sec, CrossEntropy=2.578, SmoothL1=1.127 [Epoch 107][Batch 1699], Speed: 357.493 samples/sec, CrossEntropy=2.579, SmoothL1=1.126 [Epoch 107][Batch 1799], Speed: 351.616 samples/sec, CrossEntropy=2.578, SmoothL1=1.125 [Epoch 107] Training cost: 334.305, CrossEntropy=2.579, SmoothL1=1.124 [Epoch 107] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.380 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.233 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.392 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.213 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.303 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.315 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.064 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.343 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.541 person=31.4 bicycle=15.4 car=17.6 motorcycle=25.5 airplane=39.8 bus=46.1 train=47.6 truck=18.5 boat=10.0 traffic light=7.2 fire hydrant=41.2 stop sign=42.2 parking meter=27.4 bench=11.5 bird=12.8 cat=48.5 dog=39.8 horse=34.6 sheep=27.6 cow=27.6 elephant=37.3 bear=48.7 zebra=46.7 giraffe=47.8 backpack=2.7 umbrella=20.0 handbag=2.7 tie=12.5 suitcase=16.0 frisbee=26.6 skis=9.1 snowboard=9.8 sports ball=15.6 kite=13.4 baseball bat=9.6 baseball glove=11.3 skateboard=23.2 surfboard=15.6 tennis racket=23.5 bottle=10.9 wine glass=11.4 cup=16.6 fork=11.6 knife=4.4 spoon=4.5 bowl=22.6 banana=12.4 apple=9.6 sandwich=26.5 orange=18.5 broccoli=13.0 carrot=8.3 hot dog=18.9 pizza=32.6 donut=23.2 cake=17.3 chair=11.5 couch=28.1 potted plant=12.2 bed=32.9 dining table=20.7 toilet=42.0 tv=39.0 laptop=39.4 mouse=27.0 remote=5.7 keyboard=31.1 cell phone=15.2 microwave=32.4 oven=24.6 toaster=7.1 sink=21.1 refrigerator=32.2 book=3.4 clock=27.5 vase=16.0 scissors=17.0 teddy bear=30.0 hair drier=0.0 toothbrush=6.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.9 [Epoch 108][Batch 99], Speed: 350.846 samples/sec, CrossEntropy=2.588, SmoothL1=1.139 [Epoch 108][Batch 199], Speed: 346.367 samples/sec, CrossEntropy=2.569, SmoothL1=1.123 [Epoch 108][Batch 299], Speed: 354.206 samples/sec, CrossEntropy=2.561, SmoothL1=1.117 [Epoch 108][Batch 399], Speed: 350.567 samples/sec, CrossEntropy=2.549, SmoothL1=1.113 [Epoch 108][Batch 499], Speed: 356.320 samples/sec, CrossEntropy=2.554, SmoothL1=1.115 [Epoch 108][Batch 599], Speed: 342.418 samples/sec, CrossEntropy=2.557, SmoothL1=1.111 [Epoch 108][Batch 699], Speed: 359.019 samples/sec, CrossEntropy=2.561, SmoothL1=1.110 [Epoch 108][Batch 799], Speed: 359.270 samples/sec, CrossEntropy=2.562, SmoothL1=1.111 [Epoch 108][Batch 899], Speed: 356.097 samples/sec, CrossEntropy=2.563, SmoothL1=1.112 [Epoch 108][Batch 999], Speed: 346.739 samples/sec, CrossEntropy=2.565, SmoothL1=1.114 [Epoch 108][Batch 1099], Speed: 351.157 samples/sec, CrossEntropy=2.563, SmoothL1=1.112 [Epoch 108][Batch 1199], Speed: 346.208 samples/sec, CrossEntropy=2.561, SmoothL1=1.109 [Epoch 108][Batch 1299], Speed: 355.330 samples/sec, CrossEntropy=2.560, SmoothL1=1.110 [Epoch 108][Batch 1399], Speed: 358.070 samples/sec, CrossEntropy=2.562, SmoothL1=1.109 [Epoch 108][Batch 1499], Speed: 358.026 samples/sec, CrossEntropy=2.563, SmoothL1=1.111 [Epoch 108][Batch 1599], Speed: 366.382 samples/sec, CrossEntropy=2.561, SmoothL1=1.110 [Epoch 108][Batch 1699], Speed: 353.436 samples/sec, CrossEntropy=2.559, SmoothL1=1.110 [Epoch 108][Batch 1799], Speed: 361.311 samples/sec, CrossEntropy=2.562, SmoothL1=1.111 [Epoch 108] Training cost: 335.570, CrossEntropy=2.560, SmoothL1=1.111 [Epoch 108] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.380 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.226 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.041 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.229 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.384 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.211 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.303 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.317 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.068 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.339 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.536 person=32.3 bicycle=14.5 car=17.4 motorcycle=24.5 airplane=42.4 bus=45.4 train=48.0 truck=18.5 boat=9.7 traffic light=6.7 fire hydrant=38.2 stop sign=41.3 parking meter=26.1 bench=11.1 bird=15.1 cat=51.5 dog=41.6 horse=36.3 sheep=29.3 cow=27.9 elephant=42.7 bear=50.4 zebra=46.2 giraffe=45.9 backpack=2.7 umbrella=18.8 handbag=2.9 tie=11.4 suitcase=15.9 frisbee=25.0 skis=9.9 snowboard=8.8 sports ball=14.7 kite=14.7 baseball bat=8.9 baseball glove=9.5 skateboard=21.7 surfboard=16.1 tennis racket=23.1 bottle=10.7 wine glass=11.0 cup=16.1 fork=11.9 knife=4.1 spoon=3.3 bowl=22.4 banana=11.8 apple=9.3 sandwich=27.7 orange=17.5 broccoli=12.9 carrot=8.3 hot dog=19.9 pizza=34.9 donut=23.4 cake=17.9 chair=11.4 couch=31.3 potted plant=11.4 bed=33.4 dining table=20.2 toilet=42.1 tv=39.6 laptop=39.9 mouse=29.9 remote=6.8 keyboard=31.5 cell phone=13.8 microwave=31.5 oven=23.4 toaster=3.3 sink=20.8 refrigerator=35.3 book=3.8 clock=28.1 vase=14.8 scissors=16.5 teddy bear=29.7 hair drier=0.0 toothbrush=5.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.9 [Epoch 109][Batch 99], Speed: 349.087 samples/sec, CrossEntropy=2.571, SmoothL1=1.139 [Epoch 109][Batch 199], Speed: 345.208 samples/sec, CrossEntropy=2.566, SmoothL1=1.132 [Epoch 109][Batch 299], Speed: 345.054 samples/sec, CrossEntropy=2.550, SmoothL1=1.119 [Epoch 109][Batch 399], Speed: 349.636 samples/sec, CrossEntropy=2.569, SmoothL1=1.121 [Epoch 109][Batch 499], Speed: 358.593 samples/sec, CrossEntropy=2.564, SmoothL1=1.119 [Epoch 109][Batch 599], Speed: 348.174 samples/sec, CrossEntropy=2.569, SmoothL1=1.120 [Epoch 109][Batch 699], Speed: 351.131 samples/sec, CrossEntropy=2.573, SmoothL1=1.121 [Epoch 109][Batch 799], Speed: 347.878 samples/sec, CrossEntropy=2.568, SmoothL1=1.119 [Epoch 109][Batch 899], Speed: 353.016 samples/sec, CrossEntropy=2.569, SmoothL1=1.119 [Epoch 109][Batch 999], Speed: 359.329 samples/sec, CrossEntropy=2.567, SmoothL1=1.117 [Epoch 109][Batch 1099], Speed: 359.676 samples/sec, CrossEntropy=2.568, SmoothL1=1.117 [Epoch 109][Batch 1199], Speed: 350.016 samples/sec, CrossEntropy=2.568, SmoothL1=1.119 [Epoch 109][Batch 1299], Speed: 361.226 samples/sec, CrossEntropy=2.566, SmoothL1=1.117 [Epoch 109][Batch 1399], Speed: 350.986 samples/sec, CrossEntropy=2.566, SmoothL1=1.117 [Epoch 109][Batch 1499], Speed: 348.940 samples/sec, CrossEntropy=2.568, SmoothL1=1.120 [Epoch 109][Batch 1599], Speed: 353.524 samples/sec, CrossEntropy=2.568, SmoothL1=1.119 [Epoch 109][Batch 1699], Speed: 346.237 samples/sec, CrossEntropy=2.566, SmoothL1=1.116 [Epoch 109][Batch 1799], Speed: 355.173 samples/sec, CrossEntropy=2.567, SmoothL1=1.118 [Epoch 109] Training cost: 334.706, CrossEntropy=2.567, SmoothL1=1.119 [Epoch 109] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.382 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.226 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.039 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.231 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.386 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.210 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.302 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.314 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.064 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.526 person=32.2 bicycle=13.8 car=18.0 motorcycle=24.6 airplane=42.8 bus=43.5 train=48.0 truck=17.9 boat=10.0 traffic light=7.2 fire hydrant=39.0 stop sign=40.7 parking meter=27.5 bench=11.2 bird=14.4 cat=49.0 dog=42.4 horse=36.6 sheep=29.0 cow=28.3 elephant=43.0 bear=48.3 zebra=43.7 giraffe=44.8 backpack=3.6 umbrella=20.1 handbag=3.0 tie=12.4 suitcase=15.3 frisbee=27.3 skis=9.4 snowboard=9.8 sports ball=15.7 kite=14.4 baseball bat=9.1 baseball glove=11.5 skateboard=22.4 surfboard=15.4 tennis racket=24.7 bottle=10.3 wine glass=11.4 cup=16.0 fork=11.7 knife=4.3 spoon=4.0 bowl=22.3 banana=12.3 apple=6.0 sandwich=26.5 orange=18.8 broccoli=14.6 carrot=9.1 hot dog=19.5 pizza=35.8 donut=22.7 cake=19.6 chair=11.1 couch=30.4 potted plant=11.4 bed=35.0 dining table=19.2 toilet=43.1 tv=37.3 laptop=38.9 mouse=26.3 remote=5.3 keyboard=29.2 cell phone=14.9 microwave=30.2 oven=24.7 toaster=3.6 sink=19.2 refrigerator=35.1 book=3.5 clock=27.5 vase=14.2 scissors=13.0 teddy bear=30.8 hair drier=0.0 toothbrush=5.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.8 [Epoch 110][Batch 99], Speed: 349.805 samples/sec, CrossEntropy=2.566, SmoothL1=1.127 [Epoch 110][Batch 199], Speed: 364.827 samples/sec, CrossEntropy=2.555, SmoothL1=1.105 [Epoch 110][Batch 299], Speed: 349.538 samples/sec, CrossEntropy=2.548, SmoothL1=1.105 [Epoch 110][Batch 399], Speed: 359.844 samples/sec, CrossEntropy=2.551, SmoothL1=1.103 [Epoch 110][Batch 499], Speed: 347.152 samples/sec, CrossEntropy=2.552, SmoothL1=1.106 [Epoch 110][Batch 599], Speed: 354.364 samples/sec, CrossEntropy=2.548, SmoothL1=1.106 [Epoch 110][Batch 699], Speed: 348.713 samples/sec, CrossEntropy=2.545, SmoothL1=1.100 [Epoch 110][Batch 799], Speed: 350.603 samples/sec, CrossEntropy=2.545, SmoothL1=1.101 [Epoch 110][Batch 899], Speed: 351.962 samples/sec, CrossEntropy=2.548, SmoothL1=1.102 [Epoch 110][Batch 999], Speed: 350.638 samples/sec, CrossEntropy=2.544, SmoothL1=1.099 [Epoch 110][Batch 1099], Speed: 356.031 samples/sec, CrossEntropy=2.545, SmoothL1=1.102 [Epoch 110][Batch 1199], Speed: 352.704 samples/sec, CrossEntropy=2.545, SmoothL1=1.101 [Epoch 110][Batch 1299], Speed: 353.879 samples/sec, CrossEntropy=2.547, SmoothL1=1.103 [Epoch 110][Batch 1399], Speed: 345.682 samples/sec, CrossEntropy=2.548, SmoothL1=1.103 [Epoch 110][Batch 1499], Speed: 347.174 samples/sec, CrossEntropy=2.549, SmoothL1=1.103 [Epoch 110][Batch 1599], Speed: 360.229 samples/sec, CrossEntropy=2.550, SmoothL1=1.105 [Epoch 110][Batch 1699], Speed: 351.047 samples/sec, CrossEntropy=2.550, SmoothL1=1.107 [Epoch 110][Batch 1799], Speed: 349.525 samples/sec, CrossEntropy=2.551, SmoothL1=1.109 [Epoch 110] Training cost: 335.262, CrossEntropy=2.552, SmoothL1=1.108 [Epoch 110] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.222 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.382 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.236 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.390 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.213 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.308 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.321 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.354 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.534 person=32.3 bicycle=15.7 car=18.1 motorcycle=25.3 airplane=44.2 bus=44.1 train=47.1 truck=18.8 boat=9.5 traffic light=7.2 fire hydrant=38.5 stop sign=44.2 parking meter=28.6 bench=11.0 bird=13.2 cat=48.9 dog=44.4 horse=35.4 sheep=29.8 cow=27.8 elephant=44.7 bear=55.0 zebra=46.7 giraffe=47.2 backpack=2.5 umbrella=19.6 handbag=2.9 tie=12.5 suitcase=15.3 frisbee=27.7 skis=9.0 snowboard=8.6 sports ball=14.6 kite=14.3 baseball bat=9.4 baseball glove=8.9 skateboard=25.2 surfboard=16.4 tennis racket=23.8 bottle=11.0 wine glass=10.4 cup=17.5 fork=12.1 knife=4.3 spoon=3.4 bowl=22.8 banana=12.1 apple=8.3 sandwich=26.2 orange=20.2 broccoli=12.1 carrot=8.5 hot dog=18.0 pizza=34.7 donut=23.0 cake=18.3 chair=11.5 couch=31.0 potted plant=11.2 bed=31.4 dining table=20.9 toilet=40.8 tv=40.0 laptop=42.8 mouse=27.4 remote=6.0 keyboard=29.4 cell phone=15.2 microwave=32.1 oven=25.2 toaster=2.0 sink=19.2 refrigerator=34.2 book=3.5 clock=28.3 vase=15.6 scissors=19.8 teddy bear=28.7 hair drier=0.0 toothbrush=6.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.2 [Epoch 111][Batch 99], Speed: 347.358 samples/sec, CrossEntropy=2.537, SmoothL1=1.140 [Epoch 111][Batch 199], Speed: 359.078 samples/sec, CrossEntropy=2.549, SmoothL1=1.129 [Epoch 111][Batch 299], Speed: 355.351 samples/sec, CrossEntropy=2.550, SmoothL1=1.130 [Epoch 111][Batch 399], Speed: 347.903 samples/sec, CrossEntropy=2.548, SmoothL1=1.123 [Epoch 111][Batch 499], Speed: 352.578 samples/sec, CrossEntropy=2.547, SmoothL1=1.121 [Epoch 111][Batch 599], Speed: 355.445 samples/sec, CrossEntropy=2.545, SmoothL1=1.121 [Epoch 111][Batch 699], Speed: 363.294 samples/sec, CrossEntropy=2.551, SmoothL1=1.120 [Epoch 111][Batch 799], Speed: 354.852 samples/sec, CrossEntropy=2.557, SmoothL1=1.117 [Epoch 111][Batch 899], Speed: 363.426 samples/sec, CrossEntropy=2.559, SmoothL1=1.119 [Epoch 111][Batch 999], Speed: 356.407 samples/sec, CrossEntropy=2.566, SmoothL1=1.122 [Epoch 111][Batch 1099], Speed: 351.862 samples/sec, CrossEntropy=2.567, SmoothL1=1.120 [Epoch 111][Batch 1199], Speed: 351.873 samples/sec, CrossEntropy=2.568, SmoothL1=1.118 [Epoch 111][Batch 1299], Speed: 359.346 samples/sec, CrossEntropy=2.567, SmoothL1=1.118 [Epoch 111][Batch 1399], Speed: 354.371 samples/sec, CrossEntropy=2.567, SmoothL1=1.118 [Epoch 111][Batch 1499], Speed: 361.208 samples/sec, CrossEntropy=2.569, SmoothL1=1.119 [Epoch 111][Batch 1599], Speed: 346.391 samples/sec, CrossEntropy=2.570, SmoothL1=1.119 [Epoch 111][Batch 1699], Speed: 347.474 samples/sec, CrossEntropy=2.570, SmoothL1=1.119 [Epoch 111][Batch 1799], Speed: 345.692 samples/sec, CrossEntropy=2.569, SmoothL1=1.120 [Epoch 111] Training cost: 335.214, CrossEntropy=2.569, SmoothL1=1.119 [Epoch 111] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.379 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.226 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.039 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.229 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.390 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.316 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.066 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.343 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.537 person=31.8 bicycle=14.6 car=18.0 motorcycle=24.9 airplane=44.7 bus=45.9 train=48.1 truck=19.6 boat=9.3 traffic light=6.9 fire hydrant=40.0 stop sign=43.0 parking meter=24.1 bench=11.7 bird=13.2 cat=49.3 dog=42.7 horse=36.1 sheep=28.1 cow=29.5 elephant=44.5 bear=49.0 zebra=46.1 giraffe=46.7 backpack=2.8 umbrella=20.0 handbag=2.7 tie=11.4 suitcase=15.2 frisbee=25.5 skis=10.0 snowboard=9.8 sports ball=15.5 kite=13.8 baseball bat=9.7 baseball glove=9.5 skateboard=21.5 surfboard=16.9 tennis racket=22.9 bottle=10.7 wine glass=10.8 cup=17.2 fork=12.7 knife=4.9 spoon=4.5 bowl=21.3 banana=12.2 apple=7.6 sandwich=27.8 orange=16.7 broccoli=14.9 carrot=8.5 hot dog=19.7 pizza=34.6 donut=22.4 cake=17.5 chair=10.4 couch=29.4 potted plant=10.9 bed=33.6 dining table=19.8 toilet=39.5 tv=38.7 laptop=38.2 mouse=27.9 remote=4.7 keyboard=29.0 cell phone=15.0 microwave=34.5 oven=23.4 toaster=4.1 sink=19.2 refrigerator=35.4 book=3.6 clock=28.7 vase=15.6 scissors=15.6 teddy bear=30.4 hair drier=0.0 toothbrush=6.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.9 [Epoch 112][Batch 99], Speed: 362.913 samples/sec, CrossEntropy=2.556, SmoothL1=1.108 [Epoch 112][Batch 199], Speed: 356.686 samples/sec, CrossEntropy=2.570, SmoothL1=1.127 [Epoch 112][Batch 299], Speed: 349.493 samples/sec, CrossEntropy=2.547, SmoothL1=1.118 [Epoch 112][Batch 399], Speed: 356.671 samples/sec, CrossEntropy=2.534, SmoothL1=1.113 [Epoch 112][Batch 499], Speed: 342.988 samples/sec, CrossEntropy=2.528, SmoothL1=1.109 [Epoch 112][Batch 599], Speed: 354.886 samples/sec, CrossEntropy=2.525, SmoothL1=1.106 [Epoch 112][Batch 699], Speed: 351.106 samples/sec, CrossEntropy=2.527, SmoothL1=1.102 [Epoch 112][Batch 799], Speed: 349.606 samples/sec, CrossEntropy=2.532, SmoothL1=1.103 [Epoch 112][Batch 899], Speed: 351.878 samples/sec, CrossEntropy=2.534, SmoothL1=1.101 [Epoch 112][Batch 999], Speed: 342.915 samples/sec, CrossEntropy=2.539, SmoothL1=1.104 [Epoch 112][Batch 1099], Speed: 356.936 samples/sec, CrossEntropy=2.542, SmoothL1=1.106 [Epoch 112][Batch 1199], Speed: 354.273 samples/sec, CrossEntropy=2.543, SmoothL1=1.104 [Epoch 112][Batch 1299], Speed: 352.201 samples/sec, CrossEntropy=2.543, SmoothL1=1.105 [Epoch 112][Batch 1399], Speed: 353.036 samples/sec, CrossEntropy=2.540, SmoothL1=1.103 [Epoch 112][Batch 1499], Speed: 350.770 samples/sec, CrossEntropy=2.543, SmoothL1=1.103 [Epoch 112][Batch 1599], Speed: 342.245 samples/sec, CrossEntropy=2.545, SmoothL1=1.105 [Epoch 112][Batch 1699], Speed: 347.932 samples/sec, CrossEntropy=2.549, SmoothL1=1.107 [Epoch 112][Batch 1799], Speed: 342.565 samples/sec, CrossEntropy=2.550, SmoothL1=1.107 [Epoch 112] Training cost: 335.364, CrossEntropy=2.551, SmoothL1=1.107 [Epoch 112] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.377 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.231 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.388 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.212 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.317 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.065 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.536 person=31.3 bicycle=15.9 car=17.9 motorcycle=24.3 airplane=43.5 bus=44.8 train=48.7 truck=17.4 boat=9.7 traffic light=7.3 fire hydrant=38.3 stop sign=43.4 parking meter=23.1 bench=11.8 bird=13.4 cat=49.5 dog=40.1 horse=38.0 sheep=27.2 cow=28.8 elephant=42.9 bear=47.5 zebra=45.2 giraffe=46.4 backpack=2.6 umbrella=19.8 handbag=2.6 tie=11.3 suitcase=15.4 frisbee=30.3 skis=9.7 snowboard=7.7 sports ball=15.5 kite=14.2 baseball bat=9.0 baseball glove=12.1 skateboard=21.4 surfboard=16.3 tennis racket=24.2 bottle=11.2 wine glass=11.7 cup=16.3 fork=12.1 knife=4.5 spoon=4.7 bowl=22.3 banana=11.9 apple=8.6 sandwich=24.4 orange=17.0 broccoli=13.5 carrot=8.6 hot dog=20.7 pizza=34.3 donut=23.9 cake=18.1 chair=11.7 couch=29.5 potted plant=11.3 bed=32.8 dining table=20.4 toilet=42.0 tv=38.7 laptop=40.3 mouse=27.1 remote=6.1 keyboard=29.6 cell phone=14.9 microwave=31.3 oven=24.1 toaster=0.0 sink=18.1 refrigerator=35.3 book=3.7 clock=26.1 vase=14.9 scissors=18.6 teddy bear=29.1 hair drier=0.0 toothbrush=6.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.8 [Epoch 113][Batch 99], Speed: 359.885 samples/sec, CrossEntropy=2.512, SmoothL1=1.107 [Epoch 113][Batch 199], Speed: 361.168 samples/sec, CrossEntropy=2.514, SmoothL1=1.105 [Epoch 113][Batch 299], Speed: 353.903 samples/sec, CrossEntropy=2.515, SmoothL1=1.109 [Epoch 113][Batch 399], Speed: 349.636 samples/sec, CrossEntropy=2.507, SmoothL1=1.103 [Epoch 113][Batch 499], Speed: 349.908 samples/sec, CrossEntropy=2.523, SmoothL1=1.108 [Epoch 113][Batch 599], Speed: 350.803 samples/sec, CrossEntropy=2.529, SmoothL1=1.113 [Epoch 113][Batch 699], Speed: 360.883 samples/sec, CrossEntropy=2.535, SmoothL1=1.116 [Epoch 113][Batch 799], Speed: 364.070 samples/sec, CrossEntropy=2.535, SmoothL1=1.115 [Epoch 113][Batch 899], Speed: 350.351 samples/sec, CrossEntropy=2.535, SmoothL1=1.115 [Epoch 113][Batch 999], Speed: 361.826 samples/sec, CrossEntropy=2.537, SmoothL1=1.117 [Epoch 113][Batch 1099], Speed: 357.606 samples/sec, CrossEntropy=2.539, SmoothL1=1.117 [Epoch 113][Batch 1199], Speed: 347.030 samples/sec, CrossEntropy=2.539, SmoothL1=1.116 [Epoch 113][Batch 1299], Speed: 339.246 samples/sec, CrossEntropy=2.541, SmoothL1=1.117 [Epoch 113][Batch 1399], Speed: 358.856 samples/sec, CrossEntropy=2.543, SmoothL1=1.117 [Epoch 113][Batch 1499], Speed: 355.098 samples/sec, CrossEntropy=2.542, SmoothL1=1.115 [Epoch 113][Batch 1599], Speed: 352.413 samples/sec, CrossEntropy=2.547, SmoothL1=1.115 [Epoch 113][Batch 1699], Speed: 344.303 samples/sec, CrossEntropy=2.548, SmoothL1=1.117 [Epoch 113][Batch 1799], Speed: 349.783 samples/sec, CrossEntropy=2.550, SmoothL1=1.118 [Epoch 113] Training cost: 334.816, CrossEntropy=2.549, SmoothL1=1.118 [Epoch 113] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.379 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.229 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.383 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.212 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.303 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.316 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.340 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.526 person=32.1 bicycle=15.7 car=18.5 motorcycle=24.2 airplane=41.7 bus=46.7 train=46.2 truck=18.2 boat=9.2 traffic light=6.4 fire hydrant=37.2 stop sign=42.1 parking meter=27.2 bench=10.8 bird=13.3 cat=51.4 dog=41.7 horse=35.2 sheep=28.0 cow=26.3 elephant=42.3 bear=46.2 zebra=43.2 giraffe=45.4 backpack=3.3 umbrella=20.0 handbag=2.6 tie=10.9 suitcase=15.5 frisbee=26.0 skis=9.3 snowboard=9.1 sports ball=13.9 kite=14.9 baseball bat=8.1 baseball glove=9.8 skateboard=24.8 surfboard=15.9 tennis racket=24.0 bottle=10.5 wine glass=11.2 cup=16.8 fork=12.6 knife=4.3 spoon=4.0 bowl=22.4 banana=12.5 apple=9.6 sandwich=25.3 orange=19.4 broccoli=12.8 carrot=9.3 hot dog=19.3 pizza=35.2 donut=23.8 cake=19.4 chair=10.3 couch=31.6 potted plant=10.4 bed=34.6 dining table=20.3 toilet=42.2 tv=39.5 laptop=40.0 mouse=26.2 remote=6.2 keyboard=28.8 cell phone=14.9 microwave=34.2 oven=26.1 toaster=3.0 sink=17.8 refrigerator=35.1 book=3.8 clock=28.0 vase=14.8 scissors=14.7 teddy bear=29.2 hair drier=0.0 toothbrush=5.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.8 [Epoch 114][Batch 99], Speed: 346.422 samples/sec, CrossEntropy=2.545, SmoothL1=1.096 [Epoch 114][Batch 199], Speed: 354.337 samples/sec, CrossEntropy=2.544, SmoothL1=1.104 [Epoch 114][Batch 299], Speed: 348.854 samples/sec, CrossEntropy=2.528, SmoothL1=1.100 [Epoch 114][Batch 399], Speed: 357.575 samples/sec, CrossEntropy=2.517, SmoothL1=1.101 [Epoch 114][Batch 499], Speed: 344.942 samples/sec, CrossEntropy=2.524, SmoothL1=1.102 [Epoch 114][Batch 599], Speed: 359.726 samples/sec, CrossEntropy=2.530, SmoothL1=1.104 [Epoch 114][Batch 699], Speed: 346.466 samples/sec, CrossEntropy=2.535, SmoothL1=1.104 [Epoch 114][Batch 799], Speed: 354.226 samples/sec, CrossEntropy=2.538, SmoothL1=1.108 [Epoch 114][Batch 899], Speed: 340.924 samples/sec, CrossEntropy=2.538, SmoothL1=1.108 [Epoch 114][Batch 999], Speed: 348.786 samples/sec, CrossEntropy=2.542, SmoothL1=1.110 [Epoch 114][Batch 1099], Speed: 355.695 samples/sec, CrossEntropy=2.549, SmoothL1=1.114 [Epoch 114][Batch 1199], Speed: 353.828 samples/sec, CrossEntropy=2.550, SmoothL1=1.114 [Epoch 114][Batch 1299], Speed: 355.410 samples/sec, CrossEntropy=2.553, SmoothL1=1.114 [Epoch 114][Batch 1399], Speed: 348.820 samples/sec, CrossEntropy=2.551, SmoothL1=1.114 [Epoch 114][Batch 1499], Speed: 358.794 samples/sec, CrossEntropy=2.554, SmoothL1=1.113 [Epoch 114][Batch 1599], Speed: 352.265 samples/sec, CrossEntropy=2.557, SmoothL1=1.115 [Epoch 114][Batch 1699], Speed: 358.300 samples/sec, CrossEntropy=2.561, SmoothL1=1.115 [Epoch 114][Batch 1799], Speed: 353.280 samples/sec, CrossEntropy=2.561, SmoothL1=1.115 [Epoch 114] Training cost: 336.021, CrossEntropy=2.562, SmoothL1=1.116 [Epoch 114] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.220 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.385 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.228 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.235 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.384 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.306 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.319 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.352 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.528 person=32.3 bicycle=15.2 car=17.4 motorcycle=23.6 airplane=41.5 bus=45.6 train=48.1 truck=19.1 boat=10.3 traffic light=6.9 fire hydrant=38.1 stop sign=41.0 parking meter=30.0 bench=11.7 bird=14.1 cat=47.8 dog=41.8 horse=34.1 sheep=28.5 cow=28.9 elephant=42.2 bear=48.3 zebra=43.4 giraffe=47.5 backpack=2.8 umbrella=21.4 handbag=2.7 tie=11.6 suitcase=14.3 frisbee=26.9 skis=9.7 snowboard=9.2 sports ball=16.2 kite=14.5 baseball bat=9.4 baseball glove=11.8 skateboard=23.0 surfboard=16.1 tennis racket=22.8 bottle=10.5 wine glass=11.7 cup=16.9 fork=11.5 knife=5.0 spoon=3.9 bowl=22.4 banana=12.6 apple=8.9 sandwich=26.8 orange=17.2 broccoli=12.9 carrot=9.2 hot dog=21.1 pizza=33.5 donut=23.6 cake=18.4 chair=11.9 couch=30.1 potted plant=11.3 bed=35.2 dining table=19.2 toilet=41.8 tv=38.1 laptop=40.8 mouse=29.2 remote=5.6 keyboard=30.5 cell phone=14.6 microwave=29.8 oven=25.6 toaster=8.3 sink=21.4 refrigerator=37.2 book=3.4 clock=28.4 vase=15.5 scissors=14.1 teddy bear=30.1 hair drier=0.0 toothbrush=3.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.0 [Epoch 115][Batch 99], Speed: 351.265 samples/sec, CrossEntropy=2.524, SmoothL1=1.111 [Epoch 115][Batch 199], Speed: 355.859 samples/sec, CrossEntropy=2.510, SmoothL1=1.101 [Epoch 115][Batch 299], Speed: 359.524 samples/sec, CrossEntropy=2.518, SmoothL1=1.101 [Epoch 115][Batch 399], Speed: 345.631 samples/sec, CrossEntropy=2.528, SmoothL1=1.107 [Epoch 115][Batch 499], Speed: 357.825 samples/sec, CrossEntropy=2.529, SmoothL1=1.108 [Epoch 115][Batch 599], Speed: 361.812 samples/sec, CrossEntropy=2.531, SmoothL1=1.107 [Epoch 115][Batch 699], Speed: 354.965 samples/sec, CrossEntropy=2.535, SmoothL1=1.107 [Epoch 115][Batch 799], Speed: 343.482 samples/sec, CrossEntropy=2.535, SmoothL1=1.104 [Epoch 115][Batch 899], Speed: 351.161 samples/sec, CrossEntropy=2.538, SmoothL1=1.103 [Epoch 115][Batch 999], Speed: 356.267 samples/sec, CrossEntropy=2.539, SmoothL1=1.105 [Epoch 115][Batch 1099], Speed: 346.945 samples/sec, CrossEntropy=2.539, SmoothL1=1.104 [Epoch 115][Batch 1199], Speed: 359.937 samples/sec, CrossEntropy=2.541, SmoothL1=1.106 [Epoch 115][Batch 1299], Speed: 350.442 samples/sec, CrossEntropy=2.541, SmoothL1=1.106 [Epoch 115][Batch 1399], Speed: 348.236 samples/sec, CrossEntropy=2.547, SmoothL1=1.109 [Epoch 115][Batch 1499], Speed: 359.405 samples/sec, CrossEntropy=2.547, SmoothL1=1.107 [Epoch 115][Batch 1599], Speed: 350.674 samples/sec, CrossEntropy=2.546, SmoothL1=1.107 [Epoch 115][Batch 1699], Speed: 357.541 samples/sec, CrossEntropy=2.550, SmoothL1=1.109 [Epoch 115][Batch 1799], Speed: 346.914 samples/sec, CrossEntropy=2.552, SmoothL1=1.109 [Epoch 115] Training cost: 334.668, CrossEntropy=2.552, SmoothL1=1.111 [Epoch 115] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.223 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.382 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.232 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.398 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.305 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.319 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.070 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.339 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.538 person=32.0 bicycle=14.7 car=18.5 motorcycle=25.4 airplane=43.5 bus=45.9 train=46.7 truck=18.3 boat=8.9 traffic light=7.1 fire hydrant=40.8 stop sign=42.0 parking meter=29.4 bench=11.7 bird=14.2 cat=51.1 dog=42.2 horse=35.6 sheep=28.2 cow=28.2 elephant=41.9 bear=48.9 zebra=46.3 giraffe=49.7 backpack=2.4 umbrella=19.9 handbag=3.5 tie=11.7 suitcase=15.7 frisbee=27.3 skis=9.9 snowboard=8.6 sports ball=17.8 kite=13.7 baseball bat=9.2 baseball glove=10.2 skateboard=22.3 surfboard=15.8 tennis racket=23.1 bottle=11.5 wine glass=12.2 cup=17.1 fork=12.4 knife=4.3 spoon=3.5 bowl=22.8 banana=12.2 apple=9.8 sandwich=26.1 orange=19.7 broccoli=13.4 carrot=9.6 hot dog=20.9 pizza=35.3 donut=24.6 cake=19.2 chair=11.4 couch=29.0 potted plant=11.6 bed=33.8 dining table=21.1 toilet=40.1 tv=39.6 laptop=41.0 mouse=28.1 remote=5.2 keyboard=31.5 cell phone=14.5 microwave=36.2 oven=25.5 toaster=0.0 sink=19.8 refrigerator=36.1 book=3.2 clock=28.7 vase=15.0 scissors=17.2 teddy bear=30.9 hair drier=0.0 toothbrush=6.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.3 [Epoch 116][Batch 99], Speed: 351.951 samples/sec, CrossEntropy=2.487, SmoothL1=1.114 [Epoch 116][Batch 199], Speed: 362.243 samples/sec, CrossEntropy=2.503, SmoothL1=1.104 [Epoch 116][Batch 299], Speed: 358.965 samples/sec, CrossEntropy=2.504, SmoothL1=1.108 [Epoch 116][Batch 399], Speed: 360.120 samples/sec, CrossEntropy=2.516, SmoothL1=1.109 [Epoch 116][Batch 499], Speed: 348.466 samples/sec, CrossEntropy=2.524, SmoothL1=1.110 [Epoch 116][Batch 599], Speed: 342.429 samples/sec, CrossEntropy=2.527, SmoothL1=1.109 [Epoch 116][Batch 699], Speed: 351.853 samples/sec, CrossEntropy=2.525, SmoothL1=1.106 [Epoch 116][Batch 799], Speed: 345.927 samples/sec, CrossEntropy=2.526, SmoothL1=1.110 [Epoch 116][Batch 899], Speed: 359.576 samples/sec, CrossEntropy=2.527, SmoothL1=1.112 [Epoch 116][Batch 999], Speed: 348.684 samples/sec, CrossEntropy=2.530, SmoothL1=1.110 [Epoch 116][Batch 1099], Speed: 356.572 samples/sec, CrossEntropy=2.532, SmoothL1=1.110 [Epoch 116][Batch 1199], Speed: 347.724 samples/sec, CrossEntropy=2.532, SmoothL1=1.109 [Epoch 116][Batch 1299], Speed: 348.674 samples/sec, CrossEntropy=2.534, SmoothL1=1.110 [Epoch 116][Batch 1399], Speed: 344.508 samples/sec, CrossEntropy=2.536, SmoothL1=1.108 [Epoch 116][Batch 1499], Speed: 358.747 samples/sec, CrossEntropy=2.535, SmoothL1=1.107 [Epoch 116][Batch 1599], Speed: 359.952 samples/sec, CrossEntropy=2.537, SmoothL1=1.106 [Epoch 116][Batch 1699], Speed: 352.635 samples/sec, CrossEntropy=2.537, SmoothL1=1.106 [Epoch 116][Batch 1799], Speed: 360.452 samples/sec, CrossEntropy=2.540, SmoothL1=1.109 [Epoch 116] Training cost: 334.956, CrossEntropy=2.541, SmoothL1=1.109 [Epoch 116] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.381 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.226 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.037 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.232 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.385 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.212 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.302 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.315 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.065 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.341 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.533 person=31.5 bicycle=15.9 car=18.9 motorcycle=25.6 airplane=43.8 bus=46.5 train=46.8 truck=19.3 boat=9.7 traffic light=6.4 fire hydrant=40.1 stop sign=42.0 parking meter=26.0 bench=12.2 bird=13.5 cat=49.3 dog=39.7 horse=34.8 sheep=28.7 cow=27.6 elephant=40.6 bear=47.8 zebra=43.9 giraffe=47.3 backpack=2.3 umbrella=19.1 handbag=2.6 tie=13.3 suitcase=14.9 frisbee=24.8 skis=8.8 snowboard=8.7 sports ball=16.3 kite=12.5 baseball bat=9.2 baseball glove=10.5 skateboard=21.6 surfboard=15.7 tennis racket=22.4 bottle=10.3 wine glass=11.6 cup=17.0 fork=12.3 knife=4.7 spoon=4.0 bowl=22.3 banana=12.4 apple=10.2 sandwich=25.4 orange=18.6 broccoli=12.6 carrot=9.9 hot dog=20.4 pizza=33.9 donut=23.2 cake=16.5 chair=11.0 couch=31.2 potted plant=11.7 bed=33.7 dining table=19.0 toilet=42.1 tv=39.6 laptop=41.6 mouse=24.6 remote=5.1 keyboard=30.6 cell phone=15.5 microwave=33.9 oven=23.9 toaster=7.1 sink=17.9 refrigerator=34.6 book=3.5 clock=26.5 vase=14.7 scissors=16.0 teddy bear=30.3 hair drier=0.0 toothbrush=6.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.8 [Epoch 117][Batch 99], Speed: 357.576 samples/sec, CrossEntropy=2.569, SmoothL1=1.106 [Epoch 117][Batch 199], Speed: 346.867 samples/sec, CrossEntropy=2.551, SmoothL1=1.105 [Epoch 117][Batch 299], Speed: 354.159 samples/sec, CrossEntropy=2.541, SmoothL1=1.110 [Epoch 117][Batch 399], Speed: 354.078 samples/sec, CrossEntropy=2.537, SmoothL1=1.105 [Epoch 117][Batch 499], Speed: 357.413 samples/sec, CrossEntropy=2.533, SmoothL1=1.102 [Epoch 117][Batch 599], Speed: 351.310 samples/sec, CrossEntropy=2.533, SmoothL1=1.101 [Epoch 117][Batch 699], Speed: 358.908 samples/sec, CrossEntropy=2.534, SmoothL1=1.103 [Epoch 117][Batch 799], Speed: 359.137 samples/sec, CrossEntropy=2.538, SmoothL1=1.101 [Epoch 117][Batch 899], Speed: 347.000 samples/sec, CrossEntropy=2.543, SmoothL1=1.106 [Epoch 117][Batch 999], Speed: 353.569 samples/sec, CrossEntropy=2.542, SmoothL1=1.107 [Epoch 117][Batch 1099], Speed: 362.855 samples/sec, CrossEntropy=2.541, SmoothL1=1.108 [Epoch 117][Batch 1199], Speed: 348.082 samples/sec, CrossEntropy=2.543, SmoothL1=1.108 [Epoch 117][Batch 1299], Speed: 342.629 samples/sec, CrossEntropy=2.543, SmoothL1=1.108 [Epoch 117][Batch 1399], Speed: 359.404 samples/sec, CrossEntropy=2.544, SmoothL1=1.108 [Epoch 117][Batch 1499], Speed: 352.781 samples/sec, CrossEntropy=2.544, SmoothL1=1.108 [Epoch 117][Batch 1599], Speed: 350.222 samples/sec, CrossEntropy=2.544, SmoothL1=1.106 [Epoch 117][Batch 1699], Speed: 349.348 samples/sec, CrossEntropy=2.545, SmoothL1=1.106 [Epoch 117][Batch 1799], Speed: 360.567 samples/sec, CrossEntropy=2.545, SmoothL1=1.108 [Epoch 117] Training cost: 335.635, CrossEntropy=2.545, SmoothL1=1.108 [Epoch 117] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.382 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.233 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.386 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.305 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.318 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.343 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.532 person=31.6 bicycle=15.4 car=17.8 motorcycle=24.6 airplane=42.6 bus=46.4 train=48.4 truck=17.9 boat=10.0 traffic light=7.2 fire hydrant=41.0 stop sign=42.5 parking meter=27.6 bench=11.3 bird=14.2 cat=47.4 dog=42.2 horse=36.8 sheep=30.4 cow=28.9 elephant=43.7 bear=52.2 zebra=43.9 giraffe=47.8 backpack=2.4 umbrella=20.0 handbag=2.6 tie=11.8 suitcase=12.9 frisbee=25.5 skis=9.6 snowboard=7.9 sports ball=16.2 kite=14.5 baseball bat=9.4 baseball glove=11.1 skateboard=24.2 surfboard=17.0 tennis racket=22.1 bottle=10.4 wine glass=11.6 cup=17.2 fork=10.8 knife=4.2 spoon=4.2 bowl=23.0 banana=11.8 apple=9.3 sandwich=27.5 orange=17.3 broccoli=13.8 carrot=9.0 hot dog=21.8 pizza=34.4 donut=24.3 cake=18.1 chair=11.9 couch=29.6 potted plant=12.0 bed=35.0 dining table=20.3 toilet=39.7 tv=37.2 laptop=40.9 mouse=27.8 remote=5.5 keyboard=28.9 cell phone=14.6 microwave=32.1 oven=25.1 toaster=2.4 sink=19.7 refrigerator=33.0 book=3.7 clock=27.6 vase=14.6 scissors=21.3 teddy bear=30.5 hair drier=0.0 toothbrush=3.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.1 [Epoch 118][Batch 99], Speed: 356.569 samples/sec, CrossEntropy=2.504, SmoothL1=1.090 [Epoch 118][Batch 199], Speed: 352.051 samples/sec, CrossEntropy=2.485, SmoothL1=1.076 [Epoch 118][Batch 299], Speed: 351.127 samples/sec, CrossEntropy=2.499, SmoothL1=1.074 [Epoch 118][Batch 399], Speed: 346.313 samples/sec, CrossEntropy=2.500, SmoothL1=1.077 [Epoch 118][Batch 499], Speed: 361.909 samples/sec, CrossEntropy=2.493, SmoothL1=1.076 [Epoch 118][Batch 599], Speed: 344.436 samples/sec, CrossEntropy=2.510, SmoothL1=1.088 [Epoch 118][Batch 699], Speed: 350.903 samples/sec, CrossEntropy=2.512, SmoothL1=1.090 [Epoch 118][Batch 799], Speed: 354.442 samples/sec, CrossEntropy=2.516, SmoothL1=1.091 [Epoch 118][Batch 899], Speed: 360.303 samples/sec, CrossEntropy=2.519, SmoothL1=1.091 [Epoch 118][Batch 999], Speed: 354.031 samples/sec, CrossEntropy=2.524, SmoothL1=1.093 [Epoch 118][Batch 1099], Speed: 349.463 samples/sec, CrossEntropy=2.526, SmoothL1=1.097 [Epoch 118][Batch 1199], Speed: 363.591 samples/sec, CrossEntropy=2.525, SmoothL1=1.097 [Epoch 118][Batch 1299], Speed: 347.026 samples/sec, CrossEntropy=2.527, SmoothL1=1.098 [Epoch 118][Batch 1399], Speed: 351.513 samples/sec, CrossEntropy=2.526, SmoothL1=1.098 [Epoch 118][Batch 1499], Speed: 352.945 samples/sec, CrossEntropy=2.528, SmoothL1=1.099 [Epoch 118][Batch 1599], Speed: 340.626 samples/sec, CrossEntropy=2.531, SmoothL1=1.102 [Epoch 118][Batch 1699], Speed: 348.971 samples/sec, CrossEntropy=2.532, SmoothL1=1.103 [Epoch 118][Batch 1799], Speed: 350.852 samples/sec, CrossEntropy=2.535, SmoothL1=1.105 [Epoch 118] Training cost: 335.431, CrossEntropy=2.533, SmoothL1=1.104 [Epoch 118] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.385 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.229 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.235 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.395 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.215 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.305 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.316 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.066 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.540 person=31.9 bicycle=15.0 car=18.0 motorcycle=24.6 airplane=41.7 bus=44.1 train=46.0 truck=16.9 boat=10.1 traffic light=7.0 fire hydrant=40.3 stop sign=39.0 parking meter=25.7 bench=12.0 bird=13.9 cat=48.9 dog=43.6 horse=38.3 sheep=28.6 cow=28.1 elephant=40.4 bear=50.6 zebra=47.0 giraffe=48.1 backpack=2.9 umbrella=20.9 handbag=2.8 tie=12.1 suitcase=15.9 frisbee=27.0 skis=9.1 snowboard=9.0 sports ball=16.0 kite=14.3 baseball bat=10.1 baseball glove=10.9 skateboard=24.5 surfboard=17.3 tennis racket=23.4 bottle=11.3 wine glass=13.4 cup=17.4 fork=13.0 knife=4.0 spoon=5.1 bowl=22.2 banana=13.5 apple=10.6 sandwich=24.2 orange=18.0 broccoli=12.2 carrot=8.0 hot dog=19.3 pizza=34.2 donut=22.8 cake=18.1 chair=11.6 couch=31.3 potted plant=12.2 bed=35.3 dining table=20.2 toilet=42.6 tv=39.9 laptop=41.6 mouse=28.1 remote=5.7 keyboard=29.3 cell phone=14.4 microwave=30.2 oven=24.6 toaster=6.4 sink=19.2 refrigerator=34.9 book=3.8 clock=28.1 vase=16.2 scissors=15.0 teddy bear=29.3 hair drier=0.0 toothbrush=4.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.1 [Epoch 119][Batch 99], Speed: 351.041 samples/sec, CrossEntropy=2.523, SmoothL1=1.103 [Epoch 119][Batch 199], Speed: 360.844 samples/sec, CrossEntropy=2.525, SmoothL1=1.100 [Epoch 119][Batch 299], Speed: 350.625 samples/sec, CrossEntropy=2.524, SmoothL1=1.095 [Epoch 119][Batch 399], Speed: 360.857 samples/sec, CrossEntropy=2.525, SmoothL1=1.094 [Epoch 119][Batch 499], Speed: 352.043 samples/sec, CrossEntropy=2.528, SmoothL1=1.100 [Epoch 119][Batch 599], Speed: 351.871 samples/sec, CrossEntropy=2.533, SmoothL1=1.104 [Epoch 119][Batch 699], Speed: 357.523 samples/sec, CrossEntropy=2.531, SmoothL1=1.101 [Epoch 119][Batch 799], Speed: 354.786 samples/sec, CrossEntropy=2.531, SmoothL1=1.100 [Epoch 119][Batch 899], Speed: 357.201 samples/sec, CrossEntropy=2.537, SmoothL1=1.104 [Epoch 119][Batch 999], Speed: 345.461 samples/sec, CrossEntropy=2.546, SmoothL1=1.110 [Epoch 119][Batch 1099], Speed: 343.407 samples/sec, CrossEntropy=2.544, SmoothL1=1.106 [Epoch 119][Batch 1199], Speed: 359.523 samples/sec, CrossEntropy=2.542, SmoothL1=1.104 [Epoch 119][Batch 1299], Speed: 344.395 samples/sec, CrossEntropy=2.544, SmoothL1=1.105 [Epoch 119][Batch 1399], Speed: 342.107 samples/sec, CrossEntropy=2.547, SmoothL1=1.107 [Epoch 119][Batch 1499], Speed: 353.213 samples/sec, CrossEntropy=2.547, SmoothL1=1.109 [Epoch 119][Batch 1599], Speed: 358.875 samples/sec, CrossEntropy=2.547, SmoothL1=1.109 [Epoch 119][Batch 1699], Speed: 345.332 samples/sec, CrossEntropy=2.548, SmoothL1=1.110 [Epoch 119][Batch 1799], Speed: 358.969 samples/sec, CrossEntropy=2.549, SmoothL1=1.112 [Epoch 119] Training cost: 334.741, CrossEntropy=2.549, SmoothL1=1.112 [Epoch 119] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.382 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.229 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.234 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.393 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.305 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.318 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.538 person=31.7 bicycle=15.0 car=18.2 motorcycle=25.9 airplane=44.6 bus=47.3 train=47.3 truck=19.4 boat=8.6 traffic light=6.9 fire hydrant=38.9 stop sign=43.5 parking meter=29.4 bench=12.1 bird=13.7 cat=48.4 dog=41.5 horse=36.6 sheep=27.2 cow=28.0 elephant=41.5 bear=53.3 zebra=44.3 giraffe=45.7 backpack=2.6 umbrella=20.1 handbag=2.4 tie=12.3 suitcase=15.6 frisbee=25.5 skis=10.1 snowboard=8.5 sports ball=16.5 kite=14.2 baseball bat=9.4 baseball glove=11.2 skateboard=24.4 surfboard=16.1 tennis racket=22.9 bottle=10.6 wine glass=11.8 cup=16.6 fork=10.4 knife=4.9 spoon=3.9 bowl=21.3 banana=14.5 apple=9.3 sandwich=24.5 orange=17.8 broccoli=11.9 carrot=9.5 hot dog=20.8 pizza=34.3 donut=24.8 cake=18.6 chair=11.6 couch=31.4 potted plant=12.2 bed=30.8 dining table=19.2 toilet=41.2 tv=38.5 laptop=39.2 mouse=26.2 remote=6.5 keyboard=28.7 cell phone=15.3 microwave=35.3 oven=26.4 toaster=5.9 sink=20.1 refrigerator=35.6 book=3.4 clock=27.9 vase=15.7 scissors=15.9 teddy bear=30.0 hair drier=0.0 toothbrush=5.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.1 [Epoch 120][Batch 99], Speed: 355.312 samples/sec, CrossEntropy=2.526, SmoothL1=1.107 [Epoch 120][Batch 199], Speed: 348.317 samples/sec, CrossEntropy=2.534, SmoothL1=1.120 [Epoch 120][Batch 299], Speed: 346.482 samples/sec, CrossEntropy=2.527, SmoothL1=1.108 [Epoch 120][Batch 399], Speed: 356.484 samples/sec, CrossEntropy=2.526, SmoothL1=1.107 [Epoch 120][Batch 499], Speed: 356.125 samples/sec, CrossEntropy=2.528, SmoothL1=1.100 [Epoch 120][Batch 599], Speed: 357.469 samples/sec, CrossEntropy=2.530, SmoothL1=1.095 [Epoch 120][Batch 699], Speed: 358.558 samples/sec, CrossEntropy=2.525, SmoothL1=1.092 [Epoch 120][Batch 799], Speed: 358.379 samples/sec, CrossEntropy=2.530, SmoothL1=1.093 [Epoch 120][Batch 899], Speed: 349.297 samples/sec, CrossEntropy=2.531, SmoothL1=1.092 [Epoch 120][Batch 999], Speed: 354.813 samples/sec, CrossEntropy=2.530, SmoothL1=1.092 [Epoch 120][Batch 1099], Speed: 351.702 samples/sec, CrossEntropy=2.531, SmoothL1=1.092 [Epoch 120][Batch 1199], Speed: 363.956 samples/sec, CrossEntropy=2.529, SmoothL1=1.092 [Epoch 120][Batch 1299], Speed: 357.588 samples/sec, CrossEntropy=2.530, SmoothL1=1.092 [Epoch 120][Batch 1399], Speed: 345.587 samples/sec, CrossEntropy=2.531, SmoothL1=1.092 [Epoch 120][Batch 1499], Speed: 349.657 samples/sec, CrossEntropy=2.535, SmoothL1=1.093 [Epoch 120][Batch 1599], Speed: 358.247 samples/sec, CrossEntropy=2.538, SmoothL1=1.095 [Epoch 120][Batch 1699], Speed: 351.238 samples/sec, CrossEntropy=2.538, SmoothL1=1.096 [Epoch 120][Batch 1799], Speed: 356.911 samples/sec, CrossEntropy=2.537, SmoothL1=1.098 [Epoch 120] Training cost: 334.846, CrossEntropy=2.537, SmoothL1=1.098 [Epoch 120] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.224 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.387 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.233 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.239 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.393 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.306 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.318 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.535 person=32.2 bicycle=15.3 car=17.9 motorcycle=24.8 airplane=42.2 bus=47.3 train=49.4 truck=18.6 boat=8.6 traffic light=6.8 fire hydrant=38.4 stop sign=43.9 parking meter=27.3 bench=12.4 bird=14.4 cat=50.6 dog=43.8 horse=34.6 sheep=30.3 cow=28.2 elephant=42.6 bear=54.2 zebra=43.8 giraffe=46.4 backpack=2.5 umbrella=21.1 handbag=2.9 tie=13.2 suitcase=15.8 frisbee=26.3 skis=10.0 snowboard=9.8 sports ball=17.2 kite=14.6 baseball bat=10.2 baseball glove=11.0 skateboard=24.3 surfboard=16.4 tennis racket=22.5 bottle=11.1 wine glass=11.8 cup=17.6 fork=12.8 knife=5.2 spoon=4.6 bowl=22.6 banana=14.6 apple=8.1 sandwich=26.9 orange=17.3 broccoli=11.3 carrot=9.3 hot dog=21.9 pizza=34.7 donut=24.1 cake=19.3 chair=11.7 couch=31.6 potted plant=11.6 bed=32.4 dining table=19.7 toilet=40.3 tv=39.5 laptop=40.5 mouse=28.8 remote=5.9 keyboard=32.3 cell phone=15.4 microwave=31.0 oven=25.2 toaster=4.2 sink=19.3 refrigerator=32.8 book=4.0 clock=27.8 vase=14.9 scissors=21.1 teddy bear=30.1 hair drier=0.0 toothbrush=6.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.4 [Epoch 121][Batch 99], Speed: 347.768 samples/sec, CrossEntropy=2.501, SmoothL1=1.109 [Epoch 121][Batch 199], Speed: 360.941 samples/sec, CrossEntropy=2.488, SmoothL1=1.085 [Epoch 121][Batch 299], Speed: 349.066 samples/sec, CrossEntropy=2.501, SmoothL1=1.088 [Epoch 121][Batch 399], Speed: 343.399 samples/sec, CrossEntropy=2.500, SmoothL1=1.078 [Epoch 121][Batch 499], Speed: 355.562 samples/sec, CrossEntropy=2.500, SmoothL1=1.079 [Epoch 121][Batch 599], Speed: 361.547 samples/sec, CrossEntropy=2.502, SmoothL1=1.084 [Epoch 121][Batch 699], Speed: 359.086 samples/sec, CrossEntropy=2.507, SmoothL1=1.083 [Epoch 121][Batch 799], Speed: 351.681 samples/sec, CrossEntropy=2.513, SmoothL1=1.087 [Epoch 121][Batch 899], Speed: 346.164 samples/sec, CrossEntropy=2.516, SmoothL1=1.089 [Epoch 121][Batch 999], Speed: 357.181 samples/sec, CrossEntropy=2.513, SmoothL1=1.088 [Epoch 121][Batch 1099], Speed: 362.191 samples/sec, CrossEntropy=2.515, SmoothL1=1.091 [Epoch 121][Batch 1199], Speed: 340.123 samples/sec, CrossEntropy=2.516, SmoothL1=1.094 [Epoch 121][Batch 1299], Speed: 340.727 samples/sec, CrossEntropy=2.520, SmoothL1=1.095 [Epoch 121][Batch 1399], Speed: 347.494 samples/sec, CrossEntropy=2.523, SmoothL1=1.095 [Epoch 121][Batch 1499], Speed: 349.992 samples/sec, CrossEntropy=2.524, SmoothL1=1.095 [Epoch 121][Batch 1599], Speed: 357.982 samples/sec, CrossEntropy=2.524, SmoothL1=1.095 [Epoch 121][Batch 1699], Speed: 366.028 samples/sec, CrossEntropy=2.524, SmoothL1=1.095 [Epoch 121][Batch 1799], Speed: 354.090 samples/sec, CrossEntropy=2.522, SmoothL1=1.093 [Epoch 121] Training cost: 334.542, CrossEntropy=2.522, SmoothL1=1.093 [Epoch 121] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.222 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.386 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.229 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.042 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.240 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.388 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.215 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.307 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.319 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.348 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.533 person=31.9 bicycle=15.4 car=18.3 motorcycle=24.3 airplane=44.0 bus=45.4 train=46.9 truck=18.3 boat=8.7 traffic light=6.9 fire hydrant=42.0 stop sign=41.8 parking meter=28.0 bench=12.3 bird=14.3 cat=50.2 dog=42.8 horse=37.2 sheep=30.1 cow=29.2 elephant=42.5 bear=49.9 zebra=45.3 giraffe=44.1 backpack=2.8 umbrella=20.1 handbag=2.8 tie=12.9 suitcase=16.2 frisbee=26.6 skis=9.6 snowboard=11.3 sports ball=16.0 kite=15.4 baseball bat=10.8 baseball glove=12.3 skateboard=23.1 surfboard=15.6 tennis racket=23.7 bottle=11.8 wine glass=11.1 cup=17.0 fork=11.6 knife=4.8 spoon=4.6 bowl=23.1 banana=14.2 apple=8.0 sandwich=27.0 orange=18.7 broccoli=14.2 carrot=9.0 hot dog=19.7 pizza=34.1 donut=25.4 cake=18.4 chair=11.1 couch=32.1 potted plant=12.0 bed=31.6 dining table=20.1 toilet=40.2 tv=38.2 laptop=38.6 mouse=25.9 remote=5.0 keyboard=31.6 cell phone=14.7 microwave=33.4 oven=25.7 toaster=2.9 sink=18.0 refrigerator=37.4 book=3.8 clock=27.8 vase=14.3 scissors=16.7 teddy bear=29.9 hair drier=0.0 toothbrush=4.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.2 [Epoch 122][Batch 99], Speed: 353.157 samples/sec, CrossEntropy=2.539, SmoothL1=1.121 [Epoch 122][Batch 199], Speed: 352.292 samples/sec, CrossEntropy=2.522, SmoothL1=1.104 [Epoch 122][Batch 299], Speed: 355.025 samples/sec, CrossEntropy=2.517, SmoothL1=1.093 [Epoch 122][Batch 399], Speed: 356.066 samples/sec, CrossEntropy=2.527, SmoothL1=1.095 [Epoch 122][Batch 499], Speed: 364.002 samples/sec, CrossEntropy=2.527, SmoothL1=1.102 [Epoch 122][Batch 599], Speed: 363.067 samples/sec, CrossEntropy=2.526, SmoothL1=1.104 [Epoch 122][Batch 699], Speed: 341.838 samples/sec, CrossEntropy=2.531, SmoothL1=1.103 [Epoch 122][Batch 799], Speed: 345.369 samples/sec, CrossEntropy=2.529, SmoothL1=1.102 [Epoch 122][Batch 899], Speed: 350.118 samples/sec, CrossEntropy=2.530, SmoothL1=1.102 [Epoch 122][Batch 999], Speed: 357.916 samples/sec, CrossEntropy=2.529, SmoothL1=1.098 [Epoch 122][Batch 1099], Speed: 352.823 samples/sec, CrossEntropy=2.529, SmoothL1=1.096 [Epoch 122][Batch 1199], Speed: 349.776 samples/sec, CrossEntropy=2.529, SmoothL1=1.097 [Epoch 122][Batch 1299], Speed: 344.632 samples/sec, CrossEntropy=2.532, SmoothL1=1.096 [Epoch 122][Batch 1399], Speed: 360.879 samples/sec, CrossEntropy=2.532, SmoothL1=1.096 [Epoch 122][Batch 1499], Speed: 349.546 samples/sec, CrossEntropy=2.534, SmoothL1=1.100 [Epoch 122][Batch 1599], Speed: 352.494 samples/sec, CrossEntropy=2.535, SmoothL1=1.100 [Epoch 122][Batch 1699], Speed: 346.576 samples/sec, CrossEntropy=2.535, SmoothL1=1.101 [Epoch 122][Batch 1799], Speed: 353.579 samples/sec, CrossEntropy=2.534, SmoothL1=1.097 [Epoch 122] Training cost: 335.505, CrossEntropy=2.533, SmoothL1=1.097 [Epoch 122] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.223 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.381 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.232 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.041 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.234 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.388 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.305 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.317 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.347 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.531 person=32.1 bicycle=15.2 car=18.2 motorcycle=25.9 airplane=42.2 bus=45.7 train=49.1 truck=18.4 boat=10.0 traffic light=6.9 fire hydrant=40.5 stop sign=44.2 parking meter=31.7 bench=11.7 bird=13.1 cat=49.9 dog=43.2 horse=36.2 sheep=27.4 cow=28.0 elephant=42.2 bear=51.8 zebra=44.6 giraffe=47.8 backpack=2.8 umbrella=21.4 handbag=2.5 tie=12.2 suitcase=15.7 frisbee=28.2 skis=9.0 snowboard=9.7 sports ball=16.1 kite=15.4 baseball bat=10.0 baseball glove=11.1 skateboard=23.1 surfboard=14.8 tennis racket=24.0 bottle=10.7 wine glass=10.6 cup=17.3 fork=11.3 knife=4.1 spoon=4.0 bowl=21.7 banana=13.4 apple=9.3 sandwich=25.0 orange=18.2 broccoli=14.3 carrot=8.4 hot dog=19.5 pizza=34.5 donut=23.0 cake=19.0 chair=11.6 couch=28.9 potted plant=11.9 bed=32.6 dining table=20.3 toilet=42.5 tv=40.6 laptop=41.9 mouse=27.2 remote=6.2 keyboard=28.7 cell phone=15.1 microwave=32.3 oven=25.8 toaster=7.1 sink=19.6 refrigerator=34.3 book=3.6 clock=28.2 vase=14.7 scissors=19.1 teddy bear=28.6 hair drier=0.0 toothbrush=6.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.3 [Epoch 123][Batch 99], Speed: 349.815 samples/sec, CrossEntropy=2.523, SmoothL1=1.120 [Epoch 123][Batch 199], Speed: 348.139 samples/sec, CrossEntropy=2.502, SmoothL1=1.104 [Epoch 123][Batch 299], Speed: 350.780 samples/sec, CrossEntropy=2.507, SmoothL1=1.094 [Epoch 123][Batch 399], Speed: 365.778 samples/sec, CrossEntropy=2.524, SmoothL1=1.097 [Epoch 123][Batch 499], Speed: 351.308 samples/sec, CrossEntropy=2.520, SmoothL1=1.096 [Epoch 123][Batch 599], Speed: 351.843 samples/sec, CrossEntropy=2.519, SmoothL1=1.099 [Epoch 123][Batch 699], Speed: 346.787 samples/sec, CrossEntropy=2.518, SmoothL1=1.093 [Epoch 123][Batch 799], Speed: 361.995 samples/sec, CrossEntropy=2.519, SmoothL1=1.096 [Epoch 123][Batch 899], Speed: 358.194 samples/sec, CrossEntropy=2.523, SmoothL1=1.096 [Epoch 123][Batch 999], Speed: 349.754 samples/sec, CrossEntropy=2.524, SmoothL1=1.095 [Epoch 123][Batch 1099], Speed: 349.320 samples/sec, CrossEntropy=2.524, SmoothL1=1.095 [Epoch 123][Batch 1199], Speed: 355.693 samples/sec, CrossEntropy=2.525, SmoothL1=1.096 [Epoch 123][Batch 1299], Speed: 353.763 samples/sec, CrossEntropy=2.527, SmoothL1=1.099 [Epoch 123][Batch 1399], Speed: 352.334 samples/sec, CrossEntropy=2.526, SmoothL1=1.097 [Epoch 123][Batch 1499], Speed: 351.063 samples/sec, CrossEntropy=2.526, SmoothL1=1.096 [Epoch 123][Batch 1599], Speed: 351.422 samples/sec, CrossEntropy=2.528, SmoothL1=1.097 [Epoch 123][Batch 1699], Speed: 352.663 samples/sec, CrossEntropy=2.529, SmoothL1=1.096 [Epoch 123][Batch 1799], Speed: 361.091 samples/sec, CrossEntropy=2.529, SmoothL1=1.097 [Epoch 123] Training cost: 335.553, CrossEntropy=2.528, SmoothL1=1.097 [Epoch 123] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.380 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.236 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.383 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.210 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.303 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.315 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.532 person=32.1 bicycle=13.9 car=18.3 motorcycle=25.7 airplane=44.1 bus=43.5 train=48.4 truck=19.3 boat=9.7 traffic light=7.1 fire hydrant=41.9 stop sign=42.1 parking meter=26.3 bench=11.2 bird=13.9 cat=49.9 dog=42.1 horse=35.6 sheep=29.5 cow=27.6 elephant=42.7 bear=49.9 zebra=44.9 giraffe=45.2 backpack=3.1 umbrella=20.2 handbag=3.4 tie=11.7 suitcase=15.3 frisbee=26.9 skis=9.5 snowboard=9.6 sports ball=16.0 kite=14.9 baseball bat=9.2 baseball glove=11.7 skateboard=23.7 surfboard=16.0 tennis racket=23.6 bottle=11.6 wine glass=10.7 cup=17.4 fork=12.6 knife=5.0 spoon=4.4 bowl=22.8 banana=12.8 apple=9.7 sandwich=26.3 orange=16.8 broccoli=11.1 carrot=7.7 hot dog=20.1 pizza=29.8 donut=24.1 cake=18.1 chair=11.7 couch=28.4 potted plant=11.5 bed=28.4 dining table=21.0 toilet=42.0 tv=39.2 laptop=38.3 mouse=26.7 remote=5.9 keyboard=29.4 cell phone=14.6 microwave=30.7 oven=24.8 toaster=3.0 sink=18.9 refrigerator=34.1 book=3.3 clock=28.2 vase=15.0 scissors=14.9 teddy bear=29.1 hair drier=0.0 toothbrush=6.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.8 [Epoch 124][Batch 99], Speed: 346.606 samples/sec, CrossEntropy=2.487, SmoothL1=1.068 [Epoch 124][Batch 199], Speed: 359.044 samples/sec, CrossEntropy=2.505, SmoothL1=1.082 [Epoch 124][Batch 299], Speed: 357.560 samples/sec, CrossEntropy=2.519, SmoothL1=1.080 [Epoch 124][Batch 399], Speed: 353.270 samples/sec, CrossEntropy=2.513, SmoothL1=1.085 [Epoch 124][Batch 499], Speed: 361.865 samples/sec, CrossEntropy=2.506, SmoothL1=1.085 [Epoch 124][Batch 599], Speed: 338.949 samples/sec, CrossEntropy=2.506, SmoothL1=1.084 [Epoch 124][Batch 699], Speed: 358.432 samples/sec, CrossEntropy=2.510, SmoothL1=1.085 [Epoch 124][Batch 799], Speed: 353.832 samples/sec, CrossEntropy=2.510, SmoothL1=1.089 [Epoch 124][Batch 899], Speed: 355.017 samples/sec, CrossEntropy=2.508, SmoothL1=1.088 [Epoch 124][Batch 999], Speed: 357.263 samples/sec, CrossEntropy=2.506, SmoothL1=1.086 [Epoch 124][Batch 1099], Speed: 346.828 samples/sec, CrossEntropy=2.507, SmoothL1=1.085 [Epoch 124][Batch 1199], Speed: 355.438 samples/sec, CrossEntropy=2.514, SmoothL1=1.088 [Epoch 124][Batch 1299], Speed: 368.000 samples/sec, CrossEntropy=2.516, SmoothL1=1.091 [Epoch 124][Batch 1399], Speed: 362.230 samples/sec, CrossEntropy=2.518, SmoothL1=1.092 [Epoch 124][Batch 1499], Speed: 347.878 samples/sec, CrossEntropy=2.519, SmoothL1=1.091 [Epoch 124][Batch 1599], Speed: 345.317 samples/sec, CrossEntropy=2.520, SmoothL1=1.094 [Epoch 124][Batch 1699], Speed: 347.880 samples/sec, CrossEntropy=2.521, SmoothL1=1.093 [Epoch 124][Batch 1799], Speed: 358.498 samples/sec, CrossEntropy=2.518, SmoothL1=1.091 [Epoch 124] Training cost: 334.962, CrossEntropy=2.517, SmoothL1=1.091 [Epoch 124] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.380 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.228 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.236 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.390 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.211 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.317 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.065 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.534 person=32.0 bicycle=14.8 car=18.4 motorcycle=26.1 airplane=43.8 bus=46.5 train=48.5 truck=18.3 boat=10.3 traffic light=6.9 fire hydrant=39.6 stop sign=42.7 parking meter=25.8 bench=11.6 bird=13.8 cat=47.9 dog=40.8 horse=35.0 sheep=28.6 cow=28.1 elephant=42.3 bear=51.4 zebra=46.7 giraffe=45.3 backpack=3.1 umbrella=21.1 handbag=2.9 tie=13.3 suitcase=14.8 frisbee=27.2 skis=9.7 snowboard=10.0 sports ball=15.8 kite=14.8 baseball bat=9.4 baseball glove=11.3 skateboard=22.9 surfboard=16.4 tennis racket=23.6 bottle=10.6 wine glass=11.5 cup=16.5 fork=11.7 knife=4.5 spoon=4.2 bowl=23.1 banana=13.6 apple=10.2 sandwich=26.7 orange=18.9 broccoli=11.9 carrot=8.8 hot dog=21.6 pizza=34.2 donut=22.3 cake=18.4 chair=11.0 couch=31.6 potted plant=11.8 bed=30.7 dining table=19.7 toilet=41.5 tv=37.8 laptop=40.7 mouse=26.4 remote=5.7 keyboard=28.7 cell phone=15.6 microwave=32.4 oven=25.2 toaster=7.1 sink=19.5 refrigerator=34.4 book=3.3 clock=26.7 vase=14.1 scissors=16.8 teddy bear=31.2 hair drier=0.0 toothbrush=4.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.1 [Epoch 125][Batch 99], Speed: 361.660 samples/sec, CrossEntropy=2.582, SmoothL1=1.107 [Epoch 125][Batch 199], Speed: 344.703 samples/sec, CrossEntropy=2.540, SmoothL1=1.102 [Epoch 125][Batch 299], Speed: 356.191 samples/sec, CrossEntropy=2.529, SmoothL1=1.094 [Epoch 125][Batch 399], Speed: 350.349 samples/sec, CrossEntropy=2.522, SmoothL1=1.095 [Epoch 125][Batch 499], Speed: 352.895 samples/sec, CrossEntropy=2.527, SmoothL1=1.093 [Epoch 125][Batch 599], Speed: 339.359 samples/sec, CrossEntropy=2.516, SmoothL1=1.088 [Epoch 125][Batch 699], Speed: 353.163 samples/sec, CrossEntropy=2.520, SmoothL1=1.088 [Epoch 125][Batch 799], Speed: 349.033 samples/sec, CrossEntropy=2.517, SmoothL1=1.091 [Epoch 125][Batch 899], Speed: 350.107 samples/sec, CrossEntropy=2.521, SmoothL1=1.094 [Epoch 125][Batch 999], Speed: 346.730 samples/sec, CrossEntropy=2.525, SmoothL1=1.096 [Epoch 125][Batch 1099], Speed: 364.700 samples/sec, CrossEntropy=2.527, SmoothL1=1.097 [Epoch 125][Batch 1199], Speed: 357.342 samples/sec, CrossEntropy=2.526, SmoothL1=1.096 [Epoch 125][Batch 1299], Speed: 357.139 samples/sec, CrossEntropy=2.526, SmoothL1=1.092 [Epoch 125][Batch 1399], Speed: 356.055 samples/sec, CrossEntropy=2.525, SmoothL1=1.091 [Epoch 125][Batch 1499], Speed: 355.121 samples/sec, CrossEntropy=2.526, SmoothL1=1.091 [Epoch 125][Batch 1599], Speed: 348.568 samples/sec, CrossEntropy=2.527, SmoothL1=1.090 [Epoch 125][Batch 1699], Speed: 351.932 samples/sec, CrossEntropy=2.531, SmoothL1=1.093 [Epoch 125][Batch 1799], Speed: 349.292 samples/sec, CrossEntropy=2.531, SmoothL1=1.092 [Epoch 125] Training cost: 335.326, CrossEntropy=2.531, SmoothL1=1.092 [Epoch 125] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.220 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.382 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.228 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.041 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.233 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.387 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.213 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.306 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.318 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.070 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.350 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.528 person=31.7 bicycle=14.9 car=18.4 motorcycle=25.4 airplane=44.0 bus=45.2 train=46.9 truck=18.5 boat=10.1 traffic light=7.1 fire hydrant=41.4 stop sign=41.7 parking meter=25.2 bench=11.7 bird=13.2 cat=50.6 dog=41.4 horse=36.5 sheep=29.5 cow=28.5 elephant=42.1 bear=46.8 zebra=44.7 giraffe=45.1 backpack=3.0 umbrella=20.8 handbag=3.0 tie=11.9 suitcase=15.5 frisbee=28.0 skis=9.0 snowboard=9.7 sports ball=16.3 kite=14.2 baseball bat=9.6 baseball glove=12.1 skateboard=23.3 surfboard=16.7 tennis racket=22.6 bottle=11.4 wine glass=11.2 cup=17.3 fork=12.6 knife=4.4 spoon=3.8 bowl=21.6 banana=13.8 apple=8.0 sandwich=25.9 orange=19.3 broccoli=12.1 carrot=8.7 hot dog=19.7 pizza=35.3 donut=22.7 cake=19.9 chair=11.1 couch=31.5 potted plant=11.1 bed=34.0 dining table=20.2 toilet=43.2 tv=37.0 laptop=40.7 mouse=26.3 remote=5.5 keyboard=30.6 cell phone=14.5 microwave=29.5 oven=24.8 toaster=7.7 sink=17.6 refrigerator=34.1 book=4.1 clock=28.8 vase=15.5 scissors=13.2 teddy bear=28.5 hair drier=0.0 toothbrush=6.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.0 [Epoch 126][Batch 99], Speed: 348.704 samples/sec, CrossEntropy=2.474, SmoothL1=1.089 [Epoch 126][Batch 199], Speed: 356.491 samples/sec, CrossEntropy=2.514, SmoothL1=1.108 [Epoch 126][Batch 299], Speed: 362.339 samples/sec, CrossEntropy=2.513, SmoothL1=1.105 [Epoch 126][Batch 399], Speed: 348.105 samples/sec, CrossEntropy=2.519, SmoothL1=1.111 [Epoch 126][Batch 499], Speed: 347.261 samples/sec, CrossEntropy=2.510, SmoothL1=1.103 [Epoch 126][Batch 599], Speed: 345.634 samples/sec, CrossEntropy=2.508, SmoothL1=1.103 [Epoch 126][Batch 699], Speed: 355.661 samples/sec, CrossEntropy=2.505, SmoothL1=1.100 [Epoch 126][Batch 799], Speed: 350.378 samples/sec, CrossEntropy=2.508, SmoothL1=1.097 [Epoch 126][Batch 899], Speed: 360.176 samples/sec, CrossEntropy=2.508, SmoothL1=1.095 [Epoch 126][Batch 999], Speed: 358.142 samples/sec, CrossEntropy=2.514, SmoothL1=1.100 [Epoch 126][Batch 1099], Speed: 351.891 samples/sec, CrossEntropy=2.511, SmoothL1=1.099 [Epoch 126][Batch 1199], Speed: 344.320 samples/sec, CrossEntropy=2.514, SmoothL1=1.098 [Epoch 126][Batch 1299], Speed: 353.575 samples/sec, CrossEntropy=2.517, SmoothL1=1.098 [Epoch 126][Batch 1399], Speed: 359.441 samples/sec, CrossEntropy=2.519, SmoothL1=1.098 [Epoch 126][Batch 1499], Speed: 353.547 samples/sec, CrossEntropy=2.521, SmoothL1=1.098 [Epoch 126][Batch 1599], Speed: 355.851 samples/sec, CrossEntropy=2.522, SmoothL1=1.098 [Epoch 126][Batch 1699], Speed: 346.755 samples/sec, CrossEntropy=2.521, SmoothL1=1.097 [Epoch 126][Batch 1799], Speed: 349.888 samples/sec, CrossEntropy=2.521, SmoothL1=1.097 [Epoch 126] Training cost: 335.197, CrossEntropy=2.519, SmoothL1=1.095 [Epoch 126] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.383 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.041 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.234 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.383 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.213 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.305 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.318 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.350 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.529 person=32.4 bicycle=14.6 car=18.4 motorcycle=25.8 airplane=44.2 bus=46.5 train=47.8 truck=19.9 boat=9.1 traffic light=6.9 fire hydrant=39.2 stop sign=41.8 parking meter=28.1 bench=12.3 bird=13.8 cat=49.2 dog=44.3 horse=36.2 sheep=28.4 cow=28.9 elephant=41.1 bear=51.0 zebra=46.2 giraffe=45.8 backpack=2.4 umbrella=19.5 handbag=2.4 tie=11.8 suitcase=14.8 frisbee=27.3 skis=9.0 snowboard=8.1 sports ball=17.5 kite=14.2 baseball bat=9.9 baseball glove=12.1 skateboard=23.8 surfboard=16.2 tennis racket=23.2 bottle=11.4 wine glass=10.9 cup=17.5 fork=11.6 knife=4.3 spoon=3.8 bowl=21.8 banana=12.5 apple=8.3 sandwich=25.5 orange=18.9 broccoli=12.2 carrot=8.3 hot dog=19.6 pizza=34.0 donut=25.4 cake=18.4 chair=11.8 couch=30.8 potted plant=12.2 bed=32.9 dining table=20.1 toilet=40.6 tv=38.4 laptop=40.9 mouse=31.3 remote=5.5 keyboard=30.3 cell phone=15.3 microwave=33.0 oven=22.2 toaster=5.9 sink=18.5 refrigerator=34.6 book=3.6 clock=28.0 vase=15.9 scissors=15.8 teddy bear=28.7 hair drier=0.0 toothbrush=4.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.1 [Epoch 127][Batch 99], Speed: 361.847 samples/sec, CrossEntropy=2.499, SmoothL1=1.067 [Epoch 127][Batch 199], Speed: 358.633 samples/sec, CrossEntropy=2.508, SmoothL1=1.083 [Epoch 127][Batch 299], Speed: 351.567 samples/sec, CrossEntropy=2.505, SmoothL1=1.082 [Epoch 127][Batch 399], Speed: 361.964 samples/sec, CrossEntropy=2.509, SmoothL1=1.082 [Epoch 127][Batch 499], Speed: 350.943 samples/sec, CrossEntropy=2.515, SmoothL1=1.085 [Epoch 127][Batch 599], Speed: 354.031 samples/sec, CrossEntropy=2.519, SmoothL1=1.088 [Epoch 127][Batch 699], Speed: 344.017 samples/sec, CrossEntropy=2.521, SmoothL1=1.092 [Epoch 127][Batch 799], Speed: 356.150 samples/sec, CrossEntropy=2.520, SmoothL1=1.093 [Epoch 127][Batch 899], Speed: 361.644 samples/sec, CrossEntropy=2.520, SmoothL1=1.091 [Epoch 127][Batch 999], Speed: 350.606 samples/sec, CrossEntropy=2.524, SmoothL1=1.096 [Epoch 127][Batch 1099], Speed: 347.487 samples/sec, CrossEntropy=2.525, SmoothL1=1.098 [Epoch 127][Batch 1199], Speed: 358.191 samples/sec, CrossEntropy=2.525, SmoothL1=1.096 [Epoch 127][Batch 1299], Speed: 347.951 samples/sec, CrossEntropy=2.529, SmoothL1=1.096 [Epoch 127][Batch 1399], Speed: 362.958 samples/sec, CrossEntropy=2.526, SmoothL1=1.094 [Epoch 127][Batch 1499], Speed: 353.111 samples/sec, CrossEntropy=2.529, SmoothL1=1.097 [Epoch 127][Batch 1599], Speed: 355.327 samples/sec, CrossEntropy=2.530, SmoothL1=1.100 [Epoch 127][Batch 1699], Speed: 351.932 samples/sec, CrossEntropy=2.529, SmoothL1=1.098 [Epoch 127][Batch 1799], Speed: 347.208 samples/sec, CrossEntropy=2.524, SmoothL1=1.095 [Epoch 127] Training cost: 334.506, CrossEntropy=2.522, SmoothL1=1.094 [Epoch 127] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.378 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.038 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.228 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.383 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.213 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.317 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.062 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.534 person=32.2 bicycle=14.4 car=18.5 motorcycle=24.5 airplane=44.8 bus=44.6 train=48.4 truck=18.6 boat=9.1 traffic light=7.2 fire hydrant=37.4 stop sign=40.3 parking meter=24.8 bench=11.8 bird=14.0 cat=48.4 dog=41.0 horse=36.1 sheep=29.8 cow=25.7 elephant=43.0 bear=50.4 zebra=44.6 giraffe=44.5 backpack=2.7 umbrella=18.6 handbag=2.5 tie=10.0 suitcase=15.0 frisbee=26.9 skis=8.8 snowboard=9.3 sports ball=15.2 kite=13.3 baseball bat=10.4 baseball glove=13.4 skateboard=23.7 surfboard=16.8 tennis racket=24.1 bottle=10.8 wine glass=11.0 cup=17.0 fork=11.6 knife=4.0 spoon=4.6 bowl=22.3 banana=13.7 apple=7.3 sandwich=23.9 orange=19.4 broccoli=12.5 carrot=8.4 hot dog=20.0 pizza=33.4 donut=23.0 cake=19.9 chair=11.5 couch=29.5 potted plant=10.4 bed=33.1 dining table=21.1 toilet=39.8 tv=38.2 laptop=40.5 mouse=26.9 remote=5.0 keyboard=30.7 cell phone=15.1 microwave=33.3 oven=26.8 toaster=2.5 sink=17.5 refrigerator=35.1 book=3.7 clock=27.3 vase=14.6 scissors=17.8 teddy bear=28.7 hair drier=0.0 toothbrush=5.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.8 [Epoch 128][Batch 99], Speed: 358.789 samples/sec, CrossEntropy=2.508, SmoothL1=1.072 [Epoch 128][Batch 199], Speed: 350.999 samples/sec, CrossEntropy=2.475, SmoothL1=1.083 [Epoch 128][Batch 299], Speed: 350.621 samples/sec, CrossEntropy=2.484, SmoothL1=1.080 [Epoch 128][Batch 399], Speed: 351.731 samples/sec, CrossEntropy=2.497, SmoothL1=1.084 [Epoch 128][Batch 499], Speed: 346.591 samples/sec, CrossEntropy=2.489, SmoothL1=1.081 [Epoch 128][Batch 599], Speed: 348.728 samples/sec, CrossEntropy=2.495, SmoothL1=1.089 [Epoch 128][Batch 699], Speed: 362.998 samples/sec, CrossEntropy=2.500, SmoothL1=1.088 [Epoch 128][Batch 799], Speed: 355.960 samples/sec, CrossEntropy=2.506, SmoothL1=1.094 [Epoch 128][Batch 899], Speed: 353.786 samples/sec, CrossEntropy=2.506, SmoothL1=1.096 [Epoch 128][Batch 999], Speed: 348.865 samples/sec, CrossEntropy=2.510, SmoothL1=1.098 [Epoch 128][Batch 1099], Speed: 347.866 samples/sec, CrossEntropy=2.514, SmoothL1=1.098 [Epoch 128][Batch 1199], Speed: 346.543 samples/sec, CrossEntropy=2.516, SmoothL1=1.098 [Epoch 128][Batch 1299], Speed: 357.262 samples/sec, CrossEntropy=2.513, SmoothL1=1.094 [Epoch 128][Batch 1399], Speed: 345.806 samples/sec, CrossEntropy=2.516, SmoothL1=1.095 [Epoch 128][Batch 1499], Speed: 358.541 samples/sec, CrossEntropy=2.518, SmoothL1=1.095 [Epoch 128][Batch 1599], Speed: 358.251 samples/sec, CrossEntropy=2.519, SmoothL1=1.095 [Epoch 128][Batch 1699], Speed: 363.666 samples/sec, CrossEntropy=2.518, SmoothL1=1.094 [Epoch 128][Batch 1799], Speed: 345.500 samples/sec, CrossEntropy=2.516, SmoothL1=1.094 [Epoch 128] Training cost: 335.695, CrossEntropy=2.517, SmoothL1=1.094 [Epoch 128] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.384 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.232 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.039 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.235 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.391 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.212 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.306 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.318 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.066 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.538 person=32.3 bicycle=15.8 car=18.4 motorcycle=24.9 airplane=45.0 bus=45.9 train=47.7 truck=17.2 boat=10.4 traffic light=6.2 fire hydrant=37.6 stop sign=42.4 parking meter=26.9 bench=11.6 bird=14.4 cat=48.0 dog=40.2 horse=37.1 sheep=31.3 cow=27.9 elephant=44.7 bear=51.3 zebra=46.8 giraffe=46.5 backpack=3.5 umbrella=20.7 handbag=2.8 tie=11.9 suitcase=16.4 frisbee=26.6 skis=9.8 snowboard=10.3 sports ball=15.7 kite=14.4 baseball bat=9.0 baseball glove=11.8 skateboard=23.5 surfboard=16.2 tennis racket=23.2 bottle=11.0 wine glass=11.5 cup=16.7 fork=12.0 knife=4.1 spoon=5.2 bowl=23.3 banana=12.8 apple=8.0 sandwich=24.4 orange=18.9 broccoli=14.6 carrot=9.1 hot dog=19.8 pizza=31.7 donut=22.4 cake=18.5 chair=12.2 couch=29.4 potted plant=11.3 bed=34.6 dining table=21.1 toilet=41.1 tv=39.2 laptop=39.1 mouse=28.3 remote=6.4 keyboard=30.9 cell phone=14.9 microwave=30.4 oven=25.1 toaster=2.4 sink=20.2 refrigerator=34.6 book=3.3 clock=28.3 vase=15.1 scissors=17.9 teddy bear=28.7 hair drier=0.0 toothbrush=5.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.1 [Epoch 129][Batch 99], Speed: 350.158 samples/sec, CrossEntropy=2.516, SmoothL1=1.122 [Epoch 129][Batch 199], Speed: 349.381 samples/sec, CrossEntropy=2.502, SmoothL1=1.080 [Epoch 129][Batch 299], Speed: 351.112 samples/sec, CrossEntropy=2.494, SmoothL1=1.065 [Epoch 129][Batch 399], Speed: 350.741 samples/sec, CrossEntropy=2.498, SmoothL1=1.066 [Epoch 129][Batch 499], Speed: 351.888 samples/sec, CrossEntropy=2.499, SmoothL1=1.074 [Epoch 129][Batch 599], Speed: 355.651 samples/sec, CrossEntropy=2.500, SmoothL1=1.072 [Epoch 129][Batch 699], Speed: 346.164 samples/sec, CrossEntropy=2.503, SmoothL1=1.075 [Epoch 129][Batch 799], Speed: 349.287 samples/sec, CrossEntropy=2.506, SmoothL1=1.075 [Epoch 129][Batch 899], Speed: 356.647 samples/sec, CrossEntropy=2.505, SmoothL1=1.079 [Epoch 129][Batch 999], Speed: 350.850 samples/sec, CrossEntropy=2.506, SmoothL1=1.081 [Epoch 129][Batch 1099], Speed: 359.712 samples/sec, CrossEntropy=2.507, SmoothL1=1.082 [Epoch 129][Batch 1199], Speed: 353.481 samples/sec, CrossEntropy=2.509, SmoothL1=1.085 [Epoch 129][Batch 1299], Speed: 346.854 samples/sec, CrossEntropy=2.514, SmoothL1=1.084 [Epoch 129][Batch 1399], Speed: 351.172 samples/sec, CrossEntropy=2.510, SmoothL1=1.084 [Epoch 129][Batch 1499], Speed: 349.287 samples/sec, CrossEntropy=2.511, SmoothL1=1.084 [Epoch 129][Batch 1599], Speed: 361.111 samples/sec, CrossEntropy=2.510, SmoothL1=1.085 [Epoch 129][Batch 1699], Speed: 343.246 samples/sec, CrossEntropy=2.509, SmoothL1=1.085 [Epoch 129][Batch 1799], Speed: 351.834 samples/sec, CrossEntropy=2.506, SmoothL1=1.082 [Epoch 129] Training cost: 335.108, CrossEntropy=2.506, SmoothL1=1.082 [Epoch 129] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.222 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.383 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.039 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.232 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.389 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.317 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.068 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.340 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.535 person=31.9 bicycle=15.1 car=17.5 motorcycle=24.9 airplane=43.5 bus=44.8 train=48.3 truck=20.2 boat=9.3 traffic light=6.5 fire hydrant=40.1 stop sign=42.7 parking meter=27.2 bench=11.2 bird=14.5 cat=47.1 dog=40.8 horse=36.6 sheep=29.7 cow=28.5 elephant=40.9 bear=54.5 zebra=44.9 giraffe=45.7 backpack=3.1 umbrella=20.0 handbag=2.8 tie=13.0 suitcase=15.4 frisbee=26.4 skis=9.2 snowboard=9.1 sports ball=15.2 kite=15.4 baseball bat=10.6 baseball glove=10.8 skateboard=25.0 surfboard=16.3 tennis racket=22.9 bottle=10.3 wine glass=11.4 cup=16.6 fork=12.3 knife=3.5 spoon=3.4 bowl=23.4 banana=13.2 apple=8.5 sandwich=21.2 orange=18.7 broccoli=13.3 carrot=8.2 hot dog=19.2 pizza=34.5 donut=23.8 cake=17.7 chair=11.4 couch=32.2 potted plant=11.9 bed=34.1 dining table=21.0 toilet=43.8 tv=39.6 laptop=40.4 mouse=26.5 remote=6.2 keyboard=29.2 cell phone=15.1 microwave=32.9 oven=24.6 toaster=5.9 sink=21.5 refrigerator=36.2 book=3.4 clock=27.8 vase=14.9 scissors=20.4 teddy bear=28.8 hair drier=0.0 toothbrush=5.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.2 [Epoch 130][Batch 99], Speed: 360.028 samples/sec, CrossEntropy=2.474, SmoothL1=1.065 [Epoch 130][Batch 199], Speed: 362.662 samples/sec, CrossEntropy=2.488, SmoothL1=1.083 [Epoch 130][Batch 299], Speed: 359.476 samples/sec, CrossEntropy=2.460, SmoothL1=1.076 [Epoch 130][Batch 399], Speed: 359.903 samples/sec, CrossEntropy=2.467, SmoothL1=1.073 [Epoch 130][Batch 499], Speed: 342.422 samples/sec, CrossEntropy=2.471, SmoothL1=1.072 [Epoch 130][Batch 599], Speed: 349.896 samples/sec, CrossEntropy=2.477, SmoothL1=1.073 [Epoch 130][Batch 699], Speed: 352.618 samples/sec, CrossEntropy=2.482, SmoothL1=1.077 [Epoch 130][Batch 799], Speed: 350.874 samples/sec, CrossEntropy=2.482, SmoothL1=1.075 [Epoch 130][Batch 899], Speed: 347.740 samples/sec, CrossEntropy=2.484, SmoothL1=1.073 [Epoch 130][Batch 999], Speed: 352.757 samples/sec, CrossEntropy=2.485, SmoothL1=1.073 [Epoch 130][Batch 1099], Speed: 343.879 samples/sec, CrossEntropy=2.490, SmoothL1=1.075 [Epoch 130][Batch 1199], Speed: 349.019 samples/sec, CrossEntropy=2.487, SmoothL1=1.074 [Epoch 130][Batch 1299], Speed: 346.837 samples/sec, CrossEntropy=2.488, SmoothL1=1.075 [Epoch 130][Batch 1399], Speed: 349.063 samples/sec, CrossEntropy=2.490, SmoothL1=1.076 [Epoch 130][Batch 1499], Speed: 362.088 samples/sec, CrossEntropy=2.493, SmoothL1=1.077 [Epoch 130][Batch 1599], Speed: 350.473 samples/sec, CrossEntropy=2.494, SmoothL1=1.079 [Epoch 130][Batch 1699], Speed: 366.060 samples/sec, CrossEntropy=2.495, SmoothL1=1.079 [Epoch 130][Batch 1799], Speed: 360.158 samples/sec, CrossEntropy=2.495, SmoothL1=1.079 [Epoch 130] Training cost: 334.578, CrossEntropy=2.495, SmoothL1=1.079 [Epoch 130] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.218 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.378 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.038 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.391 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.210 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.302 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.314 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.066 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.337 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.544 person=32.1 bicycle=15.4 car=18.2 motorcycle=25.9 airplane=41.9 bus=45.2 train=47.0 truck=18.1 boat=9.3 traffic light=7.4 fire hydrant=38.8 stop sign=41.4 parking meter=27.2 bench=11.5 bird=13.8 cat=46.9 dog=42.7 horse=35.5 sheep=29.7 cow=28.4 elephant=41.1 bear=45.6 zebra=45.2 giraffe=43.8 backpack=2.9 umbrella=20.3 handbag=2.1 tie=11.4 suitcase=15.8 frisbee=26.3 skis=9.6 snowboard=10.1 sports ball=15.1 kite=14.1 baseball bat=9.0 baseball glove=11.4 skateboard=24.8 surfboard=16.5 tennis racket=23.8 bottle=11.0 wine glass=11.3 cup=17.1 fork=13.4 knife=4.0 spoon=4.4 bowl=23.6 banana=14.0 apple=8.8 sandwich=25.4 orange=18.1 broccoli=12.4 carrot=8.9 hot dog=19.7 pizza=33.8 donut=25.1 cake=17.7 chair=10.8 couch=27.6 potted plant=12.3 bed=30.7 dining table=19.5 toilet=39.7 tv=38.3 laptop=39.2 mouse=26.0 remote=5.3 keyboard=30.6 cell phone=15.0 microwave=29.2 oven=23.2 toaster=4.6 sink=18.7 refrigerator=32.9 book=3.9 clock=27.3 vase=14.6 scissors=22.7 teddy bear=29.3 hair drier=0.0 toothbrush=4.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.8 [Epoch 131][Batch 99], Speed: 350.665 samples/sec, CrossEntropy=2.449, SmoothL1=1.042 [Epoch 131][Batch 199], Speed: 357.806 samples/sec, CrossEntropy=2.495, SmoothL1=1.077 [Epoch 131][Batch 299], Speed: 341.981 samples/sec, CrossEntropy=2.505, SmoothL1=1.088 [Epoch 131][Batch 399], Speed: 346.514 samples/sec, CrossEntropy=2.516, SmoothL1=1.094 [Epoch 131][Batch 499], Speed: 358.045 samples/sec, CrossEntropy=2.512, SmoothL1=1.092 [Epoch 131][Batch 599], Speed: 353.855 samples/sec, CrossEntropy=2.510, SmoothL1=1.092 [Epoch 131][Batch 699], Speed: 344.670 samples/sec, CrossEntropy=2.510, SmoothL1=1.092 [Epoch 131][Batch 799], Speed: 356.326 samples/sec, CrossEntropy=2.508, SmoothL1=1.089 [Epoch 131][Batch 899], Speed: 347.790 samples/sec, CrossEntropy=2.507, SmoothL1=1.088 [Epoch 131][Batch 999], Speed: 346.190 samples/sec, CrossEntropy=2.512, SmoothL1=1.085 [Epoch 131][Batch 1099], Speed: 357.887 samples/sec, CrossEntropy=2.510, SmoothL1=1.083 [Epoch 131][Batch 1199], Speed: 347.835 samples/sec, CrossEntropy=2.513, SmoothL1=1.083 [Epoch 131][Batch 1299], Speed: 360.062 samples/sec, CrossEntropy=2.515, SmoothL1=1.084 [Epoch 131][Batch 1399], Speed: 351.506 samples/sec, CrossEntropy=2.516, SmoothL1=1.087 [Epoch 131][Batch 1499], Speed: 352.644 samples/sec, CrossEntropy=2.514, SmoothL1=1.087 [Epoch 131][Batch 1599], Speed: 352.389 samples/sec, CrossEntropy=2.513, SmoothL1=1.085 [Epoch 131][Batch 1699], Speed: 359.039 samples/sec, CrossEntropy=2.511, SmoothL1=1.083 [Epoch 131][Batch 1799], Speed: 344.180 samples/sec, CrossEntropy=2.510, SmoothL1=1.081 [Epoch 131] Training cost: 335.952, CrossEntropy=2.511, SmoothL1=1.081 [Epoch 131] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.385 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.229 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.042 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.233 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.391 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.213 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.306 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.319 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.068 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.538 person=32.4 bicycle=15.3 car=18.3 motorcycle=26.3 airplane=41.4 bus=46.3 train=48.0 truck=18.7 boat=10.3 traffic light=7.0 fire hydrant=39.7 stop sign=42.2 parking meter=25.5 bench=12.1 bird=13.8 cat=47.8 dog=42.7 horse=36.4 sheep=29.2 cow=26.2 elephant=41.9 bear=50.7 zebra=45.7 giraffe=46.7 backpack=2.5 umbrella=20.4 handbag=3.1 tie=12.7 suitcase=16.2 frisbee=27.7 skis=9.8 snowboard=9.3 sports ball=16.5 kite=13.6 baseball bat=9.7 baseball glove=12.6 skateboard=23.4 surfboard=16.2 tennis racket=24.3 bottle=11.4 wine glass=11.6 cup=17.1 fork=13.6 knife=3.9 spoon=5.1 bowl=23.0 banana=13.2 apple=6.5 sandwich=26.9 orange=17.7 broccoli=12.0 carrot=10.0 hot dog=19.8 pizza=31.9 donut=24.1 cake=17.0 chair=11.8 couch=27.8 potted plant=12.0 bed=28.5 dining table=21.3 toilet=44.6 tv=40.0 laptop=39.9 mouse=26.9 remote=6.1 keyboard=29.8 cell phone=15.2 microwave=32.6 oven=25.1 toaster=5.0 sink=19.5 refrigerator=36.6 book=3.4 clock=28.4 vase=15.2 scissors=14.5 teddy bear=28.6 hair drier=0.0 toothbrush=6.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.1 [Epoch 132][Batch 99], Speed: 357.045 samples/sec, CrossEntropy=2.490, SmoothL1=1.057 [Epoch 132][Batch 199], Speed: 349.513 samples/sec, CrossEntropy=2.469, SmoothL1=1.053 [Epoch 132][Batch 299], Speed: 349.458 samples/sec, CrossEntropy=2.483, SmoothL1=1.070 [Epoch 132][Batch 399], Speed: 348.641 samples/sec, CrossEntropy=2.497, SmoothL1=1.085 [Epoch 132][Batch 499], Speed: 349.409 samples/sec, CrossEntropy=2.494, SmoothL1=1.081 [Epoch 132][Batch 599], Speed: 355.556 samples/sec, CrossEntropy=2.495, SmoothL1=1.085 [Epoch 132][Batch 699], Speed: 349.834 samples/sec, CrossEntropy=2.497, SmoothL1=1.084 [Epoch 132][Batch 799], Speed: 352.826 samples/sec, CrossEntropy=2.496, SmoothL1=1.086 [Epoch 132][Batch 899], Speed: 357.950 samples/sec, CrossEntropy=2.496, SmoothL1=1.087 [Epoch 132][Batch 999], Speed: 354.849 samples/sec, CrossEntropy=2.499, SmoothL1=1.085 [Epoch 132][Batch 1099], Speed: 349.749 samples/sec, CrossEntropy=2.503, SmoothL1=1.087 [Epoch 132][Batch 1199], Speed: 349.258 samples/sec, CrossEntropy=2.501, SmoothL1=1.085 [Epoch 132][Batch 1299], Speed: 358.196 samples/sec, CrossEntropy=2.505, SmoothL1=1.084 [Epoch 132][Batch 1399], Speed: 350.223 samples/sec, CrossEntropy=2.506, SmoothL1=1.084 [Epoch 132][Batch 1499], Speed: 351.799 samples/sec, CrossEntropy=2.508, SmoothL1=1.085 [Epoch 132][Batch 1599], Speed: 351.426 samples/sec, CrossEntropy=2.505, SmoothL1=1.083 [Epoch 132][Batch 1699], Speed: 358.700 samples/sec, CrossEntropy=2.506, SmoothL1=1.085 [Epoch 132][Batch 1799], Speed: 350.752 samples/sec, CrossEntropy=2.503, SmoothL1=1.084 [Epoch 132] Training cost: 335.428, CrossEntropy=2.503, SmoothL1=1.084 [Epoch 132] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.226 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.390 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.237 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.042 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.240 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.393 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.217 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.312 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.325 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.070 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.357 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.539 person=32.3 bicycle=15.7 car=18.5 motorcycle=24.7 airplane=43.9 bus=47.1 train=50.7 truck=19.6 boat=10.6 traffic light=7.1 fire hydrant=40.2 stop sign=44.8 parking meter=27.3 bench=11.6 bird=14.3 cat=48.2 dog=42.7 horse=34.3 sheep=29.4 cow=27.9 elephant=43.8 bear=52.3 zebra=46.5 giraffe=47.0 backpack=2.9 umbrella=20.1 handbag=2.9 tie=12.7 suitcase=16.1 frisbee=27.7 skis=9.0 snowboard=10.8 sports ball=16.3 kite=15.1 baseball bat=11.0 baseball glove=11.1 skateboard=23.9 surfboard=17.3 tennis racket=23.9 bottle=11.0 wine glass=11.0 cup=17.6 fork=13.8 knife=4.4 spoon=3.9 bowl=22.2 banana=12.5 apple=8.2 sandwich=28.0 orange=17.4 broccoli=14.3 carrot=8.8 hot dog=21.6 pizza=33.7 donut=23.8 cake=19.1 chair=11.5 couch=31.8 potted plant=12.1 bed=31.7 dining table=20.6 toilet=41.3 tv=39.7 laptop=41.0 mouse=29.7 remote=6.1 keyboard=28.6 cell phone=14.6 microwave=35.2 oven=24.1 toaster=8.4 sink=20.9 refrigerator=34.0 book=4.0 clock=28.4 vase=15.1 scissors=19.7 teddy bear=30.0 hair drier=0.0 toothbrush=6.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.6 [Epoch 133][Batch 99], Speed: 350.154 samples/sec, CrossEntropy=2.521, SmoothL1=1.089 [Epoch 133][Batch 199], Speed: 347.166 samples/sec, CrossEntropy=2.491, SmoothL1=1.098 [Epoch 133][Batch 299], Speed: 357.263 samples/sec, CrossEntropy=2.501, SmoothL1=1.106 [Epoch 133][Batch 399], Speed: 355.661 samples/sec, CrossEntropy=2.513, SmoothL1=1.106 [Epoch 133][Batch 499], Speed: 350.003 samples/sec, CrossEntropy=2.505, SmoothL1=1.096 [Epoch 133][Batch 599], Speed: 355.414 samples/sec, CrossEntropy=2.503, SmoothL1=1.094 [Epoch 133][Batch 699], Speed: 350.072 samples/sec, CrossEntropy=2.508, SmoothL1=1.093 [Epoch 133][Batch 799], Speed: 354.587 samples/sec, CrossEntropy=2.506, SmoothL1=1.090 [Epoch 133][Batch 899], Speed: 351.209 samples/sec, CrossEntropy=2.508, SmoothL1=1.092 [Epoch 133][Batch 999], Speed: 347.612 samples/sec, CrossEntropy=2.512, SmoothL1=1.093 [Epoch 133][Batch 1099], Speed: 363.443 samples/sec, CrossEntropy=2.515, SmoothL1=1.095 [Epoch 133][Batch 1199], Speed: 357.928 samples/sec, CrossEntropy=2.512, SmoothL1=1.092 [Epoch 133][Batch 1299], Speed: 351.581 samples/sec, CrossEntropy=2.511, SmoothL1=1.090 [Epoch 133][Batch 1399], Speed: 352.834 samples/sec, CrossEntropy=2.510, SmoothL1=1.089 [Epoch 133][Batch 1499], Speed: 362.944 samples/sec, CrossEntropy=2.510, SmoothL1=1.089 [Epoch 133][Batch 1599], Speed: 352.532 samples/sec, CrossEntropy=2.513, SmoothL1=1.089 [Epoch 133][Batch 1699], Speed: 344.182 samples/sec, CrossEntropy=2.511, SmoothL1=1.089 [Epoch 133][Batch 1799], Speed: 355.254 samples/sec, CrossEntropy=2.511, SmoothL1=1.090 [Epoch 133] Training cost: 335.408, CrossEntropy=2.510, SmoothL1=1.090 [Epoch 133] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.387 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.239 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.042 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.242 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.396 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.217 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.312 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.325 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.071 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.360 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.535 person=32.8 bicycle=16.0 car=18.8 motorcycle=26.1 airplane=43.0 bus=46.9 train=48.6 truck=20.0 boat=9.8 traffic light=7.7 fire hydrant=42.0 stop sign=44.1 parking meter=28.0 bench=11.8 bird=13.4 cat=50.8 dog=42.9 horse=38.9 sheep=31.2 cow=29.4 elephant=44.1 bear=52.3 zebra=46.8 giraffe=49.0 backpack=3.0 umbrella=20.1 handbag=3.0 tie=12.0 suitcase=17.3 frisbee=27.5 skis=10.0 snowboard=10.0 sports ball=16.2 kite=15.5 baseball bat=8.8 baseball glove=11.9 skateboard=23.8 surfboard=16.4 tennis racket=23.0 bottle=11.3 wine glass=11.8 cup=17.6 fork=12.8 knife=4.5 spoon=4.4 bowl=22.8 banana=12.4 apple=9.1 sandwich=26.0 orange=18.7 broccoli=13.3 carrot=9.4 hot dog=21.5 pizza=31.6 donut=23.5 cake=18.5 chair=12.2 couch=30.2 potted plant=12.6 bed=32.4 dining table=20.1 toilet=43.2 tv=40.6 laptop=41.9 mouse=28.0 remote=6.5 keyboard=31.2 cell phone=16.2 microwave=32.6 oven=25.2 toaster=3.3 sink=21.5 refrigerator=36.5 book=4.1 clock=28.6 vase=17.0 scissors=14.9 teddy bear=31.2 hair drier=0.0 toothbrush=4.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.7 [Epoch 134][Batch 99], Speed: 346.698 samples/sec, CrossEntropy=2.491, SmoothL1=1.074 [Epoch 134][Batch 199], Speed: 358.070 samples/sec, CrossEntropy=2.505, SmoothL1=1.077 [Epoch 134][Batch 299], Speed: 348.732 samples/sec, CrossEntropy=2.499, SmoothL1=1.079 [Epoch 134][Batch 399], Speed: 344.407 samples/sec, CrossEntropy=2.500, SmoothL1=1.085 [Epoch 134][Batch 499], Speed: 356.104 samples/sec, CrossEntropy=2.503, SmoothL1=1.087 [Epoch 134][Batch 599], Speed: 352.121 samples/sec, CrossEntropy=2.508, SmoothL1=1.087 [Epoch 134][Batch 699], Speed: 352.990 samples/sec, CrossEntropy=2.513, SmoothL1=1.090 [Epoch 134][Batch 799], Speed: 341.648 samples/sec, CrossEntropy=2.511, SmoothL1=1.093 [Epoch 134][Batch 899], Speed: 345.193 samples/sec, CrossEntropy=2.511, SmoothL1=1.089 [Epoch 134][Batch 999], Speed: 350.681 samples/sec, CrossEntropy=2.508, SmoothL1=1.090 [Epoch 134][Batch 1099], Speed: 343.087 samples/sec, CrossEntropy=2.511, SmoothL1=1.090 [Epoch 134][Batch 1199], Speed: 353.708 samples/sec, CrossEntropy=2.507, SmoothL1=1.089 [Epoch 134][Batch 1299], Speed: 348.532 samples/sec, CrossEntropy=2.508, SmoothL1=1.088 [Epoch 134][Batch 1399], Speed: 350.217 samples/sec, CrossEntropy=2.509, SmoothL1=1.089 [Epoch 134][Batch 1499], Speed: 344.937 samples/sec, CrossEntropy=2.511, SmoothL1=1.089 [Epoch 134][Batch 1599], Speed: 345.938 samples/sec, CrossEntropy=2.510, SmoothL1=1.089 [Epoch 134][Batch 1699], Speed: 335.887 samples/sec, CrossEntropy=2.509, SmoothL1=1.090 [Epoch 134][Batch 1799], Speed: 348.466 samples/sec, CrossEntropy=2.510, SmoothL1=1.090 [Epoch 134] Training cost: 335.993, CrossEntropy=2.509, SmoothL1=1.089 [Epoch 134] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.226 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.389 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.234 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.042 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.236 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.396 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.217 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.311 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.323 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.073 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.351 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.535 person=32.6 bicycle=15.3 car=17.9 motorcycle=25.8 airplane=42.8 bus=46.2 train=48.2 truck=18.2 boat=9.7 traffic light=7.0 fire hydrant=42.0 stop sign=44.4 parking meter=28.8 bench=12.2 bird=13.8 cat=50.5 dog=42.0 horse=36.8 sheep=28.8 cow=29.9 elephant=42.9 bear=51.8 zebra=46.4 giraffe=47.8 backpack=3.4 umbrella=21.2 handbag=2.7 tie=11.7 suitcase=16.8 frisbee=28.3 skis=10.0 snowboard=10.3 sports ball=16.8 kite=15.3 baseball bat=10.7 baseball glove=10.3 skateboard=23.7 surfboard=17.1 tennis racket=24.7 bottle=11.6 wine glass=11.3 cup=17.6 fork=12.1 knife=4.3 spoon=4.4 bowl=22.8 banana=12.3 apple=10.0 sandwich=24.6 orange=19.4 broccoli=12.4 carrot=9.8 hot dog=17.3 pizza=34.1 donut=23.7 cake=18.6 chair=11.6 couch=28.5 potted plant=13.6 bed=34.1 dining table=20.0 toilet=43.0 tv=39.3 laptop=40.8 mouse=28.2 remote=5.8 keyboard=31.6 cell phone=16.1 microwave=35.4 oven=24.6 toaster=6.4 sink=22.0 refrigerator=36.6 book=3.9 clock=28.8 vase=15.1 scissors=16.7 teddy bear=31.5 hair drier=0.0 toothbrush=6.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.6 [Epoch 135][Batch 99], Speed: 347.170 samples/sec, CrossEntropy=2.501, SmoothL1=1.092 [Epoch 135][Batch 199], Speed: 362.987 samples/sec, CrossEntropy=2.532, SmoothL1=1.117 [Epoch 135][Batch 299], Speed: 359.809 samples/sec, CrossEntropy=2.512, SmoothL1=1.107 [Epoch 135][Batch 399], Speed: 349.299 samples/sec, CrossEntropy=2.510, SmoothL1=1.104 [Epoch 135][Batch 499], Speed: 349.699 samples/sec, CrossEntropy=2.507, SmoothL1=1.101 [Epoch 135][Batch 599], Speed: 360.032 samples/sec, CrossEntropy=2.510, SmoothL1=1.099 [Epoch 135][Batch 699], Speed: 350.503 samples/sec, CrossEntropy=2.510, SmoothL1=1.095 [Epoch 135][Batch 799], Speed: 347.309 samples/sec, CrossEntropy=2.506, SmoothL1=1.092 [Epoch 135][Batch 899], Speed: 348.441 samples/sec, CrossEntropy=2.505, SmoothL1=1.092 [Epoch 135][Batch 999], Speed: 350.949 samples/sec, CrossEntropy=2.505, SmoothL1=1.094 [Epoch 135][Batch 1099], Speed: 350.218 samples/sec, CrossEntropy=2.507, SmoothL1=1.094 [Epoch 135][Batch 1199], Speed: 351.402 samples/sec, CrossEntropy=2.508, SmoothL1=1.094 [Epoch 135][Batch 1299], Speed: 360.394 samples/sec, CrossEntropy=2.506, SmoothL1=1.092 [Epoch 135][Batch 1399], Speed: 359.234 samples/sec, CrossEntropy=2.508, SmoothL1=1.092 [Epoch 135][Batch 1499], Speed: 354.736 samples/sec, CrossEntropy=2.510, SmoothL1=1.093 [Epoch 135][Batch 1599], Speed: 360.943 samples/sec, CrossEntropy=2.509, SmoothL1=1.090 [Epoch 135][Batch 1699], Speed: 346.752 samples/sec, CrossEntropy=2.509, SmoothL1=1.090 [Epoch 135][Batch 1799], Speed: 362.286 samples/sec, CrossEntropy=2.507, SmoothL1=1.089 [Epoch 135] Training cost: 334.226, CrossEntropy=2.508, SmoothL1=1.090 [Epoch 135] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.224 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.385 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.041 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.398 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.215 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.306 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.318 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.068 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.343 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.538 person=32.0 bicycle=16.2 car=18.8 motorcycle=25.0 airplane=43.0 bus=47.5 train=49.3 truck=18.8 boat=9.4 traffic light=6.5 fire hydrant=43.1 stop sign=43.8 parking meter=27.4 bench=11.6 bird=14.1 cat=49.5 dog=41.8 horse=36.2 sheep=27.5 cow=28.2 elephant=43.1 bear=47.7 zebra=46.7 giraffe=47.0 backpack=3.5 umbrella=20.5 handbag=2.1 tie=12.1 suitcase=14.9 frisbee=29.2 skis=9.9 snowboard=10.9 sports ball=17.7 kite=14.7 baseball bat=10.5 baseball glove=12.7 skateboard=24.7 surfboard=16.4 tennis racket=24.3 bottle=10.7 wine glass=12.4 cup=17.4 fork=10.8 knife=4.1 spoon=4.9 bowl=23.4 banana=14.2 apple=9.3 sandwich=25.7 orange=18.9 broccoli=14.3 carrot=8.0 hot dog=17.0 pizza=33.0 donut=22.5 cake=17.5 chair=10.6 couch=30.9 potted plant=11.9 bed=32.2 dining table=19.8 toilet=44.4 tv=39.8 laptop=42.2 mouse=28.0 remote=5.4 keyboard=32.0 cell phone=14.9 microwave=33.2 oven=24.5 toaster=3.0 sink=21.4 refrigerator=33.4 book=3.7 clock=27.8 vase=14.5 scissors=17.3 teddy bear=28.8 hair drier=0.0 toothbrush=6.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.4 [Epoch 136][Batch 99], Speed: 346.629 samples/sec, CrossEntropy=2.492, SmoothL1=1.069 [Epoch 136][Batch 199], Speed: 349.605 samples/sec, CrossEntropy=2.507, SmoothL1=1.084 [Epoch 136][Batch 299], Speed: 347.142 samples/sec, CrossEntropy=2.498, SmoothL1=1.083 [Epoch 136][Batch 399], Speed: 360.149 samples/sec, CrossEntropy=2.486, SmoothL1=1.077 [Epoch 136][Batch 499], Speed: 343.554 samples/sec, CrossEntropy=2.492, SmoothL1=1.074 [Epoch 136][Batch 599], Speed: 350.361 samples/sec, CrossEntropy=2.491, SmoothL1=1.075 [Epoch 136][Batch 699], Speed: 363.160 samples/sec, CrossEntropy=2.491, SmoothL1=1.075 [Epoch 136][Batch 799], Speed: 347.524 samples/sec, CrossEntropy=2.491, SmoothL1=1.078 [Epoch 136][Batch 899], Speed: 361.334 samples/sec, CrossEntropy=2.493, SmoothL1=1.079 [Epoch 136][Batch 999], Speed: 351.741 samples/sec, CrossEntropy=2.495, SmoothL1=1.077 [Epoch 136][Batch 1099], Speed: 356.933 samples/sec, CrossEntropy=2.502, SmoothL1=1.083 [Epoch 136][Batch 1199], Speed: 351.307 samples/sec, CrossEntropy=2.500, SmoothL1=1.083 [Epoch 136][Batch 1299], Speed: 366.296 samples/sec, CrossEntropy=2.497, SmoothL1=1.080 [Epoch 136][Batch 1399], Speed: 346.398 samples/sec, CrossEntropy=2.496, SmoothL1=1.079 [Epoch 136][Batch 1499], Speed: 362.562 samples/sec, CrossEntropy=2.498, SmoothL1=1.081 [Epoch 136][Batch 1599], Speed: 356.582 samples/sec, CrossEntropy=2.496, SmoothL1=1.079 [Epoch 136][Batch 1699], Speed: 354.966 samples/sec, CrossEntropy=2.498, SmoothL1=1.079 [Epoch 136][Batch 1799], Speed: 359.713 samples/sec, CrossEntropy=2.496, SmoothL1=1.079 [Epoch 136] Training cost: 335.077, CrossEntropy=2.496, SmoothL1=1.079 [Epoch 136] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.224 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.387 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.232 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.041 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.234 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.391 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.216 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.310 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.323 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.073 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.352 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.532 person=32.5 bicycle=14.6 car=18.3 motorcycle=25.5 airplane=41.5 bus=44.6 train=48.2 truck=18.5 boat=9.2 traffic light=7.5 fire hydrant=40.7 stop sign=43.8 parking meter=28.6 bench=11.4 bird=14.5 cat=49.5 dog=42.3 horse=36.9 sheep=29.2 cow=26.5 elephant=43.1 bear=50.6 zebra=46.8 giraffe=46.0 backpack=3.2 umbrella=20.4 handbag=2.9 tie=12.4 suitcase=14.8 frisbee=29.4 skis=10.1 snowboard=9.0 sports ball=17.4 kite=14.1 baseball bat=11.2 baseball glove=11.5 skateboard=23.1 surfboard=16.2 tennis racket=23.6 bottle=11.0 wine glass=12.5 cup=18.0 fork=13.4 knife=3.6 spoon=3.4 bowl=23.3 banana=13.1 apple=9.4 sandwich=24.5 orange=18.1 broccoli=12.3 carrot=9.0 hot dog=21.4 pizza=33.1 donut=22.8 cake=19.2 chair=11.4 couch=29.8 potted plant=12.4 bed=31.6 dining table=20.7 toilet=44.6 tv=39.6 laptop=42.8 mouse=29.9 remote=6.6 keyboard=31.6 cell phone=14.4 microwave=35.9 oven=23.7 toaster=2.2 sink=21.1 refrigerator=34.4 book=3.2 clock=28.1 vase=14.9 scissors=18.0 teddy bear=30.9 hair drier=0.0 toothbrush=4.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.4 [Epoch 137][Batch 99], Speed: 352.005 samples/sec, CrossEntropy=2.487, SmoothL1=1.090 [Epoch 137][Batch 199], Speed: 344.909 samples/sec, CrossEntropy=2.497, SmoothL1=1.090 [Epoch 137][Batch 299], Speed: 346.101 samples/sec, CrossEntropy=2.487, SmoothL1=1.070 [Epoch 137][Batch 399], Speed: 345.548 samples/sec, CrossEntropy=2.504, SmoothL1=1.082 [Epoch 137][Batch 499], Speed: 357.486 samples/sec, CrossEntropy=2.498, SmoothL1=1.084 [Epoch 137][Batch 599], Speed: 355.769 samples/sec, CrossEntropy=2.507, SmoothL1=1.081 [Epoch 137][Batch 699], Speed: 354.065 samples/sec, CrossEntropy=2.506, SmoothL1=1.079 [Epoch 137][Batch 799], Speed: 360.453 samples/sec, CrossEntropy=2.508, SmoothL1=1.080 [Epoch 137][Batch 899], Speed: 345.963 samples/sec, CrossEntropy=2.506, SmoothL1=1.080 [Epoch 137][Batch 999], Speed: 357.938 samples/sec, CrossEntropy=2.510, SmoothL1=1.083 [Epoch 137][Batch 1099], Speed: 349.614 samples/sec, CrossEntropy=2.511, SmoothL1=1.083 [Epoch 137][Batch 1199], Speed: 353.682 samples/sec, CrossEntropy=2.512, SmoothL1=1.084 [Epoch 137][Batch 1299], Speed: 356.327 samples/sec, CrossEntropy=2.511, SmoothL1=1.083 [Epoch 137][Batch 1399], Speed: 343.828 samples/sec, CrossEntropy=2.508, SmoothL1=1.080 [Epoch 137][Batch 1499], Speed: 353.851 samples/sec, CrossEntropy=2.508, SmoothL1=1.082 [Epoch 137][Batch 1599], Speed: 356.709 samples/sec, CrossEntropy=2.511, SmoothL1=1.084 [Epoch 137][Batch 1699], Speed: 353.839 samples/sec, CrossEntropy=2.509, SmoothL1=1.083 [Epoch 137][Batch 1799], Speed: 357.302 samples/sec, CrossEntropy=2.506, SmoothL1=1.080 [Epoch 137] Training cost: 334.987, CrossEntropy=2.506, SmoothL1=1.080 [Epoch 137] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.220 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.381 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.044 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.234 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.388 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.215 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.308 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.321 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.073 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.352 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.534 person=32.2 bicycle=15.2 car=17.9 motorcycle=25.1 airplane=41.6 bus=45.9 train=49.6 truck=18.1 boat=9.6 traffic light=7.0 fire hydrant=38.6 stop sign=43.7 parking meter=25.1 bench=12.6 bird=14.2 cat=47.8 dog=42.1 horse=36.8 sheep=29.3 cow=27.3 elephant=43.0 bear=49.3 zebra=46.2 giraffe=46.1 backpack=3.5 umbrella=20.1 handbag=2.8 tie=12.6 suitcase=15.1 frisbee=28.9 skis=9.6 snowboard=10.2 sports ball=16.6 kite=15.3 baseball bat=10.0 baseball glove=11.3 skateboard=22.9 surfboard=17.0 tennis racket=23.4 bottle=10.3 wine glass=11.5 cup=17.0 fork=12.4 knife=4.0 spoon=3.8 bowl=22.8 banana=12.6 apple=9.0 sandwich=22.9 orange=17.0 broccoli=13.8 carrot=7.9 hot dog=17.9 pizza=35.3 donut=23.1 cake=16.9 chair=12.0 couch=30.1 potted plant=11.2 bed=33.4 dining table=21.0 toilet=43.0 tv=39.7 laptop=41.5 mouse=27.6 remote=5.4 keyboard=30.9 cell phone=14.2 microwave=33.8 oven=25.3 toaster=2.8 sink=21.4 refrigerator=34.1 book=3.8 clock=27.6 vase=16.0 scissors=13.8 teddy bear=27.8 hair drier=0.0 toothbrush=5.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.0 [Epoch 138][Batch 99], Speed: 348.025 samples/sec, CrossEntropy=2.521, SmoothL1=1.044 [Epoch 138][Batch 199], Speed: 364.213 samples/sec, CrossEntropy=2.506, SmoothL1=1.059 [Epoch 138][Batch 299], Speed: 348.027 samples/sec, CrossEntropy=2.511, SmoothL1=1.064 [Epoch 138][Batch 399], Speed: 349.430 samples/sec, CrossEntropy=2.513, SmoothL1=1.059 [Epoch 138][Batch 499], Speed: 350.839 samples/sec, CrossEntropy=2.513, SmoothL1=1.065 [Epoch 138][Batch 599], Speed: 353.362 samples/sec, CrossEntropy=2.511, SmoothL1=1.062 [Epoch 138][Batch 699], Speed: 363.823 samples/sec, CrossEntropy=2.508, SmoothL1=1.065 [Epoch 138][Batch 799], Speed: 346.637 samples/sec, CrossEntropy=2.503, SmoothL1=1.066 [Epoch 138][Batch 899], Speed: 349.079 samples/sec, CrossEntropy=2.500, SmoothL1=1.066 [Epoch 138][Batch 999], Speed: 360.748 samples/sec, CrossEntropy=2.501, SmoothL1=1.068 [Epoch 138][Batch 1099], Speed: 345.151 samples/sec, CrossEntropy=2.503, SmoothL1=1.069 [Epoch 138][Batch 1199], Speed: 350.681 samples/sec, CrossEntropy=2.507, SmoothL1=1.074 [Epoch 138][Batch 1299], Speed: 355.326 samples/sec, CrossEntropy=2.505, SmoothL1=1.072 [Epoch 138][Batch 1399], Speed: 349.024 samples/sec, CrossEntropy=2.506, SmoothL1=1.072 [Epoch 138][Batch 1499], Speed: 355.768 samples/sec, CrossEntropy=2.505, SmoothL1=1.074 [Epoch 138][Batch 1599], Speed: 346.120 samples/sec, CrossEntropy=2.504, SmoothL1=1.074 [Epoch 138][Batch 1699], Speed: 354.892 samples/sec, CrossEntropy=2.502, SmoothL1=1.074 [Epoch 138][Batch 1799], Speed: 357.391 samples/sec, CrossEntropy=2.503, SmoothL1=1.076 [Epoch 138] Training cost: 335.165, CrossEntropy=2.502, SmoothL1=1.075 [Epoch 138] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.226 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.385 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.237 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.042 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.237 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.399 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.215 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.307 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.319 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.349 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.530 person=33.0 bicycle=15.6 car=18.5 motorcycle=24.3 airplane=44.7 bus=48.0 train=50.5 truck=19.6 boat=9.8 traffic light=7.0 fire hydrant=43.1 stop sign=43.7 parking meter=29.2 bench=11.9 bird=13.7 cat=50.7 dog=45.1 horse=36.6 sheep=28.6 cow=29.2 elephant=41.4 bear=52.5 zebra=45.0 giraffe=46.6 backpack=3.1 umbrella=21.5 handbag=2.6 tie=12.4 suitcase=16.1 frisbee=30.4 skis=10.5 snowboard=11.8 sports ball=17.6 kite=15.0 baseball bat=8.7 baseball glove=11.7 skateboard=23.8 surfboard=16.8 tennis racket=23.7 bottle=11.3 wine glass=11.6 cup=17.6 fork=12.1 knife=5.2 spoon=4.2 bowl=22.0 banana=13.1 apple=8.2 sandwich=25.0 orange=18.9 broccoli=13.5 carrot=7.5 hot dog=18.2 pizza=33.8 donut=22.0 cake=17.8 chair=12.4 couch=30.9 potted plant=12.6 bed=35.6 dining table=20.7 toilet=43.9 tv=39.5 laptop=40.8 mouse=27.1 remote=6.4 keyboard=30.0 cell phone=14.7 microwave=34.2 oven=24.0 toaster=0.0 sink=21.3 refrigerator=35.3 book=4.1 clock=27.9 vase=15.7 scissors=17.8 teddy bear=28.1 hair drier=0.0 toothbrush=6.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.6 [Epoch 139][Batch 99], Speed: 349.262 samples/sec, CrossEntropy=2.484, SmoothL1=1.045 [Epoch 139][Batch 199], Speed: 365.122 samples/sec, CrossEntropy=2.470, SmoothL1=1.051 [Epoch 139][Batch 299], Speed: 359.787 samples/sec, CrossEntropy=2.482, SmoothL1=1.062 [Epoch 139][Batch 399], Speed: 356.500 samples/sec, CrossEntropy=2.481, SmoothL1=1.059 [Epoch 139][Batch 499], Speed: 349.180 samples/sec, CrossEntropy=2.494, SmoothL1=1.070 [Epoch 139][Batch 599], Speed: 344.845 samples/sec, CrossEntropy=2.491, SmoothL1=1.069 [Epoch 139][Batch 699], Speed: 360.339 samples/sec, CrossEntropy=2.486, SmoothL1=1.067 [Epoch 139][Batch 799], Speed: 350.242 samples/sec, CrossEntropy=2.490, SmoothL1=1.071 [Epoch 139][Batch 899], Speed: 357.830 samples/sec, CrossEntropy=2.489, SmoothL1=1.072 [Epoch 139][Batch 999], Speed: 351.909 samples/sec, CrossEntropy=2.490, SmoothL1=1.075 [Epoch 139][Batch 1099], Speed: 353.609 samples/sec, CrossEntropy=2.489, SmoothL1=1.074 [Epoch 139][Batch 1199], Speed: 351.445 samples/sec, CrossEntropy=2.494, SmoothL1=1.073 [Epoch 139][Batch 1299], Speed: 359.588 samples/sec, CrossEntropy=2.496, SmoothL1=1.074 [Epoch 139][Batch 1399], Speed: 361.393 samples/sec, CrossEntropy=2.494, SmoothL1=1.071 [Epoch 139][Batch 1499], Speed: 351.151 samples/sec, CrossEntropy=2.494, SmoothL1=1.072 [Epoch 139][Batch 1599], Speed: 340.843 samples/sec, CrossEntropy=2.490, SmoothL1=1.072 [Epoch 139][Batch 1699], Speed: 353.789 samples/sec, CrossEntropy=2.488, SmoothL1=1.071 [Epoch 139][Batch 1799], Speed: 353.448 samples/sec, CrossEntropy=2.485, SmoothL1=1.069 [Epoch 139] Training cost: 335.645, CrossEntropy=2.485, SmoothL1=1.069 [Epoch 139] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.220 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.380 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.228 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.042 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.234 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.383 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.213 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.305 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.317 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.068 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.343 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.534 person=32.4 bicycle=14.4 car=18.5 motorcycle=23.3 airplane=41.6 bus=46.2 train=48.7 truck=19.0 boat=9.9 traffic light=7.0 fire hydrant=39.3 stop sign=41.5 parking meter=25.4 bench=11.6 bird=13.2 cat=49.3 dog=43.0 horse=37.3 sheep=28.7 cow=28.4 elephant=41.5 bear=48.8 zebra=44.2 giraffe=46.9 backpack=2.9 umbrella=21.5 handbag=2.9 tie=11.9 suitcase=13.4 frisbee=30.1 skis=10.7 snowboard=9.9 sports ball=16.8 kite=14.2 baseball bat=7.7 baseball glove=10.9 skateboard=23.4 surfboard=16.7 tennis racket=23.8 bottle=11.6 wine glass=11.7 cup=17.0 fork=11.6 knife=4.2 spoon=3.9 bowl=22.9 banana=12.1 apple=8.2 sandwich=26.4 orange=19.1 broccoli=12.0 carrot=8.9 hot dog=16.8 pizza=32.8 donut=22.7 cake=17.0 chair=12.2 couch=29.5 potted plant=11.5 bed=31.3 dining table=20.3 toilet=41.4 tv=38.6 laptop=40.9 mouse=27.9 remote=6.3 keyboard=28.8 cell phone=14.5 microwave=36.7 oven=25.2 toaster=2.5 sink=19.4 refrigerator=36.7 book=3.4 clock=28.7 vase=15.4 scissors=18.5 teddy bear=28.9 hair drier=0.0 toothbrush=6.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.0 [Epoch 140][Batch 99], Speed: 357.698 samples/sec, CrossEntropy=2.504, SmoothL1=1.087 [Epoch 140][Batch 199], Speed: 350.144 samples/sec, CrossEntropy=2.495, SmoothL1=1.079 [Epoch 140][Batch 299], Speed: 360.609 samples/sec, CrossEntropy=2.493, SmoothL1=1.086 [Epoch 140][Batch 399], Speed: 348.662 samples/sec, CrossEntropy=2.490, SmoothL1=1.081 [Epoch 140][Batch 499], Speed: 347.647 samples/sec, CrossEntropy=2.491, SmoothL1=1.081 [Epoch 140][Batch 599], Speed: 349.933 samples/sec, CrossEntropy=2.487, SmoothL1=1.079 [Epoch 140][Batch 699], Speed: 354.156 samples/sec, CrossEntropy=2.493, SmoothL1=1.077 [Epoch 140][Batch 799], Speed: 360.856 samples/sec, CrossEntropy=2.500, SmoothL1=1.079 [Epoch 140][Batch 899], Speed: 361.018 samples/sec, CrossEntropy=2.505, SmoothL1=1.083 [Epoch 140][Batch 999], Speed: 351.211 samples/sec, CrossEntropy=2.507, SmoothL1=1.083 [Epoch 140][Batch 1099], Speed: 342.710 samples/sec, CrossEntropy=2.509, SmoothL1=1.084 [Epoch 140][Batch 1199], Speed: 349.453 samples/sec, CrossEntropy=2.509, SmoothL1=1.087 [Epoch 140][Batch 1299], Speed: 352.573 samples/sec, CrossEntropy=2.508, SmoothL1=1.085 [Epoch 140][Batch 1399], Speed: 353.202 samples/sec, CrossEntropy=2.505, SmoothL1=1.086 [Epoch 140][Batch 1499], Speed: 349.224 samples/sec, CrossEntropy=2.504, SmoothL1=1.085 [Epoch 140][Batch 1599], Speed: 352.832 samples/sec, CrossEntropy=2.505, SmoothL1=1.086 [Epoch 140][Batch 1699], Speed: 348.232 samples/sec, CrossEntropy=2.505, SmoothL1=1.087 [Epoch 140][Batch 1799], Speed: 358.288 samples/sec, CrossEntropy=2.503, SmoothL1=1.086 [Epoch 140] Training cost: 335.534, CrossEntropy=2.502, SmoothL1=1.086 [Epoch 140] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.386 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.232 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.039 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.239 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.384 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.306 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.319 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.068 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.351 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.528 person=32.6 bicycle=13.5 car=18.0 motorcycle=24.3 airplane=41.8 bus=46.1 train=48.9 truck=17.6 boat=10.1 traffic light=7.2 fire hydrant=41.1 stop sign=41.5 parking meter=26.1 bench=12.1 bird=15.1 cat=49.0 dog=40.9 horse=37.1 sheep=29.2 cow=28.0 elephant=41.6 bear=50.6 zebra=44.6 giraffe=45.4 backpack=3.2 umbrella=20.2 handbag=3.1 tie=12.7 suitcase=15.3 frisbee=26.5 skis=9.4 snowboard=12.8 sports ball=16.2 kite=14.9 baseball bat=8.3 baseball glove=12.6 skateboard=23.8 surfboard=16.3 tennis racket=23.5 bottle=11.5 wine glass=10.8 cup=17.5 fork=10.5 knife=4.5 spoon=4.2 bowl=22.3 banana=13.8 apple=7.6 sandwich=26.1 orange=18.4 broccoli=13.3 carrot=8.9 hot dog=21.5 pizza=32.6 donut=24.9 cake=19.5 chair=12.2 couch=27.8 potted plant=11.7 bed=34.4 dining table=19.2 toilet=42.6 tv=39.2 laptop=40.6 mouse=27.1 remote=6.4 keyboard=32.2 cell phone=14.8 microwave=32.9 oven=24.9 toaster=3.6 sink=19.2 refrigerator=33.3 book=3.8 clock=28.6 vase=14.5 scissors=15.4 teddy bear=30.2 hair drier=0.0 toothbrush=7.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.1 [Epoch 141][Batch 99], Speed: 356.960 samples/sec, CrossEntropy=2.465, SmoothL1=1.079 [Epoch 141][Batch 199], Speed: 360.698 samples/sec, CrossEntropy=2.481, SmoothL1=1.082 [Epoch 141][Batch 299], Speed: 363.079 samples/sec, CrossEntropy=2.486, SmoothL1=1.074 [Epoch 141][Batch 399], Speed: 352.853 samples/sec, CrossEntropy=2.481, SmoothL1=1.075 [Epoch 141][Batch 499], Speed: 346.094 samples/sec, CrossEntropy=2.477, SmoothL1=1.075 [Epoch 141][Batch 599], Speed: 345.327 samples/sec, CrossEntropy=2.486, SmoothL1=1.079 [Epoch 141][Batch 699], Speed: 353.828 samples/sec, CrossEntropy=2.490, SmoothL1=1.083 [Epoch 141][Batch 799], Speed: 348.632 samples/sec, CrossEntropy=2.494, SmoothL1=1.084 [Epoch 141][Batch 899], Speed: 346.782 samples/sec, CrossEntropy=2.496, SmoothL1=1.085 [Epoch 141][Batch 999], Speed: 361.617 samples/sec, CrossEntropy=2.496, SmoothL1=1.086 [Epoch 141][Batch 1099], Speed: 361.099 samples/sec, CrossEntropy=2.495, SmoothL1=1.087 [Epoch 141][Batch 1199], Speed: 354.968 samples/sec, CrossEntropy=2.498, SmoothL1=1.090 [Epoch 141][Batch 1299], Speed: 352.671 samples/sec, CrossEntropy=2.496, SmoothL1=1.087 [Epoch 141][Batch 1399], Speed: 346.768 samples/sec, CrossEntropy=2.495, SmoothL1=1.085 [Epoch 141][Batch 1499], Speed: 344.370 samples/sec, CrossEntropy=2.495, SmoothL1=1.085 [Epoch 141][Batch 1599], Speed: 360.618 samples/sec, CrossEntropy=2.492, SmoothL1=1.082 [Epoch 141][Batch 1699], Speed: 351.356 samples/sec, CrossEntropy=2.490, SmoothL1=1.080 [Epoch 141][Batch 1799], Speed: 360.452 samples/sec, CrossEntropy=2.489, SmoothL1=1.079 [Epoch 141] Training cost: 335.402, CrossEntropy=2.488, SmoothL1=1.079 [Epoch 141] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.384 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.236 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.239 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.401 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.216 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.310 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.323 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.349 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.547 person=32.2 bicycle=14.1 car=18.3 motorcycle=26.6 airplane=42.8 bus=46.3 train=48.5 truck=17.8 boat=10.0 traffic light=7.0 fire hydrant=40.5 stop sign=43.1 parking meter=27.1 bench=12.6 bird=14.3 cat=49.1 dog=42.0 horse=37.1 sheep=29.7 cow=28.5 elephant=41.2 bear=50.8 zebra=46.7 giraffe=46.9 backpack=3.1 umbrella=19.4 handbag=2.9 tie=12.2 suitcase=13.7 frisbee=31.1 skis=9.2 snowboard=10.7 sports ball=16.9 kite=15.1 baseball bat=8.7 baseball glove=11.4 skateboard=23.5 surfboard=17.1 tennis racket=22.7 bottle=11.1 wine glass=11.0 cup=16.6 fork=12.4 knife=4.5 spoon=3.8 bowl=23.0 banana=11.8 apple=9.4 sandwich=27.9 orange=17.8 broccoli=12.7 carrot=9.4 hot dog=24.4 pizza=35.9 donut=24.6 cake=18.6 chair=10.9 couch=32.0 potted plant=11.0 bed=32.5 dining table=19.6 toilet=42.2 tv=38.6 laptop=41.8 mouse=27.9 remote=5.4 keyboard=31.2 cell phone=14.8 microwave=34.5 oven=25.7 toaster=3.9 sink=19.7 refrigerator=36.6 book=3.5 clock=29.1 vase=15.0 scissors=20.5 teddy bear=30.9 hair drier=0.0 toothbrush=4.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.5 [Epoch 142][Batch 99], Speed: 347.458 samples/sec, CrossEntropy=2.472, SmoothL1=1.073 [Epoch 142][Batch 199], Speed: 357.524 samples/sec, CrossEntropy=2.472, SmoothL1=1.082 [Epoch 142][Batch 299], Speed: 350.373 samples/sec, CrossEntropy=2.481, SmoothL1=1.085 [Epoch 142][Batch 399], Speed: 351.375 samples/sec, CrossEntropy=2.484, SmoothL1=1.085 [Epoch 142][Batch 499], Speed: 357.802 samples/sec, CrossEntropy=2.482, SmoothL1=1.085 [Epoch 142][Batch 599], Speed: 350.517 samples/sec, CrossEntropy=2.482, SmoothL1=1.081 [Epoch 142][Batch 699], Speed: 354.118 samples/sec, CrossEntropy=2.485, SmoothL1=1.083 [Epoch 142][Batch 799], Speed: 359.014 samples/sec, CrossEntropy=2.485, SmoothL1=1.081 [Epoch 142][Batch 899], Speed: 356.373 samples/sec, CrossEntropy=2.489, SmoothL1=1.082 [Epoch 142][Batch 999], Speed: 356.105 samples/sec, CrossEntropy=2.495, SmoothL1=1.085 [Epoch 142][Batch 1099], Speed: 346.750 samples/sec, CrossEntropy=2.494, SmoothL1=1.084 [Epoch 142][Batch 1199], Speed: 349.352 samples/sec, CrossEntropy=2.494, SmoothL1=1.082 [Epoch 142][Batch 1299], Speed: 356.029 samples/sec, CrossEntropy=2.493, SmoothL1=1.080 [Epoch 142][Batch 1399], Speed: 356.349 samples/sec, CrossEntropy=2.490, SmoothL1=1.077 [Epoch 142][Batch 1499], Speed: 351.334 samples/sec, CrossEntropy=2.489, SmoothL1=1.077 [Epoch 142][Batch 1599], Speed: 358.919 samples/sec, CrossEntropy=2.488, SmoothL1=1.076 [Epoch 142][Batch 1699], Speed: 341.844 samples/sec, CrossEntropy=2.487, SmoothL1=1.076 [Epoch 142][Batch 1799], Speed: 353.091 samples/sec, CrossEntropy=2.488, SmoothL1=1.077 [Epoch 142] Training cost: 335.706, CrossEntropy=2.488, SmoothL1=1.078 [Epoch 142] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.224 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.386 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.043 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.237 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.391 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.218 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.310 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.323 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.071 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.352 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.542 person=32.1 bicycle=15.0 car=18.5 motorcycle=23.9 airplane=41.6 bus=47.5 train=49.5 truck=18.9 boat=8.9 traffic light=7.1 fire hydrant=42.5 stop sign=44.8 parking meter=29.6 bench=11.4 bird=13.8 cat=51.8 dog=43.1 horse=37.8 sheep=29.2 cow=29.9 elephant=41.8 bear=51.4 zebra=44.5 giraffe=47.8 backpack=2.4 umbrella=21.1 handbag=3.1 tie=12.1 suitcase=15.1 frisbee=27.7 skis=10.1 snowboard=10.5 sports ball=16.0 kite=14.3 baseball bat=7.8 baseball glove=10.5 skateboard=21.8 surfboard=17.0 tennis racket=23.2 bottle=12.0 wine glass=11.5 cup=17.6 fork=11.8 knife=5.2 spoon=3.8 bowl=21.5 banana=12.8 apple=9.6 sandwich=28.6 orange=17.7 broccoli=13.3 carrot=9.9 hot dog=24.1 pizza=34.1 donut=22.9 cake=18.9 chair=11.4 couch=30.1 potted plant=11.1 bed=31.3 dining table=20.7 toilet=43.8 tv=39.8 laptop=41.4 mouse=29.9 remote=6.2 keyboard=28.7 cell phone=14.4 microwave=32.2 oven=25.3 toaster=2.8 sink=21.0 refrigerator=33.3 book=3.0 clock=27.7 vase=16.3 scissors=16.9 teddy bear=29.8 hair drier=0.0 toothbrush=4.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.4 [Epoch 143][Batch 99], Speed: 354.750 samples/sec, CrossEntropy=2.464, SmoothL1=1.060 [Epoch 143][Batch 199], Speed: 359.064 samples/sec, CrossEntropy=2.493, SmoothL1=1.075 [Epoch 143][Batch 299], Speed: 350.243 samples/sec, CrossEntropy=2.482, SmoothL1=1.073 [Epoch 143][Batch 399], Speed: 353.011 samples/sec, CrossEntropy=2.484, SmoothL1=1.077 [Epoch 143][Batch 499], Speed: 348.282 samples/sec, CrossEntropy=2.491, SmoothL1=1.081 [Epoch 143][Batch 599], Speed: 346.810 samples/sec, CrossEntropy=2.491, SmoothL1=1.081 [Epoch 143][Batch 699], Speed: 349.853 samples/sec, CrossEntropy=2.493, SmoothL1=1.081 [Epoch 143][Batch 799], Speed: 358.920 samples/sec, CrossEntropy=2.495, SmoothL1=1.082 [Epoch 143][Batch 899], Speed: 345.701 samples/sec, CrossEntropy=2.499, SmoothL1=1.081 [Epoch 143][Batch 999], Speed: 344.378 samples/sec, CrossEntropy=2.497, SmoothL1=1.079 [Epoch 143][Batch 1099], Speed: 355.644 samples/sec, CrossEntropy=2.496, SmoothL1=1.079 [Epoch 143][Batch 1199], Speed: 354.636 samples/sec, CrossEntropy=2.497, SmoothL1=1.078 [Epoch 143][Batch 1299], Speed: 362.604 samples/sec, CrossEntropy=2.496, SmoothL1=1.077 [Epoch 143][Batch 1399], Speed: 358.884 samples/sec, CrossEntropy=2.490, SmoothL1=1.075 [Epoch 143][Batch 1499], Speed: 362.842 samples/sec, CrossEntropy=2.491, SmoothL1=1.073 [Epoch 143][Batch 1599], Speed: 356.122 samples/sec, CrossEntropy=2.489, SmoothL1=1.073 [Epoch 143][Batch 1699], Speed: 358.212 samples/sec, CrossEntropy=2.491, SmoothL1=1.074 [Epoch 143][Batch 1799], Speed: 365.815 samples/sec, CrossEntropy=2.490, SmoothL1=1.074 [Epoch 143] Training cost: 334.907, CrossEntropy=2.491, SmoothL1=1.073 [Epoch 143] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.224 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.384 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.235 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.041 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.241 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.391 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.216 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.310 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.323 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.066 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.359 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.542 person=31.9 bicycle=14.8 car=18.4 motorcycle=25.8 airplane=41.6 bus=47.9 train=51.3 truck=18.9 boat=10.2 traffic light=6.8 fire hydrant=40.2 stop sign=44.6 parking meter=29.9 bench=11.4 bird=13.0 cat=50.1 dog=43.9 horse=37.3 sheep=27.8 cow=29.1 elephant=41.4 bear=51.2 zebra=44.8 giraffe=46.5 backpack=3.6 umbrella=20.2 handbag=2.7 tie=13.1 suitcase=15.4 frisbee=26.6 skis=8.7 snowboard=10.8 sports ball=14.8 kite=13.7 baseball bat=8.7 baseball glove=11.8 skateboard=23.2 surfboard=17.3 tennis racket=23.0 bottle=11.3 wine glass=11.8 cup=17.4 fork=10.9 knife=4.4 spoon=2.7 bowl=22.5 banana=13.3 apple=8.9 sandwich=24.2 orange=17.2 broccoli=13.3 carrot=9.3 hot dog=21.1 pizza=33.5 donut=24.3 cake=18.5 chair=11.1 couch=32.3 potted plant=12.0 bed=33.7 dining table=19.5 toilet=44.0 tv=41.1 laptop=40.8 mouse=29.8 remote=6.8 keyboard=27.6 cell phone=15.0 microwave=32.0 oven=27.2 toaster=7.6 sink=19.1 refrigerator=35.3 book=3.3 clock=29.2 vase=14.9 scissors=17.6 teddy bear=27.7 hair drier=0.0 toothbrush=6.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.4 [Epoch 144][Batch 99], Speed: 361.842 samples/sec, CrossEntropy=2.436, SmoothL1=1.061 [Epoch 144][Batch 199], Speed: 349.951 samples/sec, CrossEntropy=2.461, SmoothL1=1.066 [Epoch 144][Batch 299], Speed: 359.554 samples/sec, CrossEntropy=2.447, SmoothL1=1.054 [Epoch 144][Batch 399], Speed: 352.432 samples/sec, CrossEntropy=2.460, SmoothL1=1.057 [Epoch 144][Batch 499], Speed: 351.040 samples/sec, CrossEntropy=2.460, SmoothL1=1.062 [Epoch 144][Batch 599], Speed: 363.471 samples/sec, CrossEntropy=2.466, SmoothL1=1.065 [Epoch 144][Batch 699], Speed: 347.710 samples/sec, CrossEntropy=2.472, SmoothL1=1.068 [Epoch 144][Batch 799], Speed: 354.693 samples/sec, CrossEntropy=2.480, SmoothL1=1.070 [Epoch 144][Batch 899], Speed: 349.057 samples/sec, CrossEntropy=2.479, SmoothL1=1.070 [Epoch 144][Batch 999], Speed: 361.539 samples/sec, CrossEntropy=2.479, SmoothL1=1.068 [Epoch 144][Batch 1099], Speed: 354.921 samples/sec, CrossEntropy=2.487, SmoothL1=1.068 [Epoch 144][Batch 1199], Speed: 351.455 samples/sec, CrossEntropy=2.486, SmoothL1=1.069 [Epoch 144][Batch 1299], Speed: 358.777 samples/sec, CrossEntropy=2.482, SmoothL1=1.068 [Epoch 144][Batch 1399], Speed: 349.143 samples/sec, CrossEntropy=2.483, SmoothL1=1.067 [Epoch 144][Batch 1499], Speed: 348.544 samples/sec, CrossEntropy=2.483, SmoothL1=1.068 [Epoch 144][Batch 1599], Speed: 350.818 samples/sec, CrossEntropy=2.483, SmoothL1=1.067 [Epoch 144][Batch 1699], Speed: 348.535 samples/sec, CrossEntropy=2.482, SmoothL1=1.066 [Epoch 144][Batch 1799], Speed: 339.689 samples/sec, CrossEntropy=2.482, SmoothL1=1.066 [Epoch 144] Training cost: 335.130, CrossEntropy=2.481, SmoothL1=1.065 [Epoch 144] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.384 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.229 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.043 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.233 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.212 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.316 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.070 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.526 person=32.2 bicycle=14.2 car=18.1 motorcycle=25.0 airplane=42.3 bus=44.7 train=49.4 truck=19.6 boat=10.5 traffic light=6.8 fire hydrant=38.7 stop sign=43.3 parking meter=25.2 bench=11.2 bird=13.9 cat=46.9 dog=42.9 horse=35.5 sheep=28.4 cow=29.8 elephant=40.0 bear=47.4 zebra=45.7 giraffe=46.5 backpack=3.3 umbrella=21.0 handbag=3.1 tie=12.2 suitcase=16.5 frisbee=26.8 skis=8.4 snowboard=9.6 sports ball=15.2 kite=13.6 baseball bat=8.4 baseball glove=11.2 skateboard=22.8 surfboard=16.6 tennis racket=22.6 bottle=10.6 wine glass=11.5 cup=16.5 fork=13.2 knife=4.5 spoon=4.9 bowl=21.8 banana=11.9 apple=7.9 sandwich=23.6 orange=20.5 broccoli=13.9 carrot=8.9 hot dog=17.3 pizza=32.9 donut=24.0 cake=16.6 chair=11.8 couch=31.4 potted plant=13.0 bed=32.3 dining table=19.7 toilet=44.4 tv=37.3 laptop=40.6 mouse=25.7 remote=6.1 keyboard=29.6 cell phone=15.1 microwave=35.1 oven=24.6 toaster=0.6 sink=19.7 refrigerator=35.7 book=3.3 clock=27.1 vase=15.7 scissors=18.2 teddy bear=27.9 hair drier=0.0 toothbrush=4.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.9 [Epoch 145][Batch 99], Speed: 352.884 samples/sec, CrossEntropy=2.485, SmoothL1=1.063 [Epoch 145][Batch 199], Speed: 361.877 samples/sec, CrossEntropy=2.484, SmoothL1=1.068 [Epoch 145][Batch 299], Speed: 361.850 samples/sec, CrossEntropy=2.485, SmoothL1=1.072 [Epoch 145][Batch 399], Speed: 352.665 samples/sec, CrossEntropy=2.480, SmoothL1=1.072 [Epoch 145][Batch 499], Speed: 354.795 samples/sec, CrossEntropy=2.477, SmoothL1=1.072 [Epoch 145][Batch 599], Speed: 342.863 samples/sec, CrossEntropy=2.482, SmoothL1=1.073 [Epoch 145][Batch 699], Speed: 364.188 samples/sec, CrossEntropy=2.485, SmoothL1=1.071 [Epoch 145][Batch 799], Speed: 349.518 samples/sec, CrossEntropy=2.483, SmoothL1=1.070 [Epoch 145][Batch 899], Speed: 356.779 samples/sec, CrossEntropy=2.482, SmoothL1=1.072 [Epoch 145][Batch 999], Speed: 354.329 samples/sec, CrossEntropy=2.482, SmoothL1=1.070 [Epoch 145][Batch 1099], Speed: 351.484 samples/sec, CrossEntropy=2.487, SmoothL1=1.072 [Epoch 145][Batch 1199], Speed: 361.032 samples/sec, CrossEntropy=2.489, SmoothL1=1.073 [Epoch 145][Batch 1299], Speed: 352.407 samples/sec, CrossEntropy=2.490, SmoothL1=1.074 [Epoch 145][Batch 1399], Speed: 354.541 samples/sec, CrossEntropy=2.491, SmoothL1=1.075 [Epoch 145][Batch 1499], Speed: 354.748 samples/sec, CrossEntropy=2.489, SmoothL1=1.075 [Epoch 145][Batch 1599], Speed: 351.966 samples/sec, CrossEntropy=2.488, SmoothL1=1.074 [Epoch 145][Batch 1699], Speed: 358.430 samples/sec, CrossEntropy=2.489, SmoothL1=1.073 [Epoch 145][Batch 1799], Speed: 355.211 samples/sec, CrossEntropy=2.489, SmoothL1=1.073 [Epoch 145] Training cost: 334.676, CrossEntropy=2.488, SmoothL1=1.072 [Epoch 145] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.224 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.389 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.041 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.235 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.398 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.215 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.308 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.321 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.069 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.349 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.539 person=32.7 bicycle=15.1 car=18.4 motorcycle=25.8 airplane=40.3 bus=45.7 train=48.7 truck=17.5 boat=10.0 traffic light=6.8 fire hydrant=40.0 stop sign=42.2 parking meter=27.4 bench=11.7 bird=14.1 cat=49.3 dog=42.5 horse=36.9 sheep=27.9 cow=27.7 elephant=41.7 bear=49.9 zebra=45.3 giraffe=45.0 backpack=3.5 umbrella=20.1 handbag=2.9 tie=12.1 suitcase=17.0 frisbee=28.2 skis=9.4 snowboard=10.3 sports ball=16.7 kite=14.9 baseball bat=10.3 baseball glove=11.2 skateboard=21.9 surfboard=18.0 tennis racket=23.5 bottle=11.4 wine glass=11.3 cup=17.7 fork=12.0 knife=4.8 spoon=4.3 bowl=23.1 banana=13.5 apple=9.1 sandwich=28.2 orange=19.9 broccoli=12.5 carrot=9.2 hot dog=20.6 pizza=35.9 donut=23.9 cake=18.9 chair=11.5 couch=31.3 potted plant=12.7 bed=33.2 dining table=18.7 toilet=42.4 tv=39.7 laptop=40.4 mouse=27.0 remote=6.0 keyboard=29.2 cell phone=14.8 microwave=34.4 oven=26.4 toaster=14.3 sink=18.1 refrigerator=33.2 book=3.8 clock=29.2 vase=15.2 scissors=14.9 teddy bear=30.2 hair drier=0.0 toothbrush=4.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.4 [Epoch 146][Batch 99], Speed: 352.852 samples/sec, CrossEntropy=2.428, SmoothL1=1.054 [Epoch 146][Batch 199], Speed: 355.115 samples/sec, CrossEntropy=2.469, SmoothL1=1.070 [Epoch 146][Batch 299], Speed: 354.174 samples/sec, CrossEntropy=2.475, SmoothL1=1.073 [Epoch 146][Batch 399], Speed: 348.095 samples/sec, CrossEntropy=2.482, SmoothL1=1.073 [Epoch 146][Batch 499], Speed: 359.129 samples/sec, CrossEntropy=2.471, SmoothL1=1.072 [Epoch 146][Batch 599], Speed: 350.526 samples/sec, CrossEntropy=2.479, SmoothL1=1.074 [Epoch 146][Batch 699], Speed: 350.843 samples/sec, CrossEntropy=2.484, SmoothL1=1.074 [Epoch 146][Batch 799], Speed: 349.060 samples/sec, CrossEntropy=2.482, SmoothL1=1.073 [Epoch 146][Batch 899], Speed: 355.176 samples/sec, CrossEntropy=2.486, SmoothL1=1.075 [Epoch 146][Batch 999], Speed: 348.941 samples/sec, CrossEntropy=2.484, SmoothL1=1.076 [Epoch 146][Batch 1099], Speed: 347.034 samples/sec, CrossEntropy=2.485, SmoothL1=1.077 [Epoch 146][Batch 1199], Speed: 360.381 samples/sec, CrossEntropy=2.488, SmoothL1=1.079 [Epoch 146][Batch 1299], Speed: 352.753 samples/sec, CrossEntropy=2.488, SmoothL1=1.078 [Epoch 146][Batch 1399], Speed: 359.939 samples/sec, CrossEntropy=2.486, SmoothL1=1.078 [Epoch 146][Batch 1499], Speed: 346.408 samples/sec, CrossEntropy=2.485, SmoothL1=1.076 [Epoch 146][Batch 1599], Speed: 349.441 samples/sec, CrossEntropy=2.484, SmoothL1=1.077 [Epoch 146][Batch 1699], Speed: 357.324 samples/sec, CrossEntropy=2.486, SmoothL1=1.077 [Epoch 146][Batch 1799], Speed: 347.242 samples/sec, CrossEntropy=2.487, SmoothL1=1.076 [Epoch 146] Training cost: 334.736, CrossEntropy=2.487, SmoothL1=1.076 [Epoch 146] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.228 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.389 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.237 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.042 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.241 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.399 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.219 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.314 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.326 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.068 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.360 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.545 person=32.3 bicycle=14.3 car=18.8 motorcycle=25.0 airplane=43.0 bus=46.7 train=51.0 truck=18.5 boat=9.7 traffic light=7.2 fire hydrant=41.5 stop sign=45.3 parking meter=26.5 bench=12.1 bird=15.0 cat=48.9 dog=43.9 horse=39.6 sheep=30.6 cow=28.6 elephant=44.0 bear=52.1 zebra=45.2 giraffe=47.5 backpack=3.0 umbrella=20.1 handbag=3.4 tie=12.9 suitcase=15.1 frisbee=26.6 skis=9.6 snowboard=11.0 sports ball=15.7 kite=14.8 baseball bat=10.2 baseball glove=11.0 skateboard=25.1 surfboard=16.8 tennis racket=24.2 bottle=11.5 wine glass=12.2 cup=18.0 fork=13.0 knife=4.5 spoon=3.6 bowl=23.4 banana=12.9 apple=8.5 sandwich=28.3 orange=19.7 broccoli=14.4 carrot=10.2 hot dog=20.9 pizza=35.1 donut=25.4 cake=20.0 chair=11.9 couch=31.7 potted plant=11.5 bed=32.9 dining table=21.6 toilet=42.3 tv=39.0 laptop=42.2 mouse=29.6 remote=6.2 keyboard=31.2 cell phone=16.0 microwave=35.3 oven=26.8 toaster=2.1 sink=20.1 refrigerator=34.9 book=3.8 clock=28.0 vase=15.3 scissors=18.2 teddy bear=28.8 hair drier=0.0 toothbrush=6.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.8 [Epoch 147][Batch 99], Speed: 357.856 samples/sec, CrossEntropy=2.466, SmoothL1=1.067 [Epoch 147][Batch 199], Speed: 346.739 samples/sec, CrossEntropy=2.477, SmoothL1=1.082 [Epoch 147][Batch 299], Speed: 355.690 samples/sec, CrossEntropy=2.481, SmoothL1=1.080 [Epoch 147][Batch 399], Speed: 353.518 samples/sec, CrossEntropy=2.486, SmoothL1=1.083 [Epoch 147][Batch 499], Speed: 348.304 samples/sec, CrossEntropy=2.481, SmoothL1=1.071 [Epoch 147][Batch 599], Speed: 357.080 samples/sec, CrossEntropy=2.489, SmoothL1=1.077 [Epoch 147][Batch 699], Speed: 357.752 samples/sec, CrossEntropy=2.479, SmoothL1=1.071 [Epoch 147][Batch 799], Speed: 357.741 samples/sec, CrossEntropy=2.473, SmoothL1=1.068 [Epoch 147][Batch 899], Speed: 354.344 samples/sec, CrossEntropy=2.473, SmoothL1=1.068 [Epoch 147][Batch 999], Speed: 353.780 samples/sec, CrossEntropy=2.477, SmoothL1=1.069 [Epoch 147][Batch 1099], Speed: 354.051 samples/sec, CrossEntropy=2.477, SmoothL1=1.068 [Epoch 147][Batch 1199], Speed: 348.846 samples/sec, CrossEntropy=2.473, SmoothL1=1.064 [Epoch 147][Batch 1299], Speed: 358.723 samples/sec, CrossEntropy=2.472, SmoothL1=1.063 [Epoch 147][Batch 1399], Speed: 352.686 samples/sec, CrossEntropy=2.468, SmoothL1=1.062 [Epoch 147][Batch 1499], Speed: 357.559 samples/sec, CrossEntropy=2.467, SmoothL1=1.059 [Epoch 147][Batch 1599], Speed: 346.538 samples/sec, CrossEntropy=2.466, SmoothL1=1.057 [Epoch 147][Batch 1699], Speed: 353.922 samples/sec, CrossEntropy=2.467, SmoothL1=1.057 [Epoch 147][Batch 1799], Speed: 347.856 samples/sec, CrossEntropy=2.466, SmoothL1=1.058 [Epoch 147] Training cost: 335.181, CrossEntropy=2.467, SmoothL1=1.060 [Epoch 147] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.223 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.386 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.232 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.044 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.236 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.386 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.217 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.311 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.324 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.076 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.355 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.529 person=32.3 bicycle=15.3 car=18.3 motorcycle=26.0 airplane=39.7 bus=45.5 train=47.4 truck=18.2 boat=8.7 traffic light=7.7 fire hydrant=41.8 stop sign=43.0 parking meter=23.4 bench=11.6 bird=13.9 cat=50.7 dog=43.0 horse=36.1 sheep=29.7 cow=29.2 elephant=39.0 bear=49.0 zebra=43.9 giraffe=45.2 backpack=3.7 umbrella=20.2 handbag=2.7 tie=12.2 suitcase=14.3 frisbee=28.4 skis=10.1 snowboard=10.3 sports ball=16.6 kite=14.7 baseball bat=7.5 baseball glove=11.4 skateboard=23.9 surfboard=17.2 tennis racket=23.0 bottle=11.3 wine glass=12.1 cup=17.0 fork=11.9 knife=4.6 spoon=3.5 bowl=22.7 banana=13.0 apple=8.3 sandwich=26.8 orange=21.4 broccoli=9.7 carrot=9.1 hot dog=20.4 pizza=35.6 donut=24.6 cake=18.8 chair=12.0 couch=30.9 potted plant=12.1 bed=31.4 dining table=19.6 toilet=42.3 tv=39.0 laptop=42.8 mouse=30.6 remote=5.4 keyboard=32.0 cell phone=14.5 microwave=36.5 oven=23.6 toaster=8.8 sink=21.1 refrigerator=34.4 book=3.5 clock=28.9 vase=14.9 scissors=16.9 teddy bear=28.3 hair drier=0.0 toothbrush=4.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.3 [Epoch 148][Batch 99], Speed: 352.246 samples/sec, CrossEntropy=2.450, SmoothL1=1.069 [Epoch 148][Batch 199], Speed: 365.116 samples/sec, CrossEntropy=2.470, SmoothL1=1.063 [Epoch 148][Batch 299], Speed: 355.234 samples/sec, CrossEntropy=2.483, SmoothL1=1.067 [Epoch 148][Batch 399], Speed: 351.029 samples/sec, CrossEntropy=2.471, SmoothL1=1.066 [Epoch 148][Batch 499], Speed: 356.972 samples/sec, CrossEntropy=2.469, SmoothL1=1.062 [Epoch 148][Batch 599], Speed: 359.798 samples/sec, CrossEntropy=2.470, SmoothL1=1.064 [Epoch 148][Batch 699], Speed: 356.465 samples/sec, CrossEntropy=2.469, SmoothL1=1.066 [Epoch 148][Batch 799], Speed: 361.621 samples/sec, CrossEntropy=2.472, SmoothL1=1.069 [Epoch 148][Batch 899], Speed: 360.060 samples/sec, CrossEntropy=2.476, SmoothL1=1.071 [Epoch 148][Batch 999], Speed: 341.224 samples/sec, CrossEntropy=2.477, SmoothL1=1.071 [Epoch 148][Batch 1099], Speed: 341.650 samples/sec, CrossEntropy=2.479, SmoothL1=1.072 [Epoch 148][Batch 1199], Speed: 339.759 samples/sec, CrossEntropy=2.482, SmoothL1=1.073 [Epoch 148][Batch 1299], Speed: 347.537 samples/sec, CrossEntropy=2.484, SmoothL1=1.072 [Epoch 148][Batch 1399], Speed: 341.237 samples/sec, CrossEntropy=2.483, SmoothL1=1.072 [Epoch 148][Batch 1499], Speed: 344.913 samples/sec, CrossEntropy=2.477, SmoothL1=1.069 [Epoch 148][Batch 1599], Speed: 357.546 samples/sec, CrossEntropy=2.478, SmoothL1=1.070 [Epoch 148][Batch 1699], Speed: 350.650 samples/sec, CrossEntropy=2.476, SmoothL1=1.070 [Epoch 148][Batch 1799], Speed: 344.680 samples/sec, CrossEntropy=2.473, SmoothL1=1.069 [Epoch 148] Training cost: 334.995, CrossEntropy=2.472, SmoothL1=1.069 [Epoch 148] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.222 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.384 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.041 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.235 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.390 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.216 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.308 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.320 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.069 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.352 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.536 person=32.7 bicycle=14.6 car=18.2 motorcycle=25.5 airplane=41.6 bus=45.8 train=48.5 truck=18.0 boat=9.6 traffic light=7.3 fire hydrant=39.9 stop sign=44.9 parking meter=26.9 bench=11.5 bird=13.5 cat=49.2 dog=44.3 horse=37.1 sheep=29.1 cow=29.2 elephant=41.8 bear=50.0 zebra=45.6 giraffe=45.8 backpack=3.4 umbrella=20.7 handbag=2.5 tie=11.5 suitcase=16.0 frisbee=28.1 skis=8.9 snowboard=11.8 sports ball=15.1 kite=15.1 baseball bat=8.1 baseball glove=11.1 skateboard=24.1 surfboard=16.7 tennis racket=23.6 bottle=11.0 wine glass=11.9 cup=18.0 fork=12.6 knife=4.0 spoon=4.2 bowl=22.8 banana=13.0 apple=10.4 sandwich=24.5 orange=18.4 broccoli=9.8 carrot=8.9 hot dog=18.1 pizza=35.7 donut=23.9 cake=17.6 chair=11.8 couch=29.7 potted plant=11.7 bed=32.5 dining table=21.1 toilet=41.9 tv=38.3 laptop=41.7 mouse=30.2 remote=6.2 keyboard=29.7 cell phone=16.4 microwave=34.0 oven=25.6 toaster=1.8 sink=20.4 refrigerator=34.3 book=4.0 clock=28.5 vase=15.7 scissors=17.0 teddy bear=28.8 hair drier=0.0 toothbrush=4.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.2 [Epoch 149][Batch 99], Speed: 349.556 samples/sec, CrossEntropy=2.481, SmoothL1=1.069 [Epoch 149][Batch 199], Speed: 349.296 samples/sec, CrossEntropy=2.458, SmoothL1=1.057 [Epoch 149][Batch 299], Speed: 350.758 samples/sec, CrossEntropy=2.463, SmoothL1=1.065 [Epoch 149][Batch 399], Speed: 356.379 samples/sec, CrossEntropy=2.469, SmoothL1=1.070 [Epoch 149][Batch 499], Speed: 348.270 samples/sec, CrossEntropy=2.454, SmoothL1=1.061 [Epoch 149][Batch 599], Speed: 347.909 samples/sec, CrossEntropy=2.457, SmoothL1=1.063 [Epoch 149][Batch 699], Speed: 356.602 samples/sec, CrossEntropy=2.456, SmoothL1=1.062 [Epoch 149][Batch 799], Speed: 344.388 samples/sec, CrossEntropy=2.457, SmoothL1=1.060 [Epoch 149][Batch 899], Speed: 352.677 samples/sec, CrossEntropy=2.464, SmoothL1=1.061 [Epoch 149][Batch 999], Speed: 361.551 samples/sec, CrossEntropy=2.472, SmoothL1=1.064 [Epoch 149][Batch 1099], Speed: 359.023 samples/sec, CrossEntropy=2.473, SmoothL1=1.064 [Epoch 149][Batch 1199], Speed: 345.363 samples/sec, CrossEntropy=2.476, SmoothL1=1.063 [Epoch 149][Batch 1299], Speed: 353.045 samples/sec, CrossEntropy=2.481, SmoothL1=1.065 [Epoch 149][Batch 1399], Speed: 351.586 samples/sec, CrossEntropy=2.481, SmoothL1=1.064 [Epoch 149][Batch 1499], Speed: 362.290 samples/sec, CrossEntropy=2.477, SmoothL1=1.062 [Epoch 149][Batch 1599], Speed: 351.725 samples/sec, CrossEntropy=2.478, SmoothL1=1.062 [Epoch 149][Batch 1699], Speed: 354.424 samples/sec, CrossEntropy=2.479, SmoothL1=1.063 [Epoch 149][Batch 1799], Speed: 349.070 samples/sec, CrossEntropy=2.478, SmoothL1=1.062 [Epoch 149] Training cost: 334.881, CrossEntropy=2.478, SmoothL1=1.062 [Epoch 149] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.387 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.238 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.239 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.401 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.219 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.311 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.324 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.066 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.357 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.541 person=32.3 bicycle=14.7 car=18.4 motorcycle=25.9 airplane=45.5 bus=48.3 train=50.2 truck=19.4 boat=9.8 traffic light=7.2 fire hydrant=42.4 stop sign=42.0 parking meter=29.8 bench=11.4 bird=13.4 cat=49.1 dog=42.2 horse=35.4 sheep=31.0 cow=27.9 elephant=45.2 bear=53.0 zebra=45.7 giraffe=46.7 backpack=3.4 umbrella=21.5 handbag=2.6 tie=11.8 suitcase=17.1 frisbee=28.5 skis=8.6 snowboard=10.6 sports ball=14.7 kite=13.8 baseball bat=9.5 baseball glove=12.5 skateboard=24.4 surfboard=17.9 tennis racket=24.5 bottle=10.9 wine glass=12.1 cup=17.9 fork=11.7 knife=4.9 spoon=3.8 bowl=22.1 banana=13.2 apple=10.5 sandwich=28.7 orange=17.3 broccoli=13.4 carrot=10.1 hot dog=21.6 pizza=36.3 donut=24.9 cake=16.9 chair=12.2 couch=31.3 potted plant=11.2 bed=31.6 dining table=20.5 toilet=42.9 tv=40.6 laptop=41.2 mouse=30.3 remote=5.9 keyboard=32.8 cell phone=15.8 microwave=34.1 oven=25.3 toaster=0.0 sink=20.3 refrigerator=34.3 book=4.1 clock=28.3 vase=15.0 scissors=18.7 teddy bear=28.8 hair drier=0.0 toothbrush=5.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.7 [Epoch 150][Batch 99], Speed: 351.370 samples/sec, CrossEntropy=2.435, SmoothL1=1.080 [Epoch 150][Batch 199], Speed: 343.873 samples/sec, CrossEntropy=2.451, SmoothL1=1.063 [Epoch 150][Batch 299], Speed: 348.820 samples/sec, CrossEntropy=2.464, SmoothL1=1.056 [Epoch 150][Batch 399], Speed: 361.355 samples/sec, CrossEntropy=2.464, SmoothL1=1.055 [Epoch 150][Batch 499], Speed: 356.860 samples/sec, CrossEntropy=2.456, SmoothL1=1.053 [Epoch 150][Batch 599], Speed: 343.854 samples/sec, CrossEntropy=2.463, SmoothL1=1.055 [Epoch 150][Batch 699], Speed: 365.458 samples/sec, CrossEntropy=2.466, SmoothL1=1.057 [Epoch 150][Batch 799], Speed: 347.986 samples/sec, CrossEntropy=2.469, SmoothL1=1.055 [Epoch 150][Batch 899], Speed: 347.399 samples/sec, CrossEntropy=2.474, SmoothL1=1.056 [Epoch 150][Batch 999], Speed: 347.994 samples/sec, CrossEntropy=2.473, SmoothL1=1.056 [Epoch 150][Batch 1099], Speed: 350.689 samples/sec, CrossEntropy=2.476, SmoothL1=1.059 [Epoch 150][Batch 1199], Speed: 345.259 samples/sec, CrossEntropy=2.478, SmoothL1=1.059 [Epoch 150][Batch 1299], Speed: 353.279 samples/sec, CrossEntropy=2.474, SmoothL1=1.058 [Epoch 150][Batch 1399], Speed: 360.424 samples/sec, CrossEntropy=2.474, SmoothL1=1.058 [Epoch 150][Batch 1499], Speed: 357.064 samples/sec, CrossEntropy=2.470, SmoothL1=1.055 [Epoch 150][Batch 1599], Speed: 354.367 samples/sec, CrossEntropy=2.469, SmoothL1=1.054 [Epoch 150][Batch 1699], Speed: 356.528 samples/sec, CrossEntropy=2.469, SmoothL1=1.054 [Epoch 150][Batch 1799], Speed: 359.137 samples/sec, CrossEntropy=2.469, SmoothL1=1.055 [Epoch 150] Training cost: 334.616, CrossEntropy=2.470, SmoothL1=1.057 [Epoch 150] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.387 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.240 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.042 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.242 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.407 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.220 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.315 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.328 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.069 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.356 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.563 person=32.4 bicycle=15.7 car=19.2 motorcycle=26.4 airplane=43.3 bus=46.1 train=50.9 truck=20.1 boat=10.5 traffic light=6.7 fire hydrant=40.2 stop sign=43.2 parking meter=26.3 bench=12.1 bird=13.8 cat=49.9 dog=42.2 horse=37.9 sheep=29.6 cow=29.2 elephant=42.3 bear=49.1 zebra=46.7 giraffe=46.5 backpack=2.7 umbrella=22.0 handbag=2.7 tie=13.4 suitcase=15.1 frisbee=31.3 skis=10.5 snowboard=9.5 sports ball=16.8 kite=14.0 baseball bat=9.4 baseball glove=11.1 skateboard=24.1 surfboard=16.6 tennis racket=23.3 bottle=11.6 wine glass=12.1 cup=17.0 fork=11.3 knife=4.4 spoon=2.7 bowl=21.9 banana=14.2 apple=10.3 sandwich=27.6 orange=19.0 broccoli=14.0 carrot=10.8 hot dog=19.5 pizza=33.8 donut=24.8 cake=17.5 chair=11.7 couch=30.6 potted plant=11.1 bed=29.9 dining table=19.7 toilet=43.9 tv=39.5 laptop=40.7 mouse=28.0 remote=6.6 keyboard=31.0 cell phone=14.6 microwave=34.8 oven=25.6 toaster=12.2 sink=18.8 refrigerator=34.4 book=3.9 clock=29.3 vase=14.3 scissors=19.7 teddy bear=29.5 hair drier=7.9 toothbrush=6.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.7 [Epoch 151][Batch 99], Speed: 348.894 samples/sec, CrossEntropy=2.451, SmoothL1=1.052 [Epoch 151][Batch 199], Speed: 353.578 samples/sec, CrossEntropy=2.471, SmoothL1=1.060 [Epoch 151][Batch 299], Speed: 355.943 samples/sec, CrossEntropy=2.469, SmoothL1=1.059 [Epoch 151][Batch 399], Speed: 349.835 samples/sec, CrossEntropy=2.476, SmoothL1=1.069 [Epoch 151][Batch 499], Speed: 360.158 samples/sec, CrossEntropy=2.478, SmoothL1=1.070 [Epoch 151][Batch 599], Speed: 354.293 samples/sec, CrossEntropy=2.486, SmoothL1=1.069 [Epoch 151][Batch 699], Speed: 347.832 samples/sec, CrossEntropy=2.485, SmoothL1=1.067 [Epoch 151][Batch 799], Speed: 347.421 samples/sec, CrossEntropy=2.484, SmoothL1=1.068 [Epoch 151][Batch 899], Speed: 349.664 samples/sec, CrossEntropy=2.484, SmoothL1=1.067 [Epoch 151][Batch 999], Speed: 360.705 samples/sec, CrossEntropy=2.484, SmoothL1=1.068 [Epoch 151][Batch 1099], Speed: 357.391 samples/sec, CrossEntropy=2.482, SmoothL1=1.066 [Epoch 151][Batch 1199], Speed: 361.015 samples/sec, CrossEntropy=2.478, SmoothL1=1.064 [Epoch 151][Batch 1299], Speed: 354.246 samples/sec, CrossEntropy=2.478, SmoothL1=1.065 [Epoch 151][Batch 1399], Speed: 349.497 samples/sec, CrossEntropy=2.476, SmoothL1=1.065 [Epoch 151][Batch 1499], Speed: 352.958 samples/sec, CrossEntropy=2.473, SmoothL1=1.063 [Epoch 151][Batch 1599], Speed: 356.410 samples/sec, CrossEntropy=2.471, SmoothL1=1.064 [Epoch 151][Batch 1699], Speed: 353.142 samples/sec, CrossEntropy=2.467, SmoothL1=1.061 [Epoch 151][Batch 1799], Speed: 363.109 samples/sec, CrossEntropy=2.467, SmoothL1=1.062 [Epoch 151] Training cost: 335.114, CrossEntropy=2.466, SmoothL1=1.061 [Epoch 151] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.222 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.385 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.229 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.041 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.234 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.390 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.307 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.319 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.069 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.343 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.540 person=32.2 bicycle=15.2 car=17.3 motorcycle=25.4 airplane=43.1 bus=46.1 train=47.9 truck=17.8 boat=9.8 traffic light=7.0 fire hydrant=42.7 stop sign=40.9 parking meter=24.6 bench=12.3 bird=13.8 cat=47.7 dog=43.8 horse=35.0 sheep=30.0 cow=29.2 elephant=42.8 bear=51.6 zebra=46.6 giraffe=46.0 backpack=3.5 umbrella=19.5 handbag=2.6 tie=12.4 suitcase=16.8 frisbee=28.0 skis=10.7 snowboard=7.9 sports ball=16.7 kite=14.6 baseball bat=9.6 baseball glove=11.4 skateboard=24.3 surfboard=15.5 tennis racket=23.5 bottle=11.4 wine glass=11.2 cup=16.7 fork=12.6 knife=5.0 spoon=4.4 bowl=22.1 banana=14.0 apple=10.2 sandwich=27.4 orange=16.2 broccoli=11.8 carrot=8.3 hot dog=21.5 pizza=34.0 donut=21.7 cake=18.6 chair=11.1 couch=32.0 potted plant=11.8 bed=30.1 dining table=20.1 toilet=42.7 tv=39.6 laptop=41.5 mouse=28.6 remote=5.6 keyboard=30.4 cell phone=15.1 microwave=34.5 oven=24.8 toaster=2.4 sink=20.0 refrigerator=35.5 book=3.7 clock=28.2 vase=14.5 scissors=16.8 teddy bear=29.1 hair drier=0.0 toothbrush=3.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.2 [Epoch 152][Batch 99], Speed: 358.869 samples/sec, CrossEntropy=2.497, SmoothL1=1.073 [Epoch 152][Batch 199], Speed: 337.980 samples/sec, CrossEntropy=2.496, SmoothL1=1.067 [Epoch 152][Batch 299], Speed: 338.975 samples/sec, CrossEntropy=2.479, SmoothL1=1.055 [Epoch 152][Batch 399], Speed: 349.760 samples/sec, CrossEntropy=2.482, SmoothL1=1.061 [Epoch 152][Batch 499], Speed: 358.813 samples/sec, CrossEntropy=2.482, SmoothL1=1.067 [Epoch 152][Batch 599], Speed: 348.304 samples/sec, CrossEntropy=2.482, SmoothL1=1.070 [Epoch 152][Batch 699], Speed: 364.339 samples/sec, CrossEntropy=2.482, SmoothL1=1.071 [Epoch 152][Batch 799], Speed: 362.593 samples/sec, CrossEntropy=2.478, SmoothL1=1.069 [Epoch 152][Batch 899], Speed: 343.573 samples/sec, CrossEntropy=2.480, SmoothL1=1.069 [Epoch 152][Batch 999], Speed: 353.840 samples/sec, CrossEntropy=2.480, SmoothL1=1.066 [Epoch 152][Batch 1099], Speed: 359.354 samples/sec, CrossEntropy=2.480, SmoothL1=1.067 [Epoch 152][Batch 1199], Speed: 347.042 samples/sec, CrossEntropy=2.481, SmoothL1=1.067 [Epoch 152][Batch 1299], Speed: 342.474 samples/sec, CrossEntropy=2.477, SmoothL1=1.065 [Epoch 152][Batch 1399], Speed: 358.708 samples/sec, CrossEntropy=2.474, SmoothL1=1.064 [Epoch 152][Batch 1499], Speed: 348.810 samples/sec, CrossEntropy=2.473, SmoothL1=1.067 [Epoch 152][Batch 1599], Speed: 354.438 samples/sec, CrossEntropy=2.470, SmoothL1=1.065 [Epoch 152][Batch 1699], Speed: 342.443 samples/sec, CrossEntropy=2.469, SmoothL1=1.066 [Epoch 152][Batch 1799], Speed: 345.780 samples/sec, CrossEntropy=2.467, SmoothL1=1.064 [Epoch 152] Training cost: 334.907, CrossEntropy=2.467, SmoothL1=1.063 [Epoch 152] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.224 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.385 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.232 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.241 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.390 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.306 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.320 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.350 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.538 person=32.4 bicycle=15.9 car=18.1 motorcycle=26.4 airplane=39.7 bus=48.7 train=48.9 truck=18.6 boat=10.2 traffic light=6.8 fire hydrant=42.8 stop sign=42.4 parking meter=25.1 bench=11.6 bird=14.3 cat=48.4 dog=42.2 horse=37.9 sheep=29.3 cow=29.0 elephant=43.5 bear=50.3 zebra=45.0 giraffe=44.9 backpack=3.5 umbrella=20.8 handbag=2.6 tie=12.4 suitcase=15.3 frisbee=29.0 skis=10.4 snowboard=11.2 sports ball=17.9 kite=15.4 baseball bat=9.1 baseball glove=11.4 skateboard=23.5 surfboard=15.9 tennis racket=24.5 bottle=11.1 wine glass=11.5 cup=17.8 fork=12.7 knife=4.6 spoon=4.3 bowl=21.9 banana=13.0 apple=9.5 sandwich=25.7 orange=19.4 broccoli=13.9 carrot=8.6 hot dog=18.8 pizza=35.8 donut=24.0 cake=17.3 chair=11.4 couch=31.3 potted plant=13.1 bed=29.8 dining table=20.5 toilet=40.7 tv=38.7 laptop=40.6 mouse=32.3 remote=5.4 keyboard=30.8 cell phone=13.9 microwave=31.9 oven=23.9 toaster=5.9 sink=21.2 refrigerator=30.3 book=3.9 clock=27.7 vase=15.8 scissors=18.1 teddy bear=30.5 hair drier=0.0 toothbrush=5.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.4 [Epoch 153][Batch 99], Speed: 360.467 samples/sec, CrossEntropy=2.489, SmoothL1=1.052 [Epoch 153][Batch 199], Speed: 364.245 samples/sec, CrossEntropy=2.466, SmoothL1=1.064 [Epoch 153][Batch 299], Speed: 345.880 samples/sec, CrossEntropy=2.482, SmoothL1=1.067 [Epoch 153][Batch 399], Speed: 362.118 samples/sec, CrossEntropy=2.484, SmoothL1=1.073 [Epoch 153][Batch 499], Speed: 345.277 samples/sec, CrossEntropy=2.480, SmoothL1=1.069 [Epoch 153][Batch 599], Speed: 362.032 samples/sec, CrossEntropy=2.481, SmoothL1=1.067 [Epoch 153][Batch 699], Speed: 352.716 samples/sec, CrossEntropy=2.479, SmoothL1=1.068 [Epoch 153][Batch 799], Speed: 341.165 samples/sec, CrossEntropy=2.476, SmoothL1=1.065 [Epoch 153][Batch 899], Speed: 360.261 samples/sec, CrossEntropy=2.473, SmoothL1=1.068 [Epoch 153][Batch 999], Speed: 364.931 samples/sec, CrossEntropy=2.472, SmoothL1=1.068 [Epoch 153][Batch 1099], Speed: 357.148 samples/sec, CrossEntropy=2.474, SmoothL1=1.067 [Epoch 153][Batch 1199], Speed: 351.133 samples/sec, CrossEntropy=2.473, SmoothL1=1.066 [Epoch 153][Batch 1299], Speed: 361.597 samples/sec, CrossEntropy=2.470, SmoothL1=1.067 [Epoch 153][Batch 1399], Speed: 355.886 samples/sec, CrossEntropy=2.465, SmoothL1=1.064 [Epoch 153][Batch 1499], Speed: 361.021 samples/sec, CrossEntropy=2.467, SmoothL1=1.065 [Epoch 153][Batch 1599], Speed: 362.415 samples/sec, CrossEntropy=2.466, SmoothL1=1.064 [Epoch 153][Batch 1699], Speed: 350.542 samples/sec, CrossEntropy=2.466, SmoothL1=1.065 [Epoch 153][Batch 1799], Speed: 342.896 samples/sec, CrossEntropy=2.465, SmoothL1=1.065 [Epoch 153] Training cost: 334.171, CrossEntropy=2.466, SmoothL1=1.065 [Epoch 153] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.219 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.378 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.234 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.395 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.215 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.306 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.318 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.066 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.543 person=32.0 bicycle=13.5 car=18.2 motorcycle=23.9 airplane=43.3 bus=47.0 train=49.1 truck=17.7 boat=10.1 traffic light=6.6 fire hydrant=40.3 stop sign=42.5 parking meter=25.1 bench=11.3 bird=13.0 cat=49.1 dog=40.1 horse=36.7 sheep=28.1 cow=28.1 elephant=41.7 bear=47.0 zebra=44.7 giraffe=44.4 backpack=4.0 umbrella=21.3 handbag=3.7 tie=11.7 suitcase=15.8 frisbee=28.1 skis=9.7 snowboard=10.1 sports ball=16.4 kite=14.4 baseball bat=9.6 baseball glove=12.3 skateboard=25.1 surfboard=17.3 tennis racket=22.8 bottle=10.7 wine glass=11.5 cup=16.6 fork=12.5 knife=5.3 spoon=4.8 bowl=23.2 banana=12.0 apple=8.6 sandwich=23.4 orange=15.5 broccoli=13.0 carrot=8.4 hot dog=19.4 pizza=34.1 donut=23.3 cake=18.3 chair=10.9 couch=30.6 potted plant=11.2 bed=31.2 dining table=20.1 toilet=41.5 tv=38.9 laptop=40.1 mouse=26.8 remote=6.3 keyboard=30.2 cell phone=15.6 microwave=32.3 oven=23.4 toaster=7.0 sink=20.1 refrigerator=34.2 book=3.9 clock=27.7 vase=14.6 scissors=17.8 teddy bear=27.5 hair drier=0.0 toothbrush=5.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =21.9 [Epoch 154][Batch 99], Speed: 360.449 samples/sec, CrossEntropy=2.473, SmoothL1=1.049 [Epoch 154][Batch 199], Speed: 355.085 samples/sec, CrossEntropy=2.485, SmoothL1=1.061 [Epoch 154][Batch 299], Speed: 353.487 samples/sec, CrossEntropy=2.487, SmoothL1=1.053 [Epoch 154][Batch 399], Speed: 350.720 samples/sec, CrossEntropy=2.480, SmoothL1=1.052 [Epoch 154][Batch 499], Speed: 346.876 samples/sec, CrossEntropy=2.475, SmoothL1=1.056 [Epoch 154][Batch 599], Speed: 345.339 samples/sec, CrossEntropy=2.473, SmoothL1=1.058 [Epoch 154][Batch 699], Speed: 362.592 samples/sec, CrossEntropy=2.477, SmoothL1=1.058 [Epoch 154][Batch 799], Speed: 351.577 samples/sec, CrossEntropy=2.474, SmoothL1=1.058 [Epoch 154][Batch 899], Speed: 344.742 samples/sec, CrossEntropy=2.476, SmoothL1=1.060 [Epoch 154][Batch 999], Speed: 354.006 samples/sec, CrossEntropy=2.474, SmoothL1=1.060 [Epoch 154][Batch 1099], Speed: 341.127 samples/sec, CrossEntropy=2.472, SmoothL1=1.060 [Epoch 154][Batch 1199], Speed: 345.713 samples/sec, CrossEntropy=2.475, SmoothL1=1.059 [Epoch 154][Batch 1299], Speed: 355.171 samples/sec, CrossEntropy=2.472, SmoothL1=1.057 [Epoch 154][Batch 1399], Speed: 349.574 samples/sec, CrossEntropy=2.471, SmoothL1=1.056 [Epoch 154][Batch 1499], Speed: 354.790 samples/sec, CrossEntropy=2.466, SmoothL1=1.053 [Epoch 154][Batch 1599], Speed: 343.043 samples/sec, CrossEntropy=2.465, SmoothL1=1.053 [Epoch 154][Batch 1699], Speed: 346.288 samples/sec, CrossEntropy=2.460, SmoothL1=1.053 [Epoch 154][Batch 1799], Speed: 357.929 samples/sec, CrossEntropy=2.460, SmoothL1=1.054 [Epoch 154] Training cost: 336.520, CrossEntropy=2.462, SmoothL1=1.056 [Epoch 154] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.390 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.236 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.044 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.239 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.405 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.219 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.312 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.325 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.071 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.357 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.555 person=32.1 bicycle=16.1 car=18.3 motorcycle=24.8 airplane=42.7 bus=47.5 train=50.2 truck=20.1 boat=10.1 traffic light=7.5 fire hydrant=38.2 stop sign=41.9 parking meter=29.6 bench=12.2 bird=13.5 cat=50.7 dog=43.9 horse=36.1 sheep=28.4 cow=29.4 elephant=41.8 bear=50.0 zebra=46.0 giraffe=45.7 backpack=3.4 umbrella=21.6 handbag=3.0 tie=12.5 suitcase=16.7 frisbee=28.6 skis=9.2 snowboard=9.4 sports ball=16.4 kite=14.5 baseball bat=8.4 baseball glove=12.0 skateboard=24.0 surfboard=18.4 tennis racket=25.0 bottle=11.9 wine glass=11.6 cup=17.9 fork=12.9 knife=4.4 spoon=3.0 bowl=23.8 banana=12.9 apple=9.8 sandwich=26.6 orange=16.0 broccoli=12.2 carrot=8.2 hot dog=20.7 pizza=34.5 donut=24.2 cake=19.3 chair=11.3 couch=31.6 potted plant=11.4 bed=32.4 dining table=21.8 toilet=42.5 tv=39.8 laptop=42.4 mouse=29.1 remote=7.1 keyboard=28.6 cell phone=15.6 microwave=35.1 oven=25.7 toaster=12.7 sink=20.4 refrigerator=32.3 book=4.3 clock=28.1 vase=16.0 scissors=20.6 teddy bear=29.7 hair drier=0.0 toothbrush=7.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.7 [Epoch 155][Batch 99], Speed: 356.454 samples/sec, CrossEntropy=2.432, SmoothL1=1.036 [Epoch 155][Batch 199], Speed: 347.050 samples/sec, CrossEntropy=2.451, SmoothL1=1.042 [Epoch 155][Batch 299], Speed: 355.818 samples/sec, CrossEntropy=2.453, SmoothL1=1.047 [Epoch 155][Batch 399], Speed: 355.018 samples/sec, CrossEntropy=2.451, SmoothL1=1.043 [Epoch 155][Batch 499], Speed: 343.364 samples/sec, CrossEntropy=2.458, SmoothL1=1.049 [Epoch 155][Batch 599], Speed: 352.327 samples/sec, CrossEntropy=2.463, SmoothL1=1.050 [Epoch 155][Batch 699], Speed: 344.535 samples/sec, CrossEntropy=2.458, SmoothL1=1.045 [Epoch 155][Batch 799], Speed: 348.147 samples/sec, CrossEntropy=2.464, SmoothL1=1.048 [Epoch 155][Batch 899], Speed: 353.738 samples/sec, CrossEntropy=2.466, SmoothL1=1.050 [Epoch 155][Batch 999], Speed: 352.642 samples/sec, CrossEntropy=2.469, SmoothL1=1.050 [Epoch 155][Batch 1099], Speed: 363.477 samples/sec, CrossEntropy=2.472, SmoothL1=1.054 [Epoch 155][Batch 1199], Speed: 349.447 samples/sec, CrossEntropy=2.472, SmoothL1=1.052 [Epoch 155][Batch 1299], Speed: 358.340 samples/sec, CrossEntropy=2.471, SmoothL1=1.053 [Epoch 155][Batch 1399], Speed: 357.210 samples/sec, CrossEntropy=2.471, SmoothL1=1.053 [Epoch 155][Batch 1499], Speed: 349.618 samples/sec, CrossEntropy=2.471, SmoothL1=1.052 [Epoch 155][Batch 1599], Speed: 353.469 samples/sec, CrossEntropy=2.470, SmoothL1=1.053 [Epoch 155][Batch 1699], Speed: 357.661 samples/sec, CrossEntropy=2.471, SmoothL1=1.054 [Epoch 155][Batch 1799], Speed: 350.285 samples/sec, CrossEntropy=2.473, SmoothL1=1.056 [Epoch 155] Training cost: 336.012, CrossEntropy=2.472, SmoothL1=1.056 [Epoch 155] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.229 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.389 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.242 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.044 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.240 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.404 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.218 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.312 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.324 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.069 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.354 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.547 person=32.7 bicycle=15.9 car=18.7 motorcycle=25.6 airplane=42.3 bus=47.9 train=50.0 truck=19.8 boat=10.5 traffic light=8.0 fire hydrant=42.0 stop sign=43.9 parking meter=26.7 bench=12.8 bird=14.3 cat=50.5 dog=42.5 horse=38.2 sheep=28.3 cow=29.3 elephant=43.5 bear=54.0 zebra=45.8 giraffe=48.0 backpack=3.3 umbrella=20.4 handbag=2.9 tie=12.7 suitcase=16.0 frisbee=28.4 skis=9.8 snowboard=9.9 sports ball=17.4 kite=14.8 baseball bat=9.1 baseball glove=11.5 skateboard=23.2 surfboard=17.6 tennis racket=25.1 bottle=12.0 wine glass=11.9 cup=17.8 fork=14.8 knife=4.8 spoon=5.0 bowl=22.9 banana=14.6 apple=10.1 sandwich=26.6 orange=21.4 broccoli=13.1 carrot=9.2 hot dog=19.4 pizza=33.3 donut=23.9 cake=17.4 chair=12.1 couch=30.7 potted plant=13.4 bed=31.4 dining table=21.3 toilet=41.4 tv=40.1 laptop=41.7 mouse=28.2 remote=5.8 keyboard=30.7 cell phone=15.8 microwave=37.0 oven=26.2 toaster=6.7 sink=21.3 refrigerator=36.5 book=4.3 clock=27.3 vase=15.3 scissors=18.5 teddy bear=30.9 hair drier=0.0 toothbrush=5.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.9 [Epoch 156][Batch 99], Speed: 356.487 samples/sec, CrossEntropy=2.418, SmoothL1=1.049 [Epoch 156][Batch 199], Speed: 353.578 samples/sec, CrossEntropy=2.423, SmoothL1=1.042 [Epoch 156][Batch 299], Speed: 361.565 samples/sec, CrossEntropy=2.456, SmoothL1=1.054 [Epoch 156][Batch 399], Speed: 356.867 samples/sec, CrossEntropy=2.470, SmoothL1=1.061 [Epoch 156][Batch 499], Speed: 362.487 samples/sec, CrossEntropy=2.463, SmoothL1=1.061 [Epoch 156][Batch 599], Speed: 357.752 samples/sec, CrossEntropy=2.464, SmoothL1=1.064 [Epoch 156][Batch 699], Speed: 356.274 samples/sec, CrossEntropy=2.464, SmoothL1=1.068 [Epoch 156][Batch 799], Speed: 363.942 samples/sec, CrossEntropy=2.468, SmoothL1=1.067 [Epoch 156][Batch 899], Speed: 345.818 samples/sec, CrossEntropy=2.469, SmoothL1=1.066 [Epoch 156][Batch 999], Speed: 350.371 samples/sec, CrossEntropy=2.471, SmoothL1=1.064 [Epoch 156][Batch 1099], Speed: 354.572 samples/sec, CrossEntropy=2.475, SmoothL1=1.065 [Epoch 156][Batch 1199], Speed: 360.498 samples/sec, CrossEntropy=2.473, SmoothL1=1.066 [Epoch 156][Batch 1299], Speed: 362.526 samples/sec, CrossEntropy=2.471, SmoothL1=1.065 [Epoch 156][Batch 1399], Speed: 342.983 samples/sec, CrossEntropy=2.471, SmoothL1=1.064 [Epoch 156][Batch 1499], Speed: 352.909 samples/sec, CrossEntropy=2.469, SmoothL1=1.062 [Epoch 156][Batch 1599], Speed: 360.731 samples/sec, CrossEntropy=2.466, SmoothL1=1.061 [Epoch 156][Batch 1699], Speed: 358.421 samples/sec, CrossEntropy=2.464, SmoothL1=1.060 [Epoch 156][Batch 1799], Speed: 348.749 samples/sec, CrossEntropy=2.463, SmoothL1=1.060 [Epoch 156] Training cost: 335.426, CrossEntropy=2.463, SmoothL1=1.061 [Epoch 156] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.225 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.388 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.237 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.044 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.238 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.393 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.218 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.312 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.324 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.072 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.359 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.539 person=32.6 bicycle=15.6 car=18.3 motorcycle=25.5 airplane=42.5 bus=44.8 train=51.9 truck=18.7 boat=9.7 traffic light=7.0 fire hydrant=41.3 stop sign=41.0 parking meter=26.1 bench=12.0 bird=13.1 cat=48.7 dog=42.9 horse=37.1 sheep=29.2 cow=28.7 elephant=44.8 bear=50.3 zebra=47.1 giraffe=45.8 backpack=3.1 umbrella=20.4 handbag=3.0 tie=13.1 suitcase=15.9 frisbee=28.6 skis=9.6 snowboard=8.1 sports ball=16.8 kite=14.5 baseball bat=9.3 baseball glove=10.3 skateboard=24.0 surfboard=16.6 tennis racket=24.1 bottle=10.8 wine glass=12.5 cup=18.2 fork=12.6 knife=5.2 spoon=4.2 bowl=22.5 banana=9.7 apple=8.3 sandwich=25.5 orange=18.8 broccoli=13.7 carrot=9.1 hot dog=20.6 pizza=33.1 donut=24.6 cake=18.9 chair=11.2 couch=30.6 potted plant=11.6 bed=32.1 dining table=20.4 toilet=41.7 tv=38.1 laptop=40.2 mouse=29.6 remote=6.0 keyboard=32.4 cell phone=14.8 microwave=34.9 oven=25.5 toaster=14.4 sink=20.2 refrigerator=38.6 book=4.5 clock=29.3 vase=14.8 scissors=17.5 teddy bear=28.4 hair drier=0.0 toothbrush=5.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.5 [Epoch 157][Batch 99], Speed: 351.796 samples/sec, CrossEntropy=2.494, SmoothL1=1.069 [Epoch 157][Batch 199], Speed: 357.278 samples/sec, CrossEntropy=2.476, SmoothL1=1.067 [Epoch 157][Batch 299], Speed: 359.320 samples/sec, CrossEntropy=2.482, SmoothL1=1.074 [Epoch 157][Batch 399], Speed: 350.830 samples/sec, CrossEntropy=2.467, SmoothL1=1.064 [Epoch 157][Batch 499], Speed: 344.516 samples/sec, CrossEntropy=2.457, SmoothL1=1.060 [Epoch 157][Batch 599], Speed: 354.528 samples/sec, CrossEntropy=2.465, SmoothL1=1.060 [Epoch 157][Batch 699], Speed: 353.589 samples/sec, CrossEntropy=2.468, SmoothL1=1.061 [Epoch 157][Batch 799], Speed: 357.412 samples/sec, CrossEntropy=2.468, SmoothL1=1.056 [Epoch 157][Batch 899], Speed: 364.257 samples/sec, CrossEntropy=2.469, SmoothL1=1.054 [Epoch 157][Batch 999], Speed: 355.961 samples/sec, CrossEntropy=2.468, SmoothL1=1.055 [Epoch 157][Batch 1099], Speed: 358.957 samples/sec, CrossEntropy=2.465, SmoothL1=1.055 [Epoch 157][Batch 1199], Speed: 347.995 samples/sec, CrossEntropy=2.465, SmoothL1=1.055 [Epoch 157][Batch 1299], Speed: 357.353 samples/sec, CrossEntropy=2.464, SmoothL1=1.054 [Epoch 157][Batch 1399], Speed: 349.856 samples/sec, CrossEntropy=2.464, SmoothL1=1.052 [Epoch 157][Batch 1499], Speed: 345.710 samples/sec, CrossEntropy=2.463, SmoothL1=1.051 [Epoch 157][Batch 1599], Speed: 351.223 samples/sec, CrossEntropy=2.461, SmoothL1=1.050 [Epoch 157][Batch 1699], Speed: 349.514 samples/sec, CrossEntropy=2.462, SmoothL1=1.051 [Epoch 157][Batch 1799], Speed: 359.822 samples/sec, CrossEntropy=2.461, SmoothL1=1.049 [Epoch 157] Training cost: 335.062, CrossEntropy=2.459, SmoothL1=1.048 [Epoch 157] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.222 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.381 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.232 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.041 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.236 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.390 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.217 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.308 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.321 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.067 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.352 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.539 person=32.2 bicycle=15.6 car=18.8 motorcycle=25.2 airplane=39.5 bus=45.6 train=47.4 truck=18.4 boat=10.6 traffic light=6.7 fire hydrant=41.6 stop sign=42.4 parking meter=30.0 bench=11.7 bird=14.0 cat=48.9 dog=43.0 horse=37.1 sheep=28.9 cow=26.8 elephant=41.3 bear=46.2 zebra=46.1 giraffe=45.1 backpack=3.8 umbrella=21.0 handbag=2.9 tie=12.3 suitcase=15.2 frisbee=25.0 skis=9.6 snowboard=8.9 sports ball=15.7 kite=13.5 baseball bat=9.1 baseball glove=11.7 skateboard=24.7 surfboard=17.7 tennis racket=23.2 bottle=11.2 wine glass=12.3 cup=17.4 fork=10.9 knife=4.1 spoon=3.3 bowl=23.1 banana=11.3 apple=9.5 sandwich=25.1 orange=18.0 broccoli=11.5 carrot=8.7 hot dog=21.2 pizza=35.5 donut=24.9 cake=19.0 chair=10.5 couch=30.1 potted plant=12.9 bed=34.7 dining table=20.5 toilet=45.0 tv=40.2 laptop=41.4 mouse=29.2 remote=6.3 keyboard=30.8 cell phone=14.6 microwave=32.5 oven=25.0 toaster=8.3 sink=19.7 refrigerator=33.9 book=3.8 clock=27.8 vase=15.5 scissors=17.5 teddy bear=29.6 hair drier=0.0 toothbrush=4.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.2 [Epoch 158][Batch 99], Speed: 349.579 samples/sec, CrossEntropy=2.432, SmoothL1=1.077 [Epoch 158][Batch 199], Speed: 360.894 samples/sec, CrossEntropy=2.433, SmoothL1=1.064 [Epoch 158][Batch 299], Speed: 347.248 samples/sec, CrossEntropy=2.441, SmoothL1=1.054 [Epoch 158][Batch 399], Speed: 352.036 samples/sec, CrossEntropy=2.449, SmoothL1=1.063 [Epoch 158][Batch 499], Speed: 345.571 samples/sec, CrossEntropy=2.440, SmoothL1=1.055 [Epoch 158][Batch 599], Speed: 345.948 samples/sec, CrossEntropy=2.438, SmoothL1=1.054 [Epoch 158][Batch 699], Speed: 357.622 samples/sec, CrossEntropy=2.444, SmoothL1=1.056 [Epoch 158][Batch 799], Speed: 358.733 samples/sec, CrossEntropy=2.455, SmoothL1=1.060 [Epoch 158][Batch 899], Speed: 347.781 samples/sec, CrossEntropy=2.456, SmoothL1=1.059 [Epoch 158][Batch 999], Speed: 344.944 samples/sec, CrossEntropy=2.454, SmoothL1=1.059 [Epoch 158][Batch 1099], Speed: 358.640 samples/sec, CrossEntropy=2.456, SmoothL1=1.060 [Epoch 158][Batch 1199], Speed: 354.467 samples/sec, CrossEntropy=2.453, SmoothL1=1.057 [Epoch 158][Batch 1299], Speed: 346.110 samples/sec, CrossEntropy=2.451, SmoothL1=1.057 [Epoch 158][Batch 1399], Speed: 354.179 samples/sec, CrossEntropy=2.447, SmoothL1=1.055 [Epoch 158][Batch 1499], Speed: 351.570 samples/sec, CrossEntropy=2.446, SmoothL1=1.055 [Epoch 158][Batch 1599], Speed: 343.732 samples/sec, CrossEntropy=2.447, SmoothL1=1.053 [Epoch 158][Batch 1699], Speed: 353.377 samples/sec, CrossEntropy=2.448, SmoothL1=1.055 [Epoch 158][Batch 1799], Speed: 353.981 samples/sec, CrossEntropy=2.451, SmoothL1=1.058 [Epoch 158] Training cost: 334.920, CrossEntropy=2.452, SmoothL1=1.058 [Epoch 158] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.223 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.384 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.232 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.043 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.239 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.385 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.216 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.309 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.323 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.073 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.354 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.530 person=32.4 bicycle=15.8 car=18.5 motorcycle=25.1 airplane=40.6 bus=44.5 train=50.1 truck=19.7 boat=10.7 traffic light=6.4 fire hydrant=40.6 stop sign=44.0 parking meter=25.8 bench=11.3 bird=14.8 cat=50.8 dog=43.7 horse=37.6 sheep=28.9 cow=28.9 elephant=42.7 bear=50.0 zebra=46.6 giraffe=48.1 backpack=2.7 umbrella=17.1 handbag=3.3 tie=11.9 suitcase=15.8 frisbee=28.1 skis=8.9 snowboard=9.8 sports ball=17.4 kite=14.8 baseball bat=8.5 baseball glove=12.8 skateboard=23.0 surfboard=17.9 tennis racket=24.3 bottle=11.4 wine glass=11.3 cup=17.4 fork=13.3 knife=4.1 spoon=3.3 bowl=22.4 banana=12.9 apple=10.2 sandwich=23.9 orange=19.5 broccoli=14.2 carrot=8.3 hot dog=19.7 pizza=35.4 donut=24.2 cake=19.4 chair=11.3 couch=30.8 potted plant=12.3 bed=31.4 dining table=21.0 toilet=41.6 tv=38.0 laptop=39.2 mouse=31.8 remote=6.2 keyboard=27.5 cell phone=14.3 microwave=32.5 oven=23.8 toaster=0.0 sink=21.0 refrigerator=35.5 book=4.2 clock=28.5 vase=15.2 scissors=20.2 teddy bear=29.6 hair drier=0.0 toothbrush=6.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.3 [Epoch 159][Batch 99], Speed: 353.765 samples/sec, CrossEntropy=2.430, SmoothL1=1.046 [Epoch 159][Batch 199], Speed: 363.624 samples/sec, CrossEntropy=2.421, SmoothL1=1.046 [Epoch 159][Batch 299], Speed: 341.443 samples/sec, CrossEntropy=2.424, SmoothL1=1.043 [Epoch 159][Batch 399], Speed: 353.164 samples/sec, CrossEntropy=2.432, SmoothL1=1.046 [Epoch 159][Batch 499], Speed: 345.360 samples/sec, CrossEntropy=2.443, SmoothL1=1.046 [Epoch 159][Batch 599], Speed: 356.427 samples/sec, CrossEntropy=2.459, SmoothL1=1.051 [Epoch 159][Batch 699], Speed: 352.480 samples/sec, CrossEntropy=2.464, SmoothL1=1.054 [Epoch 159][Batch 799], Speed: 358.860 samples/sec, CrossEntropy=2.465, SmoothL1=1.056 [Epoch 159][Batch 899], Speed: 359.324 samples/sec, CrossEntropy=2.465, SmoothL1=1.057 [Epoch 159][Batch 999], Speed: 353.041 samples/sec, CrossEntropy=2.462, SmoothL1=1.057 [Epoch 159][Batch 1099], Speed: 347.159 samples/sec, CrossEntropy=2.465, SmoothL1=1.056 [Epoch 159][Batch 1199], Speed: 354.659 samples/sec, CrossEntropy=2.468, SmoothL1=1.058 [Epoch 159][Batch 1299], Speed: 361.388 samples/sec, CrossEntropy=2.466, SmoothL1=1.058 [Epoch 159][Batch 1399], Speed: 353.073 samples/sec, CrossEntropy=2.466, SmoothL1=1.058 [Epoch 159][Batch 1499], Speed: 353.038 samples/sec, CrossEntropy=2.463, SmoothL1=1.057 [Epoch 159][Batch 1599], Speed: 348.821 samples/sec, CrossEntropy=2.462, SmoothL1=1.057 [Epoch 159][Batch 1699], Speed: 362.317 samples/sec, CrossEntropy=2.464, SmoothL1=1.059 [Epoch 159][Batch 1799], Speed: 360.306 samples/sec, CrossEntropy=2.462, SmoothL1=1.058 [Epoch 160] Set learning rate to 0.0001 [Epoch 160] Set learning rate to 0.0001 [Epoch 160] Set learning rate to 0.0001 [Epoch 159] Training cost: 335.024, CrossEntropy=2.463, SmoothL1=1.059 [Epoch 159] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.227 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.388 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.236 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.042 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.238 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.401 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.217 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.311 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.323 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.069 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.554 person=32.7 bicycle=15.5 car=18.9 motorcycle=26.1 airplane=41.0 bus=46.8 train=51.0 truck=17.9 boat=9.3 traffic light=7.0 fire hydrant=40.7 stop sign=43.9 parking meter=30.4 bench=12.1 bird=14.3 cat=51.1 dog=43.2 horse=37.6 sheep=28.4 cow=29.9 elephant=42.8 bear=52.0 zebra=45.9 giraffe=48.2 backpack=3.2 umbrella=19.8 handbag=3.2 tie=11.6 suitcase=16.0 frisbee=28.1 skis=10.0 snowboard=10.0 sports ball=16.4 kite=15.2 baseball bat=8.9 baseball glove=12.2 skateboard=25.3 surfboard=17.3 tennis racket=24.4 bottle=11.5 wine glass=11.5 cup=16.6 fork=13.0 knife=3.4 spoon=3.7 bowl=22.5 banana=13.7 apple=7.5 sandwich=24.3 orange=20.3 broccoli=13.5 carrot=9.4 hot dog=20.3 pizza=33.9 donut=25.3 cake=14.8 chair=10.8 couch=31.7 potted plant=12.7 bed=31.1 dining table=19.2 toilet=43.0 tv=39.5 laptop=42.7 mouse=30.0 remote=6.1 keyboard=32.3 cell phone=15.0 microwave=33.7 oven=25.2 toaster=12.1 sink=19.8 refrigerator=37.4 book=3.7 clock=26.9 vase=14.5 scissors=15.8 teddy bear=30.5 hair drier=0.0 toothbrush=4.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =22.7 [Epoch 160] Set learning rate to 0.0001 [Epoch 160][Batch 99], Speed: 357.741 samples/sec, CrossEntropy=2.460, SmoothL1=1.059 [Epoch 160][Batch 199], Speed: 347.107 samples/sec, CrossEntropy=2.433, SmoothL1=1.048 [Epoch 160][Batch 299], Speed: 349.511 samples/sec, CrossEntropy=2.405, SmoothL1=1.035 [Epoch 160][Batch 399], Speed: 361.671 samples/sec, CrossEntropy=2.388, SmoothL1=1.031 [Epoch 160][Batch 499], Speed: 359.367 samples/sec, CrossEntropy=2.385, SmoothL1=1.032 [Epoch 160][Batch 599], Speed: 348.254 samples/sec, CrossEntropy=2.384, SmoothL1=1.031 [Epoch 160][Batch 699], Speed: 346.167 samples/sec, CrossEntropy=2.379, SmoothL1=1.025 [Epoch 160][Batch 799], Speed: 364.821 samples/sec, CrossEntropy=2.377, SmoothL1=1.024 [Epoch 160][Batch 899], Speed: 346.967 samples/sec, CrossEntropy=2.373, SmoothL1=1.019 [Epoch 160][Batch 999], Speed: 357.494 samples/sec, CrossEntropy=2.365, SmoothL1=1.014 [Epoch 160][Batch 1099], Speed: 346.387 samples/sec, CrossEntropy=2.363, SmoothL1=1.013 [Epoch 160][Batch 1199], Speed: 347.098 samples/sec, CrossEntropy=2.359, SmoothL1=1.010 [Epoch 160][Batch 1299], Speed: 360.613 samples/sec, CrossEntropy=2.352, SmoothL1=1.008 [Epoch 160][Batch 1399], Speed: 357.802 samples/sec, CrossEntropy=2.349, SmoothL1=1.009 [Epoch 160][Batch 1499], Speed: 354.707 samples/sec, CrossEntropy=2.342, SmoothL1=1.004 [Epoch 160][Batch 1599], Speed: 348.987 samples/sec, CrossEntropy=2.341, SmoothL1=1.004 [Epoch 160][Batch 1699], Speed: 344.055 samples/sec, CrossEntropy=2.340, SmoothL1=1.004 [Epoch 160][Batch 1799], Speed: 356.895 samples/sec, CrossEntropy=2.337, SmoothL1=1.004 [Epoch 160] Training cost: 336.032, CrossEntropy=2.334, SmoothL1=1.002 [Epoch 160] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.246 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.411 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.260 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.047 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.232 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.583 person=34.2 bicycle=16.9 car=19.6 motorcycle=27.5 airplane=43.5 bus=49.5 train=52.8 truck=20.6 boat=11.5 traffic light=7.4 fire hydrant=44.4 stop sign=44.6 parking meter=31.6 bench=14.1 bird=15.5 cat=53.4 dog=46.4 horse=40.5 sheep=31.9 cow=31.6 elephant=45.9 bear=56.0 zebra=48.9 giraffe=51.5 backpack=4.1 umbrella=22.0 handbag=3.8 tie=13.7 suitcase=19.2 frisbee=28.6 skis=10.7 snowboard=11.5 sports ball=17.9 kite=16.5 baseball bat=9.6 baseball glove=13.0 skateboard=26.7 surfboard=18.2 tennis racket=25.6 bottle=13.5 wine glass=12.8 cup=19.3 fork=15.1 knife=4.9 spoon=5.1 bowl=25.5 banana=14.8 apple=10.5 sandwich=29.6 orange=20.5 broccoli=14.3 carrot=10.6 hot dog=22.7 pizza=37.6 donut=28.0 cake=20.1 chair=12.7 couch=34.4 potted plant=14.0 bed=33.9 dining table=21.2 toilet=45.7 tv=41.7 laptop=44.4 mouse=31.8 remote=7.4 keyboard=33.2 cell phone=15.8 microwave=36.8 oven=27.4 toaster=8.2 sink=23.1 refrigerator=38.6 book=4.6 clock=29.4 vase=16.5 scissors=22.4 teddy bear=33.1 hair drier=0.0 toothbrush=8.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.6 [Epoch 161][Batch 99], Speed: 352.176 samples/sec, CrossEntropy=2.319, SmoothL1=1.005 [Epoch 161][Batch 199], Speed: 356.852 samples/sec, CrossEntropy=2.321, SmoothL1=0.989 [Epoch 161][Batch 299], Speed: 354.963 samples/sec, CrossEntropy=2.305, SmoothL1=0.979 [Epoch 161][Batch 399], Speed: 348.694 samples/sec, CrossEntropy=2.302, SmoothL1=0.976 [Epoch 161][Batch 499], Speed: 348.691 samples/sec, CrossEntropy=2.297, SmoothL1=0.977 [Epoch 161][Batch 599], Speed: 351.541 samples/sec, CrossEntropy=2.297, SmoothL1=0.976 [Epoch 161][Batch 699], Speed: 366.134 samples/sec, CrossEntropy=2.296, SmoothL1=0.978 [Epoch 161][Batch 799], Speed: 359.401 samples/sec, CrossEntropy=2.297, SmoothL1=0.979 [Epoch 161][Batch 899], Speed: 355.592 samples/sec, CrossEntropy=2.295, SmoothL1=0.978 [Epoch 161][Batch 999], Speed: 355.828 samples/sec, CrossEntropy=2.292, SmoothL1=0.980 [Epoch 161][Batch 1099], Speed: 362.715 samples/sec, CrossEntropy=2.291, SmoothL1=0.981 [Epoch 161][Batch 1199], Speed: 355.321 samples/sec, CrossEntropy=2.289, SmoothL1=0.981 [Epoch 161][Batch 1299], Speed: 346.706 samples/sec, CrossEntropy=2.288, SmoothL1=0.981 [Epoch 161][Batch 1399], Speed: 351.822 samples/sec, CrossEntropy=2.288, SmoothL1=0.981 [Epoch 161][Batch 1499], Speed: 346.220 samples/sec, CrossEntropy=2.286, SmoothL1=0.980 [Epoch 161][Batch 1599], Speed: 353.370 samples/sec, CrossEntropy=2.287, SmoothL1=0.983 [Epoch 161][Batch 1699], Speed: 341.285 samples/sec, CrossEntropy=2.286, SmoothL1=0.984 [Epoch 161][Batch 1799], Speed: 359.094 samples/sec, CrossEntropy=2.286, SmoothL1=0.983 [Epoch 161] Training cost: 334.677, CrossEntropy=2.285, SmoothL1=0.982 [Epoch 161] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.246 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.411 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.257 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.259 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.232 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.331 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.343 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.376 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.582 person=34.3 bicycle=16.6 car=19.9 motorcycle=27.8 airplane=44.4 bus=50.2 train=53.5 truck=21.2 boat=11.3 traffic light=7.7 fire hydrant=44.6 stop sign=46.2 parking meter=30.0 bench=13.6 bird=15.4 cat=54.0 dog=46.6 horse=40.4 sheep=32.2 cow=31.6 elephant=46.4 bear=56.8 zebra=48.6 giraffe=51.2 backpack=4.0 umbrella=21.7 handbag=3.8 tie=14.2 suitcase=18.9 frisbee=30.3 skis=10.4 snowboard=10.7 sports ball=18.1 kite=16.4 baseball bat=9.7 baseball glove=13.5 skateboard=25.1 surfboard=17.8 tennis racket=26.1 bottle=13.5 wine glass=12.3 cup=19.1 fork=15.3 knife=5.0 spoon=4.8 bowl=25.8 banana=15.2 apple=11.1 sandwich=28.8 orange=21.0 broccoli=14.2 carrot=10.1 hot dog=21.5 pizza=36.5 donut=26.9 cake=20.0 chair=13.0 couch=34.0 potted plant=14.5 bed=34.2 dining table=21.4 toilet=45.7 tv=41.9 laptop=45.1 mouse=32.1 remote=7.6 keyboard=33.8 cell phone=15.7 microwave=36.5 oven=27.4 toaster=8.2 sink=22.5 refrigerator=38.7 book=4.7 clock=29.8 vase=16.4 scissors=21.1 teddy bear=33.3 hair drier=0.0 toothbrush=6.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.6 [Epoch 162][Batch 99], Speed: 342.147 samples/sec, CrossEntropy=2.248, SmoothL1=0.961 [Epoch 162][Batch 199], Speed: 350.122 samples/sec, CrossEntropy=2.257, SmoothL1=0.977 [Epoch 162][Batch 299], Speed: 359.139 samples/sec, CrossEntropy=2.248, SmoothL1=0.962 [Epoch 162][Batch 399], Speed: 356.847 samples/sec, CrossEntropy=2.248, SmoothL1=0.964 [Epoch 162][Batch 499], Speed: 350.653 samples/sec, CrossEntropy=2.250, SmoothL1=0.964 [Epoch 162][Batch 599], Speed: 345.375 samples/sec, CrossEntropy=2.256, SmoothL1=0.968 [Epoch 162][Batch 699], Speed: 355.064 samples/sec, CrossEntropy=2.256, SmoothL1=0.968 [Epoch 162][Batch 799], Speed: 361.085 samples/sec, CrossEntropy=2.253, SmoothL1=0.964 [Epoch 162][Batch 899], Speed: 362.963 samples/sec, CrossEntropy=2.250, SmoothL1=0.963 [Epoch 162][Batch 999], Speed: 348.417 samples/sec, CrossEntropy=2.252, SmoothL1=0.964 [Epoch 162][Batch 1099], Speed: 348.771 samples/sec, CrossEntropy=2.248, SmoothL1=0.963 [Epoch 162][Batch 1199], Speed: 356.401 samples/sec, CrossEntropy=2.247, SmoothL1=0.962 [Epoch 162][Batch 1299], Speed: 357.890 samples/sec, CrossEntropy=2.247, SmoothL1=0.963 [Epoch 162][Batch 1399], Speed: 360.312 samples/sec, CrossEntropy=2.246, SmoothL1=0.963 [Epoch 162][Batch 1499], Speed: 345.354 samples/sec, CrossEntropy=2.245, SmoothL1=0.962 [Epoch 162][Batch 1599], Speed: 363.378 samples/sec, CrossEntropy=2.245, SmoothL1=0.960 [Epoch 162][Batch 1699], Speed: 359.914 samples/sec, CrossEntropy=2.242, SmoothL1=0.959 [Epoch 162][Batch 1799], Speed: 349.867 samples/sec, CrossEntropy=2.244, SmoothL1=0.960 [Epoch 162] Training cost: 334.578, CrossEntropy=2.244, SmoothL1=0.960 [Epoch 162] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.246 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.410 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.257 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.331 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.377 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.576 person=34.3 bicycle=16.9 car=19.8 motorcycle=27.7 airplane=45.2 bus=49.7 train=53.8 truck=21.3 boat=11.1 traffic light=7.7 fire hydrant=45.3 stop sign=45.9 parking meter=31.3 bench=13.9 bird=15.4 cat=53.5 dog=46.9 horse=40.4 sheep=32.6 cow=31.8 elephant=46.2 bear=54.6 zebra=48.9 giraffe=51.0 backpack=3.9 umbrella=22.0 handbag=3.8 tie=13.9 suitcase=18.3 frisbee=30.1 skis=10.9 snowboard=12.9 sports ball=17.7 kite=16.7 baseball bat=9.1 baseball glove=13.2 skateboard=26.2 surfboard=17.9 tennis racket=25.9 bottle=13.6 wine glass=12.5 cup=19.2 fork=15.3 knife=5.0 spoon=5.3 bowl=25.6 banana=14.5 apple=10.3 sandwich=29.1 orange=20.4 broccoli=13.5 carrot=10.1 hot dog=22.4 pizza=37.2 donut=27.0 cake=20.0 chair=12.8 couch=34.7 potted plant=13.9 bed=33.8 dining table=21.4 toilet=45.6 tv=42.1 laptop=43.9 mouse=32.5 remote=7.8 keyboard=32.2 cell phone=16.0 microwave=35.6 oven=28.1 toaster=4.8 sink=23.0 refrigerator=39.0 book=4.6 clock=29.5 vase=16.3 scissors=21.3 teddy bear=32.4 hair drier=0.0 toothbrush=7.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.6 [Epoch 163][Batch 99], Speed: 365.211 samples/sec, CrossEntropy=2.254, SmoothL1=0.961 [Epoch 163][Batch 199], Speed: 354.911 samples/sec, CrossEntropy=2.240, SmoothL1=0.960 [Epoch 163][Batch 299], Speed: 360.893 samples/sec, CrossEntropy=2.244, SmoothL1=0.969 [Epoch 163][Batch 399], Speed: 362.979 samples/sec, CrossEntropy=2.243, SmoothL1=0.968 [Epoch 163][Batch 499], Speed: 359.443 samples/sec, CrossEntropy=2.235, SmoothL1=0.962 [Epoch 163][Batch 599], Speed: 362.295 samples/sec, CrossEntropy=2.240, SmoothL1=0.965 [Epoch 163][Batch 699], Speed: 360.429 samples/sec, CrossEntropy=2.243, SmoothL1=0.966 [Epoch 163][Batch 799], Speed: 355.674 samples/sec, CrossEntropy=2.244, SmoothL1=0.967 [Epoch 163][Batch 899], Speed: 358.386 samples/sec, CrossEntropy=2.253, SmoothL1=0.971 [Epoch 163][Batch 999], Speed: 347.932 samples/sec, CrossEntropy=2.256, SmoothL1=0.972 [Epoch 163][Batch 1099], Speed: 350.763 samples/sec, CrossEntropy=2.256, SmoothL1=0.972 [Epoch 163][Batch 1199], Speed: 349.987 samples/sec, CrossEntropy=2.253, SmoothL1=0.969 [Epoch 163][Batch 1299], Speed: 358.366 samples/sec, CrossEntropy=2.254, SmoothL1=0.968 [Epoch 163][Batch 1399], Speed: 352.130 samples/sec, CrossEntropy=2.253, SmoothL1=0.968 [Epoch 163][Batch 1499], Speed: 350.048 samples/sec, CrossEntropy=2.253, SmoothL1=0.969 [Epoch 163][Batch 1599], Speed: 360.558 samples/sec, CrossEntropy=2.253, SmoothL1=0.971 [Epoch 163][Batch 1699], Speed: 356.426 samples/sec, CrossEntropy=2.256, SmoothL1=0.972 [Epoch 163][Batch 1799], Speed: 350.125 samples/sec, CrossEntropy=2.252, SmoothL1=0.970 [Epoch 163] Training cost: 334.333, CrossEntropy=2.250, SmoothL1=0.969 [Epoch 163] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.412 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.260 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.047 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.441 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.378 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.585 person=34.4 bicycle=17.3 car=19.9 motorcycle=28.2 airplane=45.3 bus=49.6 train=54.2 truck=21.8 boat=11.4 traffic light=7.6 fire hydrant=45.3 stop sign=45.4 parking meter=30.4 bench=13.7 bird=15.9 cat=52.5 dog=46.8 horse=41.5 sheep=32.7 cow=31.9 elephant=46.6 bear=57.7 zebra=49.3 giraffe=51.3 backpack=3.8 umbrella=22.4 handbag=3.8 tie=14.2 suitcase=18.9 frisbee=30.2 skis=10.9 snowboard=12.0 sports ball=17.5 kite=16.5 baseball bat=10.4 baseball glove=13.5 skateboard=25.3 surfboard=17.8 tennis racket=25.8 bottle=13.7 wine glass=12.8 cup=19.0 fork=15.3 knife=5.3 spoon=4.6 bowl=25.7 banana=15.2 apple=10.6 sandwich=30.2 orange=20.7 broccoli=13.7 carrot=9.8 hot dog=21.7 pizza=36.6 donut=27.0 cake=20.7 chair=13.0 couch=34.5 potted plant=14.3 bed=34.0 dining table=21.4 toilet=46.7 tv=42.1 laptop=44.2 mouse=33.1 remote=7.6 keyboard=33.4 cell phone=15.6 microwave=35.9 oven=27.9 toaster=7.7 sink=23.1 refrigerator=38.5 book=4.7 clock=29.5 vase=16.5 scissors=21.6 teddy bear=33.3 hair drier=0.0 toothbrush=7.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 164][Batch 99], Speed: 358.688 samples/sec, CrossEntropy=2.255, SmoothL1=0.985 [Epoch 164][Batch 199], Speed: 348.766 samples/sec, CrossEntropy=2.241, SmoothL1=0.963 [Epoch 164][Batch 299], Speed: 354.694 samples/sec, CrossEntropy=2.253, SmoothL1=0.964 [Epoch 164][Batch 399], Speed: 342.120 samples/sec, CrossEntropy=2.248, SmoothL1=0.967 [Epoch 164][Batch 499], Speed: 359.544 samples/sec, CrossEntropy=2.251, SmoothL1=0.968 [Epoch 164][Batch 599], Speed: 350.275 samples/sec, CrossEntropy=2.249, SmoothL1=0.965 [Epoch 164][Batch 699], Speed: 346.917 samples/sec, CrossEntropy=2.252, SmoothL1=0.964 [Epoch 164][Batch 799], Speed: 348.919 samples/sec, CrossEntropy=2.247, SmoothL1=0.961 [Epoch 164][Batch 899], Speed: 359.881 samples/sec, CrossEntropy=2.244, SmoothL1=0.961 [Epoch 164][Batch 999], Speed: 364.447 samples/sec, CrossEntropy=2.241, SmoothL1=0.960 [Epoch 164][Batch 1099], Speed: 349.795 samples/sec, CrossEntropy=2.238, SmoothL1=0.958 [Epoch 164][Batch 1199], Speed: 352.621 samples/sec, CrossEntropy=2.234, SmoothL1=0.960 [Epoch 164][Batch 1299], Speed: 353.776 samples/sec, CrossEntropy=2.234, SmoothL1=0.960 [Epoch 164][Batch 1399], Speed: 347.861 samples/sec, CrossEntropy=2.233, SmoothL1=0.961 [Epoch 164][Batch 1499], Speed: 340.003 samples/sec, CrossEntropy=2.231, SmoothL1=0.959 [Epoch 164][Batch 1599], Speed: 353.300 samples/sec, CrossEntropy=2.229, SmoothL1=0.958 [Epoch 164][Batch 1699], Speed: 347.452 samples/sec, CrossEntropy=2.229, SmoothL1=0.958 [Epoch 164][Batch 1799], Speed: 356.790 samples/sec, CrossEntropy=2.228, SmoothL1=0.959 [Epoch 164] Training cost: 334.387, CrossEntropy=2.228, SmoothL1=0.959 [Epoch 164] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.413 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.257 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.263 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.439 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.077 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.377 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.584 person=34.4 bicycle=17.1 car=19.9 motorcycle=27.6 airplane=44.6 bus=49.3 train=54.3 truck=21.8 boat=11.6 traffic light=7.8 fire hydrant=45.6 stop sign=46.5 parking meter=31.5 bench=13.9 bird=15.6 cat=51.9 dog=46.7 horse=41.0 sheep=32.6 cow=31.4 elephant=46.6 bear=56.0 zebra=48.9 giraffe=51.2 backpack=3.9 umbrella=22.1 handbag=3.7 tie=13.8 suitcase=18.7 frisbee=30.0 skis=10.8 snowboard=12.0 sports ball=17.8 kite=17.0 baseball bat=10.3 baseball glove=14.0 skateboard=26.2 surfboard=18.5 tennis racket=25.9 bottle=13.6 wine glass=12.7 cup=18.8 fork=15.5 knife=5.2 spoon=4.8 bowl=25.8 banana=15.3 apple=11.6 sandwich=29.9 orange=20.5 broccoli=13.3 carrot=10.2 hot dog=22.0 pizza=36.5 donut=26.9 cake=20.0 chair=12.8 couch=34.7 potted plant=14.4 bed=33.7 dining table=21.1 toilet=46.4 tv=42.3 laptop=44.4 mouse=32.8 remote=7.6 keyboard=33.2 cell phone=15.5 microwave=34.7 oven=27.5 toaster=7.7 sink=22.9 refrigerator=39.1 book=4.7 clock=29.2 vase=16.9 scissors=19.0 teddy bear=33.0 hair drier=5.0 toothbrush=7.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 165][Batch 99], Speed: 356.948 samples/sec, CrossEntropy=2.272, SmoothL1=0.984 [Epoch 165][Batch 199], Speed: 362.331 samples/sec, CrossEntropy=2.269, SmoothL1=0.995 [Epoch 165][Batch 299], Speed: 356.235 samples/sec, CrossEntropy=2.263, SmoothL1=0.983 [Epoch 165][Batch 399], Speed: 341.279 samples/sec, CrossEntropy=2.251, SmoothL1=0.974 [Epoch 165][Batch 499], Speed: 355.151 samples/sec, CrossEntropy=2.256, SmoothL1=0.972 [Epoch 165][Batch 599], Speed: 346.918 samples/sec, CrossEntropy=2.253, SmoothL1=0.971 [Epoch 165][Batch 699], Speed: 344.390 samples/sec, CrossEntropy=2.247, SmoothL1=0.966 [Epoch 165][Batch 799], Speed: 357.670 samples/sec, CrossEntropy=2.245, SmoothL1=0.964 [Epoch 165][Batch 899], Speed: 349.760 samples/sec, CrossEntropy=2.248, SmoothL1=0.965 [Epoch 165][Batch 999], Speed: 350.473 samples/sec, CrossEntropy=2.243, SmoothL1=0.961 [Epoch 165][Batch 1099], Speed: 350.015 samples/sec, CrossEntropy=2.243, SmoothL1=0.961 [Epoch 165][Batch 1199], Speed: 349.124 samples/sec, CrossEntropy=2.244, SmoothL1=0.961 [Epoch 165][Batch 1299], Speed: 361.505 samples/sec, CrossEntropy=2.246, SmoothL1=0.963 [Epoch 165][Batch 1399], Speed: 347.234 samples/sec, CrossEntropy=2.247, SmoothL1=0.965 [Epoch 165][Batch 1499], Speed: 344.123 samples/sec, CrossEntropy=2.245, SmoothL1=0.963 [Epoch 165][Batch 1599], Speed: 346.104 samples/sec, CrossEntropy=2.242, SmoothL1=0.961 [Epoch 165][Batch 1699], Speed: 344.913 samples/sec, CrossEntropy=2.242, SmoothL1=0.961 [Epoch 165][Batch 1799], Speed: 346.732 samples/sec, CrossEntropy=2.240, SmoothL1=0.959 [Epoch 165] Training cost: 335.452, CrossEntropy=2.240, SmoothL1=0.959 [Epoch 165] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.412 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.259 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.047 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.263 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.442 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.077 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.377 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.583 person=34.7 bicycle=16.4 car=19.9 motorcycle=27.7 airplane=44.3 bus=49.6 train=54.2 truck=21.4 boat=11.6 traffic light=7.7 fire hydrant=46.0 stop sign=45.6 parking meter=31.7 bench=13.5 bird=15.5 cat=53.4 dog=47.7 horse=40.9 sheep=32.3 cow=31.3 elephant=47.1 bear=56.8 zebra=49.1 giraffe=51.4 backpack=3.6 umbrella=21.9 handbag=3.9 tie=13.6 suitcase=18.5 frisbee=30.8 skis=11.4 snowboard=11.9 sports ball=18.0 kite=16.7 baseball bat=9.4 baseball glove=13.3 skateboard=27.1 surfboard=18.2 tennis racket=26.0 bottle=13.6 wine glass=12.6 cup=18.9 fork=14.9 knife=5.4 spoon=4.7 bowl=25.3 banana=15.0 apple=11.3 sandwich=29.2 orange=20.0 broccoli=14.0 carrot=10.0 hot dog=22.7 pizza=36.8 donut=27.0 cake=20.5 chair=13.1 couch=34.2 potted plant=14.2 bed=33.5 dining table=21.2 toilet=46.3 tv=42.2 laptop=44.7 mouse=32.4 remote=7.5 keyboard=33.1 cell phone=15.9 microwave=35.2 oven=26.9 toaster=4.7 sink=22.8 refrigerator=38.5 book=4.7 clock=29.5 vase=16.9 scissors=19.8 teddy bear=32.8 hair drier=8.9 toothbrush=7.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 166][Batch 99], Speed: 344.486 samples/sec, CrossEntropy=2.193, SmoothL1=0.951 [Epoch 166][Batch 199], Speed: 353.024 samples/sec, CrossEntropy=2.188, SmoothL1=0.945 [Epoch 166][Batch 299], Speed: 346.810 samples/sec, CrossEntropy=2.206, SmoothL1=0.947 [Epoch 166][Batch 399], Speed: 349.687 samples/sec, CrossEntropy=2.209, SmoothL1=0.950 [Epoch 166][Batch 499], Speed: 360.627 samples/sec, CrossEntropy=2.214, SmoothL1=0.955 [Epoch 166][Batch 599], Speed: 348.686 samples/sec, CrossEntropy=2.212, SmoothL1=0.954 [Epoch 166][Batch 699], Speed: 358.341 samples/sec, CrossEntropy=2.211, SmoothL1=0.952 [Epoch 166][Batch 799], Speed: 352.458 samples/sec, CrossEntropy=2.211, SmoothL1=0.951 [Epoch 166][Batch 899], Speed: 351.172 samples/sec, CrossEntropy=2.210, SmoothL1=0.949 [Epoch 166][Batch 999], Speed: 352.563 samples/sec, CrossEntropy=2.211, SmoothL1=0.947 [Epoch 166][Batch 1099], Speed: 358.564 samples/sec, CrossEntropy=2.213, SmoothL1=0.945 [Epoch 166][Batch 1199], Speed: 365.947 samples/sec, CrossEntropy=2.214, SmoothL1=0.944 [Epoch 166][Batch 1299], Speed: 350.571 samples/sec, CrossEntropy=2.213, SmoothL1=0.943 [Epoch 166][Batch 1399], Speed: 350.934 samples/sec, CrossEntropy=2.216, SmoothL1=0.944 [Epoch 166][Batch 1499], Speed: 348.095 samples/sec, CrossEntropy=2.218, SmoothL1=0.946 [Epoch 166][Batch 1599], Speed: 351.210 samples/sec, CrossEntropy=2.219, SmoothL1=0.947 [Epoch 166][Batch 1699], Speed: 353.387 samples/sec, CrossEntropy=2.216, SmoothL1=0.945 [Epoch 166][Batch 1799], Speed: 347.254 samples/sec, CrossEntropy=2.218, SmoothL1=0.947 [Epoch 166] Training cost: 335.593, CrossEntropy=2.218, SmoothL1=0.947 [Epoch 166] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.413 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.259 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.439 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.079 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.580 person=34.4 bicycle=17.2 car=19.8 motorcycle=27.9 airplane=45.3 bus=50.7 train=53.8 truck=21.6 boat=11.4 traffic light=7.8 fire hydrant=46.2 stop sign=46.3 parking meter=31.9 bench=13.6 bird=15.1 cat=53.9 dog=46.6 horse=41.5 sheep=32.0 cow=31.4 elephant=46.6 bear=56.8 zebra=49.3 giraffe=50.5 backpack=3.9 umbrella=22.1 handbag=3.5 tie=14.3 suitcase=19.6 frisbee=30.3 skis=10.8 snowboard=11.5 sports ball=18.2 kite=16.9 baseball bat=9.2 baseball glove=12.9 skateboard=27.0 surfboard=18.4 tennis racket=26.1 bottle=13.8 wine glass=12.6 cup=18.9 fork=15.8 knife=5.3 spoon=4.5 bowl=25.3 banana=15.0 apple=11.0 sandwich=29.6 orange=19.6 broccoli=13.6 carrot=10.3 hot dog=21.2 pizza=36.3 donut=27.6 cake=20.3 chair=13.3 couch=34.4 potted plant=14.3 bed=34.7 dining table=20.8 toilet=46.0 tv=41.7 laptop=44.2 mouse=32.4 remote=8.1 keyboard=33.5 cell phone=16.3 microwave=36.0 oven=27.3 toaster=8.2 sink=22.7 refrigerator=37.9 book=5.0 clock=29.3 vase=17.7 scissors=19.1 teddy bear=32.9 hair drier=0.0 toothbrush=8.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 167][Batch 99], Speed: 353.306 samples/sec, CrossEntropy=2.195, SmoothL1=0.925 [Epoch 167][Batch 199], Speed: 351.418 samples/sec, CrossEntropy=2.193, SmoothL1=0.929 [Epoch 167][Batch 299], Speed: 359.099 samples/sec, CrossEntropy=2.209, SmoothL1=0.938 [Epoch 167][Batch 399], Speed: 359.771 samples/sec, CrossEntropy=2.208, SmoothL1=0.940 [Epoch 167][Batch 499], Speed: 351.284 samples/sec, CrossEntropy=2.217, SmoothL1=0.945 [Epoch 167][Batch 599], Speed: 345.355 samples/sec, CrossEntropy=2.217, SmoothL1=0.947 [Epoch 167][Batch 699], Speed: 343.842 samples/sec, CrossEntropy=2.221, SmoothL1=0.951 [Epoch 167][Batch 799], Speed: 345.920 samples/sec, CrossEntropy=2.226, SmoothL1=0.954 [Epoch 167][Batch 899], Speed: 350.370 samples/sec, CrossEntropy=2.222, SmoothL1=0.952 [Epoch 167][Batch 999], Speed: 345.587 samples/sec, CrossEntropy=2.219, SmoothL1=0.950 [Epoch 167][Batch 1099], Speed: 354.253 samples/sec, CrossEntropy=2.219, SmoothL1=0.949 [Epoch 167][Batch 1199], Speed: 349.493 samples/sec, CrossEntropy=2.219, SmoothL1=0.951 [Epoch 167][Batch 1299], Speed: 349.359 samples/sec, CrossEntropy=2.217, SmoothL1=0.949 [Epoch 167][Batch 1399], Speed: 356.352 samples/sec, CrossEntropy=2.216, SmoothL1=0.950 [Epoch 167][Batch 1499], Speed: 356.763 samples/sec, CrossEntropy=2.218, SmoothL1=0.950 [Epoch 167][Batch 1599], Speed: 358.798 samples/sec, CrossEntropy=2.217, SmoothL1=0.949 [Epoch 167][Batch 1699], Speed: 364.345 samples/sec, CrossEntropy=2.218, SmoothL1=0.951 [Epoch 167][Batch 1799], Speed: 346.169 samples/sec, CrossEntropy=2.219, SmoothL1=0.950 [Epoch 167] Training cost: 334.839, CrossEntropy=2.218, SmoothL1=0.949 [Epoch 167] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.247 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.413 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.259 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.047 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.263 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.433 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.232 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.330 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.343 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.376 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.573 person=34.5 bicycle=16.5 car=20.1 motorcycle=28.0 airplane=44.6 bus=50.6 train=54.1 truck=21.5 boat=11.3 traffic light=7.7 fire hydrant=44.1 stop sign=46.1 parking meter=31.5 bench=13.6 bird=15.1 cat=52.1 dog=47.0 horse=40.5 sheep=32.5 cow=31.1 elephant=46.5 bear=56.4 zebra=48.6 giraffe=51.0 backpack=3.9 umbrella=22.2 handbag=3.4 tie=14.3 suitcase=18.7 frisbee=30.5 skis=11.2 snowboard=11.8 sports ball=17.6 kite=16.1 baseball bat=9.7 baseball glove=13.5 skateboard=26.9 surfboard=18.6 tennis racket=26.0 bottle=13.6 wine glass=12.8 cup=18.8 fork=15.4 knife=5.0 spoon=4.5 bowl=25.3 banana=15.3 apple=10.9 sandwich=29.5 orange=21.0 broccoli=13.9 carrot=10.6 hot dog=22.1 pizza=36.3 donut=27.5 cake=19.8 chair=13.1 couch=34.5 potted plant=14.0 bed=35.5 dining table=21.4 toilet=47.3 tv=41.8 laptop=43.6 mouse=32.5 remote=7.6 keyboard=33.2 cell phone=16.2 microwave=36.6 oven=27.1 toaster=7.1 sink=23.4 refrigerator=38.4 book=4.7 clock=29.3 vase=17.1 scissors=19.8 teddy bear=32.8 hair drier=0.0 toothbrush=7.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.7 [Epoch 168][Batch 99], Speed: 356.796 samples/sec, CrossEntropy=2.207, SmoothL1=0.955 [Epoch 168][Batch 199], Speed: 352.883 samples/sec, CrossEntropy=2.211, SmoothL1=0.956 [Epoch 168][Batch 299], Speed: 345.150 samples/sec, CrossEntropy=2.207, SmoothL1=0.944 [Epoch 168][Batch 399], Speed: 343.665 samples/sec, CrossEntropy=2.201, SmoothL1=0.940 [Epoch 168][Batch 499], Speed: 344.326 samples/sec, CrossEntropy=2.202, SmoothL1=0.943 [Epoch 168][Batch 599], Speed: 353.055 samples/sec, CrossEntropy=2.206, SmoothL1=0.946 [Epoch 168][Batch 699], Speed: 344.275 samples/sec, CrossEntropy=2.205, SmoothL1=0.946 [Epoch 168][Batch 799], Speed: 355.693 samples/sec, CrossEntropy=2.210, SmoothL1=0.945 [Epoch 168][Batch 899], Speed: 349.216 samples/sec, CrossEntropy=2.206, SmoothL1=0.942 [Epoch 168][Batch 999], Speed: 355.449 samples/sec, CrossEntropy=2.204, SmoothL1=0.943 [Epoch 168][Batch 1099], Speed: 346.830 samples/sec, CrossEntropy=2.205, SmoothL1=0.945 [Epoch 168][Batch 1199], Speed: 347.959 samples/sec, CrossEntropy=2.205, SmoothL1=0.945 [Epoch 168][Batch 1299], Speed: 359.407 samples/sec, CrossEntropy=2.208, SmoothL1=0.945 [Epoch 168][Batch 1399], Speed: 343.585 samples/sec, CrossEntropy=2.209, SmoothL1=0.946 [Epoch 168][Batch 1499], Speed: 349.382 samples/sec, CrossEntropy=2.212, SmoothL1=0.947 [Epoch 168][Batch 1599], Speed: 348.326 samples/sec, CrossEntropy=2.216, SmoothL1=0.950 [Epoch 168][Batch 1699], Speed: 354.327 samples/sec, CrossEntropy=2.216, SmoothL1=0.950 [Epoch 168][Batch 1799], Speed: 351.593 samples/sec, CrossEntropy=2.216, SmoothL1=0.951 [Epoch 168] Training cost: 335.099, CrossEntropy=2.218, SmoothL1=0.953 [Epoch 168] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.413 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.382 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.579 person=34.6 bicycle=16.6 car=19.9 motorcycle=27.9 airplane=46.4 bus=50.6 train=53.9 truck=22.1 boat=11.6 traffic light=8.2 fire hydrant=46.4 stop sign=46.0 parking meter=31.9 bench=13.7 bird=15.5 cat=53.5 dog=47.0 horse=40.5 sheep=32.6 cow=32.4 elephant=46.7 bear=56.3 zebra=48.7 giraffe=50.5 backpack=4.0 umbrella=22.2 handbag=3.6 tie=13.6 suitcase=18.4 frisbee=30.0 skis=11.2 snowboard=12.5 sports ball=17.5 kite=16.7 baseball bat=9.6 baseball glove=13.2 skateboard=27.1 surfboard=18.6 tennis racket=26.2 bottle=13.8 wine glass=13.2 cup=18.9 fork=15.4 knife=5.4 spoon=5.0 bowl=24.8 banana=15.1 apple=11.0 sandwich=29.5 orange=20.1 broccoli=14.4 carrot=10.2 hot dog=22.5 pizza=36.9 donut=27.3 cake=20.8 chair=13.0 couch=34.3 potted plant=14.5 bed=34.0 dining table=21.2 toilet=47.5 tv=42.0 laptop=44.4 mouse=32.1 remote=8.2 keyboard=33.2 cell phone=15.8 microwave=37.9 oven=28.0 toaster=7.4 sink=23.3 refrigerator=39.6 book=4.9 clock=29.8 vase=17.3 scissors=21.5 teddy bear=33.0 hair drier=0.0 toothbrush=8.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 169][Batch 99], Speed: 356.275 samples/sec, CrossEntropy=2.165, SmoothL1=0.927 [Epoch 169][Batch 199], Speed: 346.931 samples/sec, CrossEntropy=2.184, SmoothL1=0.937 [Epoch 169][Batch 299], Speed: 353.479 samples/sec, CrossEntropy=2.182, SmoothL1=0.936 [Epoch 169][Batch 399], Speed: 351.941 samples/sec, CrossEntropy=2.189, SmoothL1=0.940 [Epoch 169][Batch 499], Speed: 351.745 samples/sec, CrossEntropy=2.195, SmoothL1=0.949 [Epoch 169][Batch 599], Speed: 354.775 samples/sec, CrossEntropy=2.205, SmoothL1=0.951 [Epoch 169][Batch 699], Speed: 347.207 samples/sec, CrossEntropy=2.202, SmoothL1=0.946 [Epoch 169][Batch 799], Speed: 349.640 samples/sec, CrossEntropy=2.203, SmoothL1=0.947 [Epoch 169][Batch 899], Speed: 337.934 samples/sec, CrossEntropy=2.200, SmoothL1=0.945 [Epoch 169][Batch 999], Speed: 360.869 samples/sec, CrossEntropy=2.205, SmoothL1=0.948 [Epoch 169][Batch 1099], Speed: 350.013 samples/sec, CrossEntropy=2.205, SmoothL1=0.947 [Epoch 169][Batch 1199], Speed: 354.343 samples/sec, CrossEntropy=2.207, SmoothL1=0.949 [Epoch 169][Batch 1299], Speed: 364.019 samples/sec, CrossEntropy=2.209, SmoothL1=0.949 [Epoch 169][Batch 1399], Speed: 349.883 samples/sec, CrossEntropy=2.210, SmoothL1=0.949 [Epoch 169][Batch 1499], Speed: 353.552 samples/sec, CrossEntropy=2.209, SmoothL1=0.949 [Epoch 169][Batch 1599], Speed: 361.387 samples/sec, CrossEntropy=2.208, SmoothL1=0.948 [Epoch 169][Batch 1699], Speed: 357.364 samples/sec, CrossEntropy=2.207, SmoothL1=0.948 [Epoch 169][Batch 1799], Speed: 354.996 samples/sec, CrossEntropy=2.206, SmoothL1=0.947 [Epoch 169] Training cost: 334.999, CrossEntropy=2.205, SmoothL1=0.948 [Epoch 169] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.441 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.077 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.586 person=34.6 bicycle=17.2 car=19.9 motorcycle=28.0 airplane=46.1 bus=50.1 train=53.5 truck=22.2 boat=11.3 traffic light=7.9 fire hydrant=45.6 stop sign=46.8 parking meter=32.8 bench=13.8 bird=15.6 cat=53.4 dog=47.2 horse=40.8 sheep=33.2 cow=32.0 elephant=46.8 bear=57.5 zebra=48.7 giraffe=50.4 backpack=4.1 umbrella=21.8 handbag=3.6 tie=13.7 suitcase=18.6 frisbee=30.4 skis=10.9 snowboard=12.3 sports ball=17.9 kite=17.0 baseball bat=9.5 baseball glove=13.5 skateboard=27.0 surfboard=18.6 tennis racket=26.2 bottle=13.1 wine glass=12.9 cup=18.7 fork=15.5 knife=5.6 spoon=4.9 bowl=24.6 banana=14.8 apple=11.2 sandwich=29.6 orange=20.4 broccoli=14.0 carrot=10.3 hot dog=22.5 pizza=36.6 donut=27.1 cake=21.2 chair=13.1 couch=35.0 potted plant=14.1 bed=33.9 dining table=20.6 toilet=47.0 tv=41.9 laptop=44.4 mouse=32.7 remote=8.0 keyboard=32.8 cell phone=15.7 microwave=38.4 oven=27.5 toaster=8.4 sink=22.6 refrigerator=38.1 book=4.8 clock=29.9 vase=17.0 scissors=21.8 teddy bear=32.8 hair drier=0.0 toothbrush=7.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 170][Batch 99], Speed: 355.698 samples/sec, CrossEntropy=2.190, SmoothL1=0.929 [Epoch 170][Batch 199], Speed: 348.057 samples/sec, CrossEntropy=2.190, SmoothL1=0.933 [Epoch 170][Batch 299], Speed: 356.719 samples/sec, CrossEntropy=2.197, SmoothL1=0.935 [Epoch 170][Batch 399], Speed: 357.280 samples/sec, CrossEntropy=2.197, SmoothL1=0.946 [Epoch 170][Batch 499], Speed: 359.438 samples/sec, CrossEntropy=2.197, SmoothL1=0.943 [Epoch 170][Batch 599], Speed: 343.718 samples/sec, CrossEntropy=2.200, SmoothL1=0.946 [Epoch 170][Batch 699], Speed: 351.814 samples/sec, CrossEntropy=2.197, SmoothL1=0.946 [Epoch 170][Batch 799], Speed: 351.155 samples/sec, CrossEntropy=2.203, SmoothL1=0.945 [Epoch 170][Batch 899], Speed: 342.496 samples/sec, CrossEntropy=2.207, SmoothL1=0.950 [Epoch 170][Batch 999], Speed: 355.482 samples/sec, CrossEntropy=2.208, SmoothL1=0.950 [Epoch 170][Batch 1099], Speed: 358.649 samples/sec, CrossEntropy=2.207, SmoothL1=0.948 [Epoch 170][Batch 1199], Speed: 352.748 samples/sec, CrossEntropy=2.206, SmoothL1=0.946 [Epoch 170][Batch 1299], Speed: 349.231 samples/sec, CrossEntropy=2.207, SmoothL1=0.948 [Epoch 170][Batch 1399], Speed: 359.914 samples/sec, CrossEntropy=2.208, SmoothL1=0.948 [Epoch 170][Batch 1499], Speed: 352.116 samples/sec, CrossEntropy=2.208, SmoothL1=0.949 [Epoch 170][Batch 1599], Speed: 349.496 samples/sec, CrossEntropy=2.207, SmoothL1=0.949 [Epoch 170][Batch 1699], Speed: 351.731 samples/sec, CrossEntropy=2.205, SmoothL1=0.949 [Epoch 170][Batch 1799], Speed: 344.266 samples/sec, CrossEntropy=2.205, SmoothL1=0.949 [Epoch 170] Training cost: 335.658, CrossEntropy=2.206, SmoothL1=0.949 [Epoch 170] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.247 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.413 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.258 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.263 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.433 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.577 person=34.4 bicycle=16.9 car=20.0 motorcycle=27.5 airplane=45.0 bus=49.8 train=53.7 truck=21.4 boat=11.7 traffic light=7.8 fire hydrant=45.0 stop sign=46.2 parking meter=32.3 bench=13.3 bird=15.8 cat=53.4 dog=46.8 horse=40.8 sheep=33.1 cow=31.7 elephant=46.0 bear=57.4 zebra=49.2 giraffe=50.4 backpack=3.9 umbrella=21.7 handbag=3.6 tie=14.3 suitcase=19.3 frisbee=30.9 skis=11.1 snowboard=12.6 sports ball=17.6 kite=17.2 baseball bat=9.7 baseball glove=13.8 skateboard=27.3 surfboard=18.1 tennis racket=26.0 bottle=13.3 wine glass=12.5 cup=18.9 fork=15.4 knife=5.6 spoon=5.2 bowl=25.2 banana=14.9 apple=11.3 sandwich=28.9 orange=20.7 broccoli=14.1 carrot=10.6 hot dog=23.1 pizza=36.3 donut=27.2 cake=20.4 chair=13.1 couch=33.5 potted plant=14.0 bed=33.7 dining table=20.8 toilet=46.5 tv=41.7 laptop=44.8 mouse=31.9 remote=7.7 keyboard=33.7 cell phone=15.7 microwave=36.8 oven=27.0 toaster=2.7 sink=23.1 refrigerator=38.9 book=4.7 clock=29.7 vase=17.1 scissors=18.7 teddy bear=32.2 hair drier=0.0 toothbrush=8.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.7 [Epoch 171][Batch 99], Speed: 350.082 samples/sec, CrossEntropy=2.198, SmoothL1=0.925 [Epoch 171][Batch 199], Speed: 354.268 samples/sec, CrossEntropy=2.228, SmoothL1=0.944 [Epoch 171][Batch 299], Speed: 349.630 samples/sec, CrossEntropy=2.220, SmoothL1=0.936 [Epoch 171][Batch 399], Speed: 353.226 samples/sec, CrossEntropy=2.227, SmoothL1=0.953 [Epoch 171][Batch 499], Speed: 343.644 samples/sec, CrossEntropy=2.212, SmoothL1=0.945 [Epoch 171][Batch 599], Speed: 352.293 samples/sec, CrossEntropy=2.208, SmoothL1=0.945 [Epoch 171][Batch 699], Speed: 353.871 samples/sec, CrossEntropy=2.209, SmoothL1=0.945 [Epoch 171][Batch 799], Speed: 353.802 samples/sec, CrossEntropy=2.207, SmoothL1=0.944 [Epoch 171][Batch 899], Speed: 345.181 samples/sec, CrossEntropy=2.205, SmoothL1=0.944 [Epoch 171][Batch 999], Speed: 354.621 samples/sec, CrossEntropy=2.205, SmoothL1=0.943 [Epoch 171][Batch 1099], Speed: 348.193 samples/sec, CrossEntropy=2.209, SmoothL1=0.944 [Epoch 171][Batch 1199], Speed: 368.113 samples/sec, CrossEntropy=2.210, SmoothL1=0.946 [Epoch 171][Batch 1299], Speed: 348.309 samples/sec, CrossEntropy=2.207, SmoothL1=0.945 [Epoch 171][Batch 1399], Speed: 349.039 samples/sec, CrossEntropy=2.208, SmoothL1=0.945 [Epoch 171][Batch 1499], Speed: 349.538 samples/sec, CrossEntropy=2.210, SmoothL1=0.945 [Epoch 171][Batch 1599], Speed: 351.176 samples/sec, CrossEntropy=2.210, SmoothL1=0.945 [Epoch 171][Batch 1699], Speed: 366.434 samples/sec, CrossEntropy=2.209, SmoothL1=0.944 [Epoch 171][Batch 1799], Speed: 359.963 samples/sec, CrossEntropy=2.209, SmoothL1=0.945 [Epoch 171] Training cost: 334.938, CrossEntropy=2.210, SmoothL1=0.945 [Epoch 171] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.247 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.413 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.259 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.331 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.378 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.578 person=34.5 bicycle=17.0 car=20.1 motorcycle=27.8 airplane=45.9 bus=49.3 train=53.1 truck=21.4 boat=11.4 traffic light=8.1 fire hydrant=45.5 stop sign=45.7 parking meter=31.6 bench=13.4 bird=16.0 cat=53.4 dog=46.3 horse=41.5 sheep=33.1 cow=32.0 elephant=46.8 bear=57.0 zebra=49.0 giraffe=49.6 backpack=3.8 umbrella=21.5 handbag=3.6 tie=14.4 suitcase=19.1 frisbee=31.0 skis=11.2 snowboard=12.2 sports ball=18.2 kite=17.5 baseball bat=10.3 baseball glove=13.5 skateboard=26.6 surfboard=18.5 tennis racket=26.4 bottle=13.5 wine glass=12.6 cup=18.8 fork=15.1 knife=5.4 spoon=4.8 bowl=25.2 banana=15.2 apple=10.8 sandwich=27.9 orange=20.1 broccoli=13.4 carrot=10.5 hot dog=21.6 pizza=36.2 donut=27.3 cake=20.4 chair=13.1 couch=33.6 potted plant=13.7 bed=33.4 dining table=20.9 toilet=47.0 tv=42.2 laptop=43.7 mouse=32.0 remote=7.8 keyboard=33.4 cell phone=16.0 microwave=36.2 oven=27.8 toaster=3.7 sink=23.2 refrigerator=39.0 book=4.9 clock=29.8 vase=16.5 scissors=20.2 teddy bear=32.7 hair drier=0.0 toothbrush=7.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.7 [Epoch 172][Batch 99], Speed: 348.442 samples/sec, CrossEntropy=2.211, SmoothL1=0.942 [Epoch 172][Batch 199], Speed: 358.917 samples/sec, CrossEntropy=2.233, SmoothL1=0.948 [Epoch 172][Batch 299], Speed: 353.263 samples/sec, CrossEntropy=2.214, SmoothL1=0.945 [Epoch 172][Batch 399], Speed: 342.738 samples/sec, CrossEntropy=2.212, SmoothL1=0.948 [Epoch 172][Batch 499], Speed: 352.330 samples/sec, CrossEntropy=2.216, SmoothL1=0.953 [Epoch 172][Batch 599], Speed: 356.184 samples/sec, CrossEntropy=2.215, SmoothL1=0.951 [Epoch 172][Batch 699], Speed: 353.371 samples/sec, CrossEntropy=2.213, SmoothL1=0.948 [Epoch 172][Batch 799], Speed: 359.731 samples/sec, CrossEntropy=2.213, SmoothL1=0.946 [Epoch 172][Batch 899], Speed: 351.444 samples/sec, CrossEntropy=2.207, SmoothL1=0.944 [Epoch 172][Batch 999], Speed: 358.427 samples/sec, CrossEntropy=2.204, SmoothL1=0.943 [Epoch 172][Batch 1099], Speed: 351.197 samples/sec, CrossEntropy=2.201, SmoothL1=0.942 [Epoch 172][Batch 1199], Speed: 344.605 samples/sec, CrossEntropy=2.202, SmoothL1=0.942 [Epoch 172][Batch 1299], Speed: 361.449 samples/sec, CrossEntropy=2.199, SmoothL1=0.939 [Epoch 172][Batch 1399], Speed: 356.988 samples/sec, CrossEntropy=2.199, SmoothL1=0.939 [Epoch 172][Batch 1499], Speed: 348.874 samples/sec, CrossEntropy=2.199, SmoothL1=0.939 [Epoch 172][Batch 1599], Speed: 349.497 samples/sec, CrossEntropy=2.199, SmoothL1=0.939 [Epoch 172][Batch 1699], Speed: 350.389 samples/sec, CrossEntropy=2.198, SmoothL1=0.939 [Epoch 172][Batch 1799], Speed: 357.268 samples/sec, CrossEntropy=2.198, SmoothL1=0.940 [Epoch 172] Training cost: 334.525, CrossEntropy=2.197, SmoothL1=0.939 [Epoch 172] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.413 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.435 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.232 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.331 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.079 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.376 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.584 person=34.5 bicycle=16.4 car=20.2 motorcycle=27.4 airplane=45.6 bus=50.0 train=53.0 truck=21.6 boat=11.2 traffic light=8.0 fire hydrant=45.7 stop sign=46.8 parking meter=31.4 bench=13.8 bird=15.8 cat=53.2 dog=46.9 horse=41.6 sheep=33.0 cow=31.9 elephant=46.2 bear=56.5 zebra=48.3 giraffe=50.0 backpack=4.0 umbrella=22.0 handbag=3.7 tie=14.4 suitcase=18.8 frisbee=31.1 skis=11.1 snowboard=13.1 sports ball=17.9 kite=16.8 baseball bat=10.2 baseball glove=13.2 skateboard=26.9 surfboard=18.4 tennis racket=26.2 bottle=13.6 wine glass=12.5 cup=19.1 fork=15.3 knife=5.3 spoon=4.6 bowl=25.2 banana=15.2 apple=10.9 sandwich=29.0 orange=20.0 broccoli=13.7 carrot=10.7 hot dog=22.0 pizza=36.8 donut=26.6 cake=20.6 chair=13.0 couch=33.8 potted plant=14.1 bed=35.0 dining table=21.1 toilet=46.8 tv=41.7 laptop=44.1 mouse=32.8 remote=8.1 keyboard=33.3 cell phone=15.6 microwave=35.3 oven=27.7 toaster=7.1 sink=23.4 refrigerator=38.7 book=4.8 clock=29.7 vase=16.6 scissors=19.1 teddy bear=33.2 hair drier=0.0 toothbrush=8.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 173][Batch 99], Speed: 355.535 samples/sec, CrossEntropy=2.223, SmoothL1=0.944 [Epoch 173][Batch 199], Speed: 357.829 samples/sec, CrossEntropy=2.204, SmoothL1=0.941 [Epoch 173][Batch 299], Speed: 363.260 samples/sec, CrossEntropy=2.211, SmoothL1=0.942 [Epoch 173][Batch 399], Speed: 359.167 samples/sec, CrossEntropy=2.204, SmoothL1=0.943 [Epoch 173][Batch 499], Speed: 348.427 samples/sec, CrossEntropy=2.188, SmoothL1=0.933 [Epoch 173][Batch 599], Speed: 356.536 samples/sec, CrossEntropy=2.186, SmoothL1=0.929 [Epoch 173][Batch 699], Speed: 361.153 samples/sec, CrossEntropy=2.185, SmoothL1=0.928 [Epoch 173][Batch 799], Speed: 360.017 samples/sec, CrossEntropy=2.183, SmoothL1=0.929 [Epoch 173][Batch 899], Speed: 351.638 samples/sec, CrossEntropy=2.184, SmoothL1=0.933 [Epoch 173][Batch 999], Speed: 354.472 samples/sec, CrossEntropy=2.181, SmoothL1=0.934 [Epoch 173][Batch 1099], Speed: 361.869 samples/sec, CrossEntropy=2.178, SmoothL1=0.934 [Epoch 173][Batch 1199], Speed: 356.180 samples/sec, CrossEntropy=2.182, SmoothL1=0.936 [Epoch 173][Batch 1299], Speed: 347.645 samples/sec, CrossEntropy=2.181, SmoothL1=0.937 [Epoch 173][Batch 1399], Speed: 348.316 samples/sec, CrossEntropy=2.183, SmoothL1=0.936 [Epoch 173][Batch 1499], Speed: 349.273 samples/sec, CrossEntropy=2.180, SmoothL1=0.934 [Epoch 173][Batch 1599], Speed: 348.894 samples/sec, CrossEntropy=2.181, SmoothL1=0.933 [Epoch 173][Batch 1699], Speed: 349.520 samples/sec, CrossEntropy=2.183, SmoothL1=0.934 [Epoch 173][Batch 1799], Speed: 361.802 samples/sec, CrossEntropy=2.186, SmoothL1=0.936 [Epoch 173] Training cost: 334.993, CrossEntropy=2.185, SmoothL1=0.937 [Epoch 173] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.247 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.413 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.259 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.587 person=34.4 bicycle=16.8 car=20.1 motorcycle=27.4 airplane=45.4 bus=49.9 train=53.8 truck=21.5 boat=11.7 traffic light=8.1 fire hydrant=46.1 stop sign=46.0 parking meter=33.5 bench=13.4 bird=15.4 cat=53.6 dog=46.4 horse=40.9 sheep=32.7 cow=31.8 elephant=45.7 bear=54.8 zebra=49.2 giraffe=50.0 backpack=3.9 umbrella=22.2 handbag=3.4 tie=14.5 suitcase=19.9 frisbee=31.4 skis=11.1 snowboard=12.8 sports ball=18.3 kite=16.9 baseball bat=9.3 baseball glove=12.9 skateboard=26.6 surfboard=18.5 tennis racket=26.7 bottle=13.5 wine glass=13.0 cup=18.9 fork=15.3 knife=5.6 spoon=4.8 bowl=25.5 banana=15.0 apple=10.4 sandwich=29.3 orange=20.1 broccoli=13.5 carrot=11.2 hot dog=22.7 pizza=36.2 donut=27.3 cake=20.1 chair=13.2 couch=33.4 potted plant=13.9 bed=33.8 dining table=21.0 toilet=46.5 tv=42.6 laptop=44.4 mouse=31.8 remote=7.8 keyboard=33.9 cell phone=15.9 microwave=35.0 oven=27.5 toaster=4.7 sink=23.0 refrigerator=38.6 book=5.0 clock=29.1 vase=17.1 scissors=20.8 teddy bear=32.7 hair drier=0.0 toothbrush=7.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.7 [Epoch 174][Batch 99], Speed: 354.836 samples/sec, CrossEntropy=2.146, SmoothL1=0.903 [Epoch 174][Batch 199], Speed: 361.459 samples/sec, CrossEntropy=2.143, SmoothL1=0.928 [Epoch 174][Batch 299], Speed: 349.256 samples/sec, CrossEntropy=2.157, SmoothL1=0.929 [Epoch 174][Batch 399], Speed: 360.599 samples/sec, CrossEntropy=2.178, SmoothL1=0.939 [Epoch 174][Batch 499], Speed: 357.731 samples/sec, CrossEntropy=2.180, SmoothL1=0.937 [Epoch 174][Batch 599], Speed: 343.718 samples/sec, CrossEntropy=2.176, SmoothL1=0.942 [Epoch 174][Batch 699], Speed: 343.696 samples/sec, CrossEntropy=2.180, SmoothL1=0.940 [Epoch 174][Batch 799], Speed: 358.355 samples/sec, CrossEntropy=2.185, SmoothL1=0.944 [Epoch 174][Batch 899], Speed: 354.604 samples/sec, CrossEntropy=2.189, SmoothL1=0.943 [Epoch 174][Batch 999], Speed: 354.173 samples/sec, CrossEntropy=2.191, SmoothL1=0.946 [Epoch 174][Batch 1099], Speed: 347.902 samples/sec, CrossEntropy=2.192, SmoothL1=0.947 [Epoch 174][Batch 1199], Speed: 357.206 samples/sec, CrossEntropy=2.191, SmoothL1=0.946 [Epoch 174][Batch 1299], Speed: 353.593 samples/sec, CrossEntropy=2.192, SmoothL1=0.946 [Epoch 174][Batch 1399], Speed: 344.519 samples/sec, CrossEntropy=2.192, SmoothL1=0.946 [Epoch 174][Batch 1499], Speed: 345.463 samples/sec, CrossEntropy=2.191, SmoothL1=0.945 [Epoch 174][Batch 1599], Speed: 357.493 samples/sec, CrossEntropy=2.188, SmoothL1=0.944 [Epoch 174][Batch 1699], Speed: 354.370 samples/sec, CrossEntropy=2.188, SmoothL1=0.942 [Epoch 174][Batch 1799], Speed: 353.737 samples/sec, CrossEntropy=2.188, SmoothL1=0.942 [Epoch 174] Training cost: 335.192, CrossEntropy=2.187, SmoothL1=0.941 [Epoch 174] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.260 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.263 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.331 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.079 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.377 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.585 person=34.4 bicycle=16.5 car=20.1 motorcycle=27.8 airplane=45.3 bus=49.8 train=54.6 truck=21.4 boat=12.0 traffic light=7.6 fire hydrant=45.6 stop sign=45.9 parking meter=31.3 bench=13.9 bird=16.0 cat=54.4 dog=46.9 horse=40.9 sheep=32.8 cow=31.3 elephant=45.9 bear=57.4 zebra=48.8 giraffe=49.2 backpack=4.0 umbrella=22.2 handbag=3.6 tie=14.4 suitcase=19.2 frisbee=30.4 skis=11.7 snowboard=12.8 sports ball=17.7 kite=17.8 baseball bat=10.1 baseball glove=13.4 skateboard=26.9 surfboard=18.2 tennis racket=25.5 bottle=13.4 wine glass=12.7 cup=19.1 fork=15.2 knife=5.4 spoon=4.6 bowl=25.1 banana=15.1 apple=10.5 sandwich=29.5 orange=20.6 broccoli=13.4 carrot=10.5 hot dog=23.4 pizza=36.7 donut=27.2 cake=21.0 chair=13.1 couch=34.7 potted plant=13.6 bed=34.9 dining table=21.1 toilet=47.1 tv=42.4 laptop=44.0 mouse=32.8 remote=7.3 keyboard=33.4 cell phone=15.7 microwave=37.4 oven=27.3 toaster=8.8 sink=23.5 refrigerator=37.6 book=4.6 clock=29.7 vase=17.0 scissors=19.5 teddy bear=32.9 hair drier=0.0 toothbrush=7.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 175][Batch 99], Speed: 359.489 samples/sec, CrossEntropy=2.197, SmoothL1=0.927 [Epoch 175][Batch 199], Speed: 362.423 samples/sec, CrossEntropy=2.206, SmoothL1=0.940 [Epoch 175][Batch 299], Speed: 347.216 samples/sec, CrossEntropy=2.201, SmoothL1=0.943 [Epoch 175][Batch 399], Speed: 351.411 samples/sec, CrossEntropy=2.189, SmoothL1=0.940 [Epoch 175][Batch 499], Speed: 345.824 samples/sec, CrossEntropy=2.184, SmoothL1=0.934 [Epoch 175][Batch 599], Speed: 351.394 samples/sec, CrossEntropy=2.192, SmoothL1=0.939 [Epoch 175][Batch 699], Speed: 350.941 samples/sec, CrossEntropy=2.193, SmoothL1=0.940 [Epoch 175][Batch 799], Speed: 351.205 samples/sec, CrossEntropy=2.197, SmoothL1=0.942 [Epoch 175][Batch 899], Speed: 353.126 samples/sec, CrossEntropy=2.196, SmoothL1=0.945 [Epoch 175][Batch 999], Speed: 352.055 samples/sec, CrossEntropy=2.194, SmoothL1=0.944 [Epoch 175][Batch 1099], Speed: 349.122 samples/sec, CrossEntropy=2.192, SmoothL1=0.943 [Epoch 175][Batch 1199], Speed: 352.687 samples/sec, CrossEntropy=2.194, SmoothL1=0.945 [Epoch 175][Batch 1299], Speed: 349.996 samples/sec, CrossEntropy=2.190, SmoothL1=0.943 [Epoch 175][Batch 1399], Speed: 348.956 samples/sec, CrossEntropy=2.189, SmoothL1=0.941 [Epoch 175][Batch 1499], Speed: 354.736 samples/sec, CrossEntropy=2.188, SmoothL1=0.939 [Epoch 175][Batch 1599], Speed: 351.238 samples/sec, CrossEntropy=2.187, SmoothL1=0.938 [Epoch 175][Batch 1699], Speed: 360.938 samples/sec, CrossEntropy=2.184, SmoothL1=0.938 [Epoch 175][Batch 1799], Speed: 350.945 samples/sec, CrossEntropy=2.187, SmoothL1=0.940 [Epoch 175] Training cost: 335.784, CrossEntropy=2.186, SmoothL1=0.939 [Epoch 175] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.439 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.579 person=34.5 bicycle=17.2 car=20.3 motorcycle=28.3 airplane=45.6 bus=50.4 train=55.0 truck=21.9 boat=11.5 traffic light=8.5 fire hydrant=44.3 stop sign=46.6 parking meter=31.1 bench=13.9 bird=15.6 cat=54.6 dog=46.8 horse=41.7 sheep=33.1 cow=32.5 elephant=46.2 bear=57.1 zebra=48.8 giraffe=49.7 backpack=4.0 umbrella=21.9 handbag=3.5 tie=14.4 suitcase=18.6 frisbee=31.5 skis=11.1 snowboard=13.1 sports ball=17.5 kite=17.3 baseball bat=8.8 baseball glove=13.1 skateboard=26.6 surfboard=18.9 tennis racket=26.3 bottle=13.6 wine glass=12.9 cup=19.1 fork=14.8 knife=5.3 spoon=4.5 bowl=25.2 banana=14.6 apple=10.1 sandwich=29.4 orange=19.5 broccoli=13.9 carrot=10.7 hot dog=23.3 pizza=37.3 donut=27.9 cake=21.1 chair=13.3 couch=33.6 potted plant=13.2 bed=34.5 dining table=21.0 toilet=47.4 tv=42.5 laptop=44.2 mouse=33.2 remote=7.4 keyboard=32.4 cell phone=15.7 microwave=36.7 oven=28.0 toaster=9.2 sink=23.0 refrigerator=38.7 book=4.7 clock=30.6 vase=16.8 scissors=19.2 teddy bear=33.2 hair drier=0.0 toothbrush=7.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 176][Batch 99], Speed: 359.806 samples/sec, CrossEntropy=2.227, SmoothL1=0.946 [Epoch 176][Batch 199], Speed: 357.316 samples/sec, CrossEntropy=2.219, SmoothL1=0.935 [Epoch 176][Batch 299], Speed: 353.008 samples/sec, CrossEntropy=2.210, SmoothL1=0.935 [Epoch 176][Batch 399], Speed: 365.745 samples/sec, CrossEntropy=2.211, SmoothL1=0.938 [Epoch 176][Batch 499], Speed: 358.244 samples/sec, CrossEntropy=2.204, SmoothL1=0.936 [Epoch 176][Batch 599], Speed: 343.318 samples/sec, CrossEntropy=2.205, SmoothL1=0.937 [Epoch 176][Batch 699], Speed: 357.736 samples/sec, CrossEntropy=2.200, SmoothL1=0.933 [Epoch 176][Batch 799], Speed: 356.523 samples/sec, CrossEntropy=2.196, SmoothL1=0.933 [Epoch 176][Batch 899], Speed: 357.851 samples/sec, CrossEntropy=2.195, SmoothL1=0.934 [Epoch 176][Batch 999], Speed: 357.056 samples/sec, CrossEntropy=2.194, SmoothL1=0.933 [Epoch 176][Batch 1099], Speed: 347.795 samples/sec, CrossEntropy=2.194, SmoothL1=0.935 [Epoch 176][Batch 1199], Speed: 349.490 samples/sec, CrossEntropy=2.191, SmoothL1=0.935 [Epoch 176][Batch 1299], Speed: 355.225 samples/sec, CrossEntropy=2.190, SmoothL1=0.935 [Epoch 176][Batch 1399], Speed: 359.631 samples/sec, CrossEntropy=2.192, SmoothL1=0.937 [Epoch 176][Batch 1499], Speed: 343.918 samples/sec, CrossEntropy=2.190, SmoothL1=0.935 [Epoch 176][Batch 1599], Speed: 357.232 samples/sec, CrossEntropy=2.191, SmoothL1=0.935 [Epoch 176][Batch 1699], Speed: 345.495 samples/sec, CrossEntropy=2.190, SmoothL1=0.936 [Epoch 176][Batch 1799], Speed: 351.335 samples/sec, CrossEntropy=2.191, SmoothL1=0.936 [Epoch 176] Training cost: 335.363, CrossEntropy=2.190, SmoothL1=0.937 [Epoch 176] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.260 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.443 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.587 person=34.6 bicycle=17.0 car=20.2 motorcycle=27.8 airplane=44.7 bus=50.0 train=54.0 truck=22.2 boat=11.3 traffic light=8.0 fire hydrant=46.1 stop sign=46.4 parking meter=31.6 bench=13.7 bird=15.9 cat=53.5 dog=47.1 horse=41.1 sheep=33.5 cow=32.1 elephant=45.7 bear=56.6 zebra=48.7 giraffe=49.9 backpack=4.0 umbrella=21.9 handbag=3.8 tie=14.6 suitcase=19.0 frisbee=31.7 skis=10.7 snowboard=12.3 sports ball=17.9 kite=16.7 baseball bat=9.7 baseball glove=13.1 skateboard=26.9 surfboard=18.3 tennis racket=25.9 bottle=13.6 wine glass=12.7 cup=19.6 fork=14.8 knife=5.2 spoon=4.5 bowl=25.0 banana=14.9 apple=10.7 sandwich=29.6 orange=20.3 broccoli=13.5 carrot=10.4 hot dog=22.6 pizza=36.8 donut=27.4 cake=20.7 chair=13.3 couch=33.9 potted plant=13.9 bed=34.2 dining table=21.0 toilet=47.5 tv=42.1 laptop=43.6 mouse=32.5 remote=7.9 keyboard=32.7 cell phone=15.7 microwave=35.6 oven=28.2 toaster=9.4 sink=24.5 refrigerator=39.0 book=4.8 clock=29.9 vase=16.7 scissors=21.1 teddy bear=32.9 hair drier=0.0 toothbrush=8.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 177][Batch 99], Speed: 351.015 samples/sec, CrossEntropy=2.207, SmoothL1=0.959 [Epoch 177][Batch 199], Speed: 349.581 samples/sec, CrossEntropy=2.187, SmoothL1=0.944 [Epoch 177][Batch 299], Speed: 347.927 samples/sec, CrossEntropy=2.197, SmoothL1=0.946 [Epoch 177][Batch 399], Speed: 352.915 samples/sec, CrossEntropy=2.192, SmoothL1=0.947 [Epoch 177][Batch 499], Speed: 351.594 samples/sec, CrossEntropy=2.198, SmoothL1=0.945 [Epoch 177][Batch 599], Speed: 356.975 samples/sec, CrossEntropy=2.198, SmoothL1=0.946 [Epoch 177][Batch 699], Speed: 352.367 samples/sec, CrossEntropy=2.194, SmoothL1=0.945 [Epoch 177][Batch 799], Speed: 350.819 samples/sec, CrossEntropy=2.187, SmoothL1=0.940 [Epoch 177][Batch 899], Speed: 360.747 samples/sec, CrossEntropy=2.188, SmoothL1=0.941 [Epoch 177][Batch 999], Speed: 351.159 samples/sec, CrossEntropy=2.182, SmoothL1=0.939 [Epoch 177][Batch 1099], Speed: 350.522 samples/sec, CrossEntropy=2.180, SmoothL1=0.942 [Epoch 177][Batch 1199], Speed: 350.692 samples/sec, CrossEntropy=2.179, SmoothL1=0.941 [Epoch 177][Batch 1299], Speed: 351.311 samples/sec, CrossEntropy=2.181, SmoothL1=0.942 [Epoch 177][Batch 1399], Speed: 356.905 samples/sec, CrossEntropy=2.181, SmoothL1=0.942 [Epoch 177][Batch 1499], Speed: 347.826 samples/sec, CrossEntropy=2.180, SmoothL1=0.941 [Epoch 177][Batch 1599], Speed: 361.647 samples/sec, CrossEntropy=2.181, SmoothL1=0.940 [Epoch 177][Batch 1699], Speed: 354.521 samples/sec, CrossEntropy=2.181, SmoothL1=0.938 [Epoch 177][Batch 1799], Speed: 352.347 samples/sec, CrossEntropy=2.181, SmoothL1=0.937 [Epoch 177] Training cost: 335.444, CrossEntropy=2.181, SmoothL1=0.937 [Epoch 177] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.247 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.412 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.258 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.436 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.232 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.330 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.343 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.077 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.583 person=34.5 bicycle=17.0 car=20.2 motorcycle=27.9 airplane=45.6 bus=50.1 train=53.9 truck=21.8 boat=11.7 traffic light=8.2 fire hydrant=45.4 stop sign=46.0 parking meter=31.8 bench=13.7 bird=15.9 cat=54.0 dog=46.7 horse=41.1 sheep=32.5 cow=32.4 elephant=46.3 bear=53.8 zebra=49.2 giraffe=49.5 backpack=4.2 umbrella=21.8 handbag=3.7 tie=14.2 suitcase=18.8 frisbee=31.7 skis=10.9 snowboard=12.4 sports ball=17.6 kite=16.8 baseball bat=9.2 baseball glove=12.9 skateboard=26.8 surfboard=18.4 tennis racket=26.3 bottle=13.8 wine glass=12.8 cup=18.7 fork=15.4 knife=5.3 spoon=4.4 bowl=24.8 banana=15.3 apple=10.3 sandwich=27.9 orange=19.9 broccoli=13.6 carrot=10.1 hot dog=22.9 pizza=37.4 donut=26.8 cake=20.7 chair=13.0 couch=34.1 potted plant=13.8 bed=34.5 dining table=20.7 toilet=47.8 tv=41.8 laptop=43.7 mouse=33.0 remote=6.9 keyboard=32.6 cell phone=16.1 microwave=34.4 oven=27.0 toaster=5.4 sink=23.9 refrigerator=39.0 book=4.8 clock=29.9 vase=17.0 scissors=19.4 teddy bear=31.9 hair drier=0.0 toothbrush=7.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.7 [Epoch 178][Batch 99], Speed: 365.950 samples/sec, CrossEntropy=2.193, SmoothL1=0.935 [Epoch 178][Batch 199], Speed: 344.395 samples/sec, CrossEntropy=2.180, SmoothL1=0.929 [Epoch 178][Batch 299], Speed: 349.291 samples/sec, CrossEntropy=2.187, SmoothL1=0.938 [Epoch 178][Batch 399], Speed: 345.511 samples/sec, CrossEntropy=2.198, SmoothL1=0.950 [Epoch 178][Batch 499], Speed: 362.453 samples/sec, CrossEntropy=2.189, SmoothL1=0.942 [Epoch 178][Batch 599], Speed: 355.302 samples/sec, CrossEntropy=2.184, SmoothL1=0.939 [Epoch 178][Batch 699], Speed: 343.639 samples/sec, CrossEntropy=2.185, SmoothL1=0.936 [Epoch 178][Batch 799], Speed: 341.273 samples/sec, CrossEntropy=2.177, SmoothL1=0.930 [Epoch 178][Batch 899], Speed: 359.412 samples/sec, CrossEntropy=2.176, SmoothL1=0.928 [Epoch 178][Batch 999], Speed: 358.895 samples/sec, CrossEntropy=2.170, SmoothL1=0.925 [Epoch 178][Batch 1099], Speed: 353.920 samples/sec, CrossEntropy=2.173, SmoothL1=0.927 [Epoch 178][Batch 1199], Speed: 365.913 samples/sec, CrossEntropy=2.175, SmoothL1=0.927 [Epoch 178][Batch 1299], Speed: 351.301 samples/sec, CrossEntropy=2.175, SmoothL1=0.928 [Epoch 178][Batch 1399], Speed: 360.322 samples/sec, CrossEntropy=2.176, SmoothL1=0.930 [Epoch 178][Batch 1499], Speed: 347.888 samples/sec, CrossEntropy=2.175, SmoothL1=0.929 [Epoch 178][Batch 1599], Speed: 353.143 samples/sec, CrossEntropy=2.175, SmoothL1=0.928 [Epoch 178][Batch 1699], Speed: 352.691 samples/sec, CrossEntropy=2.174, SmoothL1=0.926 [Epoch 178][Batch 1799], Speed: 355.693 samples/sec, CrossEntropy=2.172, SmoothL1=0.925 [Epoch 178] Training cost: 335.225, CrossEntropy=2.171, SmoothL1=0.926 [Epoch 178] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.440 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.585 person=34.4 bicycle=16.8 car=20.4 motorcycle=28.1 airplane=45.7 bus=49.2 train=53.3 truck=22.1 boat=11.8 traffic light=8.1 fire hydrant=45.5 stop sign=46.4 parking meter=33.0 bench=13.6 bird=15.3 cat=53.2 dog=47.3 horse=42.0 sheep=32.5 cow=31.9 elephant=47.0 bear=57.6 zebra=48.3 giraffe=49.6 backpack=4.3 umbrella=22.0 handbag=3.8 tie=14.6 suitcase=18.5 frisbee=31.2 skis=10.9 snowboard=13.6 sports ball=17.5 kite=17.3 baseball bat=9.6 baseball glove=13.4 skateboard=27.3 surfboard=18.5 tennis racket=25.8 bottle=13.5 wine glass=12.7 cup=18.9 fork=15.3 knife=5.4 spoon=4.2 bowl=25.4 banana=15.3 apple=10.8 sandwich=28.4 orange=20.3 broccoli=13.8 carrot=9.8 hot dog=23.1 pizza=37.1 donut=27.0 cake=20.7 chair=13.2 couch=33.7 potted plant=14.5 bed=34.3 dining table=20.8 toilet=47.1 tv=42.2 laptop=44.5 mouse=33.4 remote=7.6 keyboard=32.7 cell phone=16.1 microwave=36.9 oven=27.8 toaster=8.4 sink=23.7 refrigerator=39.0 book=4.9 clock=30.4 vase=16.9 scissors=19.9 teddy bear=32.3 hair drier=0.0 toothbrush=8.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 179][Batch 99], Speed: 341.410 samples/sec, CrossEntropy=2.157, SmoothL1=0.922 [Epoch 179][Batch 199], Speed: 349.836 samples/sec, CrossEntropy=2.158, SmoothL1=0.921 [Epoch 179][Batch 299], Speed: 347.692 samples/sec, CrossEntropy=2.158, SmoothL1=0.924 [Epoch 179][Batch 399], Speed: 351.695 samples/sec, CrossEntropy=2.150, SmoothL1=0.912 [Epoch 179][Batch 499], Speed: 353.174 samples/sec, CrossEntropy=2.156, SmoothL1=0.918 [Epoch 179][Batch 599], Speed: 360.291 samples/sec, CrossEntropy=2.161, SmoothL1=0.918 [Epoch 179][Batch 699], Speed: 360.908 samples/sec, CrossEntropy=2.165, SmoothL1=0.923 [Epoch 179][Batch 799], Speed: 343.884 samples/sec, CrossEntropy=2.166, SmoothL1=0.927 [Epoch 179][Batch 899], Speed: 338.224 samples/sec, CrossEntropy=2.163, SmoothL1=0.924 [Epoch 179][Batch 999], Speed: 354.226 samples/sec, CrossEntropy=2.163, SmoothL1=0.927 [Epoch 179][Batch 1099], Speed: 344.474 samples/sec, CrossEntropy=2.160, SmoothL1=0.924 [Epoch 179][Batch 1199], Speed: 355.786 samples/sec, CrossEntropy=2.164, SmoothL1=0.927 [Epoch 179][Batch 1299], Speed: 360.688 samples/sec, CrossEntropy=2.168, SmoothL1=0.930 [Epoch 179][Batch 1399], Speed: 346.866 samples/sec, CrossEntropy=2.169, SmoothL1=0.931 [Epoch 179][Batch 1499], Speed: 352.690 samples/sec, CrossEntropy=2.169, SmoothL1=0.931 [Epoch 179][Batch 1599], Speed: 353.445 samples/sec, CrossEntropy=2.168, SmoothL1=0.933 [Epoch 179][Batch 1699], Speed: 358.022 samples/sec, CrossEntropy=2.169, SmoothL1=0.931 [Epoch 179][Batch 1799], Speed: 356.042 samples/sec, CrossEntropy=2.169, SmoothL1=0.930 [Epoch 179] Training cost: 335.784, CrossEntropy=2.169, SmoothL1=0.930 [Epoch 179] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.442 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.079 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.588 person=34.5 bicycle=16.6 car=20.1 motorcycle=27.4 airplane=45.8 bus=49.6 train=54.2 truck=22.3 boat=11.6 traffic light=8.5 fire hydrant=45.8 stop sign=46.7 parking meter=33.3 bench=13.3 bird=15.9 cat=53.9 dog=46.9 horse=42.0 sheep=32.9 cow=32.1 elephant=46.8 bear=55.1 zebra=48.5 giraffe=49.4 backpack=4.0 umbrella=21.7 handbag=3.8 tie=14.6 suitcase=18.7 frisbee=31.5 skis=10.7 snowboard=12.5 sports ball=17.8 kite=16.7 baseball bat=10.1 baseball glove=13.6 skateboard=26.3 surfboard=18.3 tennis racket=25.7 bottle=13.5 wine glass=13.2 cup=19.0 fork=15.4 knife=5.7 spoon=4.3 bowl=24.5 banana=15.0 apple=10.3 sandwich=28.5 orange=19.5 broccoli=13.3 carrot=10.3 hot dog=23.5 pizza=36.0 donut=27.1 cake=20.2 chair=13.0 couch=34.8 potted plant=13.5 bed=33.7 dining table=20.5 toilet=47.3 tv=41.4 laptop=44.7 mouse=32.7 remote=7.7 keyboard=33.6 cell phone=16.3 microwave=36.2 oven=28.3 toaster=9.2 sink=23.8 refrigerator=37.9 book=4.8 clock=30.2 vase=16.8 scissors=22.6 teddy bear=32.9 hair drier=0.7 toothbrush=8.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 180][Batch 99], Speed: 350.075 samples/sec, CrossEntropy=2.160, SmoothL1=0.916 [Epoch 180][Batch 199], Speed: 357.921 samples/sec, CrossEntropy=2.172, SmoothL1=0.919 [Epoch 180][Batch 299], Speed: 359.029 samples/sec, CrossEntropy=2.170, SmoothL1=0.924 [Epoch 180][Batch 399], Speed: 351.932 samples/sec, CrossEntropy=2.183, SmoothL1=0.934 [Epoch 180][Batch 499], Speed: 359.094 samples/sec, CrossEntropy=2.185, SmoothL1=0.934 [Epoch 180][Batch 599], Speed: 355.442 samples/sec, CrossEntropy=2.180, SmoothL1=0.932 [Epoch 180][Batch 699], Speed: 349.997 samples/sec, CrossEntropy=2.176, SmoothL1=0.930 [Epoch 180][Batch 799], Speed: 346.903 samples/sec, CrossEntropy=2.170, SmoothL1=0.927 [Epoch 180][Batch 899], Speed: 361.231 samples/sec, CrossEntropy=2.170, SmoothL1=0.926 [Epoch 180][Batch 999], Speed: 350.800 samples/sec, CrossEntropy=2.173, SmoothL1=0.928 [Epoch 180][Batch 1099], Speed: 362.830 samples/sec, CrossEntropy=2.173, SmoothL1=0.927 [Epoch 180][Batch 1199], Speed: 364.002 samples/sec, CrossEntropy=2.171, SmoothL1=0.926 [Epoch 180][Batch 1299], Speed: 348.356 samples/sec, CrossEntropy=2.170, SmoothL1=0.925 [Epoch 180][Batch 1399], Speed: 350.118 samples/sec, CrossEntropy=2.169, SmoothL1=0.925 [Epoch 180][Batch 1499], Speed: 350.140 samples/sec, CrossEntropy=2.168, SmoothL1=0.925 [Epoch 180][Batch 1599], Speed: 352.651 samples/sec, CrossEntropy=2.168, SmoothL1=0.924 [Epoch 180][Batch 1699], Speed: 349.516 samples/sec, CrossEntropy=2.169, SmoothL1=0.925 [Epoch 180][Batch 1799], Speed: 352.848 samples/sec, CrossEntropy=2.169, SmoothL1=0.925 [Epoch 180] Training cost: 334.839, CrossEntropy=2.169, SmoothL1=0.925 [Epoch 180] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.079 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.582 person=34.5 bicycle=16.9 car=20.0 motorcycle=27.9 airplane=46.3 bus=49.7 train=54.6 truck=22.2 boat=11.7 traffic light=8.3 fire hydrant=46.0 stop sign=46.4 parking meter=32.1 bench=13.6 bird=15.5 cat=53.7 dog=46.9 horse=41.9 sheep=33.6 cow=32.0 elephant=46.9 bear=55.9 zebra=48.8 giraffe=49.8 backpack=3.8 umbrella=22.0 handbag=3.7 tie=14.2 suitcase=18.5 frisbee=31.5 skis=11.0 snowboard=13.1 sports ball=17.8 kite=17.1 baseball bat=10.6 baseball glove=13.2 skateboard=27.0 surfboard=18.2 tennis racket=25.7 bottle=13.8 wine glass=12.7 cup=19.0 fork=15.6 knife=5.6 spoon=4.6 bowl=24.9 banana=14.8 apple=10.6 sandwich=28.6 orange=21.0 broccoli=13.4 carrot=10.2 hot dog=22.5 pizza=36.3 donut=27.3 cake=20.2 chair=13.4 couch=33.8 potted plant=13.4 bed=33.8 dining table=20.6 toilet=47.7 tv=41.8 laptop=44.7 mouse=32.6 remote=7.7 keyboard=33.5 cell phone=16.2 microwave=35.3 oven=27.6 toaster=10.1 sink=23.4 refrigerator=38.4 book=4.8 clock=29.8 vase=16.6 scissors=19.0 teddy bear=32.1 hair drier=0.0 toothbrush=7.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 181][Batch 99], Speed: 360.576 samples/sec, CrossEntropy=2.170, SmoothL1=0.926 [Epoch 181][Batch 199], Speed: 358.530 samples/sec, CrossEntropy=2.166, SmoothL1=0.931 [Epoch 181][Batch 299], Speed: 346.486 samples/sec, CrossEntropy=2.162, SmoothL1=0.931 [Epoch 181][Batch 399], Speed: 362.707 samples/sec, CrossEntropy=2.175, SmoothL1=0.931 [Epoch 181][Batch 499], Speed: 355.681 samples/sec, CrossEntropy=2.177, SmoothL1=0.931 [Epoch 181][Batch 599], Speed: 356.814 samples/sec, CrossEntropy=2.174, SmoothL1=0.931 [Epoch 181][Batch 699], Speed: 351.689 samples/sec, CrossEntropy=2.178, SmoothL1=0.934 [Epoch 181][Batch 799], Speed: 353.770 samples/sec, CrossEntropy=2.171, SmoothL1=0.930 [Epoch 181][Batch 899], Speed: 347.483 samples/sec, CrossEntropy=2.168, SmoothL1=0.929 [Epoch 181][Batch 999], Speed: 349.863 samples/sec, CrossEntropy=2.166, SmoothL1=0.929 [Epoch 181][Batch 1099], Speed: 341.298 samples/sec, CrossEntropy=2.169, SmoothL1=0.930 [Epoch 181][Batch 1199], Speed: 357.733 samples/sec, CrossEntropy=2.169, SmoothL1=0.929 [Epoch 181][Batch 1299], Speed: 352.624 samples/sec, CrossEntropy=2.168, SmoothL1=0.930 [Epoch 181][Batch 1399], Speed: 365.802 samples/sec, CrossEntropy=2.168, SmoothL1=0.931 [Epoch 181][Batch 1499], Speed: 354.223 samples/sec, CrossEntropy=2.170, SmoothL1=0.930 [Epoch 181][Batch 1599], Speed: 349.428 samples/sec, CrossEntropy=2.170, SmoothL1=0.930 [Epoch 181][Batch 1699], Speed: 357.680 samples/sec, CrossEntropy=2.170, SmoothL1=0.931 [Epoch 181][Batch 1799], Speed: 354.715 samples/sec, CrossEntropy=2.172, SmoothL1=0.931 [Epoch 181] Training cost: 335.121, CrossEntropy=2.171, SmoothL1=0.930 [Epoch 181] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.435 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.331 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.584 person=34.4 bicycle=16.5 car=20.1 motorcycle=27.6 airplane=45.3 bus=50.6 train=54.6 truck=21.4 boat=11.2 traffic light=8.2 fire hydrant=46.5 stop sign=46.9 parking meter=32.9 bench=13.5 bird=15.7 cat=53.5 dog=46.3 horse=41.5 sheep=33.1 cow=31.3 elephant=46.5 bear=57.5 zebra=48.4 giraffe=49.6 backpack=4.0 umbrella=22.7 handbag=3.6 tie=14.6 suitcase=18.5 frisbee=31.3 skis=10.3 snowboard=12.5 sports ball=18.0 kite=16.8 baseball bat=10.1 baseball glove=13.7 skateboard=27.1 surfboard=18.3 tennis racket=26.0 bottle=13.8 wine glass=12.6 cup=19.0 fork=15.3 knife=5.8 spoon=4.5 bowl=24.6 banana=14.6 apple=10.4 sandwich=28.9 orange=20.7 broccoli=13.5 carrot=10.0 hot dog=23.1 pizza=36.4 donut=27.5 cake=21.0 chair=13.3 couch=34.5 potted plant=14.1 bed=34.3 dining table=20.5 toilet=47.0 tv=42.1 laptop=44.2 mouse=33.5 remote=7.6 keyboard=33.2 cell phone=15.9 microwave=36.1 oven=27.7 toaster=7.2 sink=23.1 refrigerator=39.2 book=4.8 clock=30.1 vase=16.6 scissors=20.1 teddy bear=31.9 hair drier=0.0 toothbrush=7.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 182][Batch 99], Speed: 346.671 samples/sec, CrossEntropy=2.189, SmoothL1=0.949 [Epoch 182][Batch 199], Speed: 359.715 samples/sec, CrossEntropy=2.181, SmoothL1=0.938 [Epoch 182][Batch 299], Speed: 355.194 samples/sec, CrossEntropy=2.173, SmoothL1=0.929 [Epoch 182][Batch 399], Speed: 364.107 samples/sec, CrossEntropy=2.180, SmoothL1=0.936 [Epoch 182][Batch 499], Speed: 356.222 samples/sec, CrossEntropy=2.177, SmoothL1=0.936 [Epoch 182][Batch 599], Speed: 346.849 samples/sec, CrossEntropy=2.179, SmoothL1=0.940 [Epoch 182][Batch 699], Speed: 364.560 samples/sec, CrossEntropy=2.179, SmoothL1=0.941 [Epoch 182][Batch 799], Speed: 348.684 samples/sec, CrossEntropy=2.182, SmoothL1=0.942 [Epoch 182][Batch 899], Speed: 360.032 samples/sec, CrossEntropy=2.187, SmoothL1=0.944 [Epoch 182][Batch 999], Speed: 353.009 samples/sec, CrossEntropy=2.181, SmoothL1=0.942 [Epoch 182][Batch 1099], Speed: 347.548 samples/sec, CrossEntropy=2.183, SmoothL1=0.944 [Epoch 182][Batch 1199], Speed: 355.530 samples/sec, CrossEntropy=2.181, SmoothL1=0.941 [Epoch 182][Batch 1299], Speed: 351.000 samples/sec, CrossEntropy=2.181, SmoothL1=0.940 [Epoch 182][Batch 1399], Speed: 354.477 samples/sec, CrossEntropy=2.177, SmoothL1=0.936 [Epoch 182][Batch 1499], Speed: 348.441 samples/sec, CrossEntropy=2.176, SmoothL1=0.936 [Epoch 182][Batch 1599], Speed: 347.956 samples/sec, CrossEntropy=2.174, SmoothL1=0.935 [Epoch 182][Batch 1699], Speed: 351.979 samples/sec, CrossEntropy=2.175, SmoothL1=0.936 [Epoch 182][Batch 1799], Speed: 352.582 samples/sec, CrossEntropy=2.176, SmoothL1=0.936 [Epoch 182] Training cost: 335.093, CrossEntropy=2.174, SmoothL1=0.936 [Epoch 182] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.435 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.330 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.343 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.578 person=34.4 bicycle=16.9 car=20.1 motorcycle=28.2 airplane=45.5 bus=50.2 train=53.4 truck=22.4 boat=11.4 traffic light=8.4 fire hydrant=46.4 stop sign=46.1 parking meter=33.4 bench=13.7 bird=16.0 cat=53.5 dog=46.7 horse=41.3 sheep=33.7 cow=31.4 elephant=46.2 bear=56.1 zebra=49.1 giraffe=49.4 backpack=4.2 umbrella=22.1 handbag=3.5 tie=14.8 suitcase=18.2 frisbee=31.4 skis=11.2 snowboard=13.2 sports ball=18.0 kite=16.8 baseball bat=10.2 baseball glove=12.8 skateboard=27.3 surfboard=18.0 tennis racket=26.0 bottle=13.4 wine glass=12.7 cup=18.9 fork=15.4 knife=5.7 spoon=4.7 bowl=24.4 banana=14.4 apple=11.0 sandwich=28.6 orange=20.5 broccoli=13.6 carrot=10.5 hot dog=23.7 pizza=36.7 donut=26.9 cake=20.9 chair=13.2 couch=33.6 potted plant=13.7 bed=34.4 dining table=21.2 toilet=47.2 tv=42.0 laptop=44.7 mouse=33.4 remote=7.9 keyboard=33.5 cell phone=15.9 microwave=35.2 oven=26.1 toaster=7.1 sink=23.1 refrigerator=39.1 book=4.8 clock=29.7 vase=16.7 scissors=20.4 teddy bear=33.1 hair drier=0.0 toothbrush=7.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 183][Batch 99], Speed: 357.223 samples/sec, CrossEntropy=2.167, SmoothL1=0.924 [Epoch 183][Batch 199], Speed: 353.015 samples/sec, CrossEntropy=2.153, SmoothL1=0.915 [Epoch 183][Batch 299], Speed: 355.895 samples/sec, CrossEntropy=2.155, SmoothL1=0.916 [Epoch 183][Batch 399], Speed: 347.111 samples/sec, CrossEntropy=2.161, SmoothL1=0.919 [Epoch 183][Batch 499], Speed: 342.575 samples/sec, CrossEntropy=2.161, SmoothL1=0.921 [Epoch 183][Batch 599], Speed: 350.162 samples/sec, CrossEntropy=2.160, SmoothL1=0.920 [Epoch 183][Batch 699], Speed: 351.321 samples/sec, CrossEntropy=2.160, SmoothL1=0.921 [Epoch 183][Batch 799], Speed: 350.335 samples/sec, CrossEntropy=2.158, SmoothL1=0.921 [Epoch 183][Batch 899], Speed: 349.853 samples/sec, CrossEntropy=2.161, SmoothL1=0.923 [Epoch 183][Batch 999], Speed: 349.835 samples/sec, CrossEntropy=2.162, SmoothL1=0.923 [Epoch 183][Batch 1099], Speed: 357.186 samples/sec, CrossEntropy=2.164, SmoothL1=0.924 [Epoch 183][Batch 1199], Speed: 351.872 samples/sec, CrossEntropy=2.164, SmoothL1=0.926 [Epoch 183][Batch 1299], Speed: 356.663 samples/sec, CrossEntropy=2.160, SmoothL1=0.923 [Epoch 183][Batch 1399], Speed: 352.009 samples/sec, CrossEntropy=2.162, SmoothL1=0.924 [Epoch 183][Batch 1499], Speed: 353.538 samples/sec, CrossEntropy=2.164, SmoothL1=0.924 [Epoch 183][Batch 1599], Speed: 357.356 samples/sec, CrossEntropy=2.164, SmoothL1=0.925 [Epoch 183][Batch 1699], Speed: 352.264 samples/sec, CrossEntropy=2.165, SmoothL1=0.926 [Epoch 183][Batch 1799], Speed: 348.757 samples/sec, CrossEntropy=2.164, SmoothL1=0.924 [Epoch 183] Training cost: 335.413, CrossEntropy=2.165, SmoothL1=0.924 [Epoch 183] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.260 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.435 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.582 person=34.5 bicycle=17.4 car=20.1 motorcycle=28.1 airplane=44.9 bus=50.4 train=53.9 truck=22.5 boat=11.3 traffic light=8.1 fire hydrant=45.1 stop sign=46.3 parking meter=32.2 bench=13.2 bird=16.0 cat=54.1 dog=46.7 horse=42.1 sheep=33.2 cow=32.2 elephant=46.7 bear=55.2 zebra=48.5 giraffe=49.7 backpack=4.0 umbrella=22.2 handbag=3.3 tie=15.0 suitcase=18.2 frisbee=31.2 skis=11.5 snowboard=12.2 sports ball=18.3 kite=17.0 baseball bat=9.4 baseball glove=13.3 skateboard=27.0 surfboard=18.2 tennis racket=26.1 bottle=13.6 wine glass=13.0 cup=18.8 fork=15.1 knife=5.4 spoon=4.7 bowl=24.2 banana=14.9 apple=10.0 sandwich=27.8 orange=20.4 broccoli=13.9 carrot=10.3 hot dog=22.7 pizza=37.4 donut=27.6 cake=20.6 chair=13.0 couch=33.2 potted plant=13.5 bed=34.7 dining table=20.9 toilet=48.4 tv=42.2 laptop=44.3 mouse=32.0 remote=7.3 keyboard=33.4 cell phone=16.4 microwave=35.5 oven=28.3 toaster=9.2 sink=22.8 refrigerator=37.5 book=4.8 clock=30.3 vase=17.1 scissors=20.8 teddy bear=31.8 hair drier=0.0 toothbrush=7.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 184][Batch 99], Speed: 354.330 samples/sec, CrossEntropy=2.134, SmoothL1=0.876 [Epoch 184][Batch 199], Speed: 353.499 samples/sec, CrossEntropy=2.179, SmoothL1=0.909 [Epoch 184][Batch 299], Speed: 350.173 samples/sec, CrossEntropy=2.164, SmoothL1=0.909 [Epoch 184][Batch 399], Speed: 351.160 samples/sec, CrossEntropy=2.153, SmoothL1=0.915 [Epoch 184][Batch 499], Speed: 349.464 samples/sec, CrossEntropy=2.162, SmoothL1=0.922 [Epoch 184][Batch 599], Speed: 346.587 samples/sec, CrossEntropy=2.159, SmoothL1=0.922 [Epoch 184][Batch 699], Speed: 358.460 samples/sec, CrossEntropy=2.159, SmoothL1=0.922 [Epoch 184][Batch 799], Speed: 356.041 samples/sec, CrossEntropy=2.154, SmoothL1=0.921 [Epoch 184][Batch 899], Speed: 341.425 samples/sec, CrossEntropy=2.154, SmoothL1=0.923 [Epoch 184][Batch 999], Speed: 351.708 samples/sec, CrossEntropy=2.157, SmoothL1=0.926 [Epoch 184][Batch 1099], Speed: 345.724 samples/sec, CrossEntropy=2.158, SmoothL1=0.926 [Epoch 184][Batch 1199], Speed: 347.830 samples/sec, CrossEntropy=2.161, SmoothL1=0.926 [Epoch 184][Batch 1299], Speed: 341.745 samples/sec, CrossEntropy=2.162, SmoothL1=0.926 [Epoch 184][Batch 1399], Speed: 358.673 samples/sec, CrossEntropy=2.164, SmoothL1=0.928 [Epoch 184][Batch 1499], Speed: 350.597 samples/sec, CrossEntropy=2.162, SmoothL1=0.925 [Epoch 184][Batch 1599], Speed: 356.589 samples/sec, CrossEntropy=2.160, SmoothL1=0.925 [Epoch 184][Batch 1699], Speed: 339.437 samples/sec, CrossEntropy=2.161, SmoothL1=0.926 [Epoch 184][Batch 1799], Speed: 348.487 samples/sec, CrossEntropy=2.162, SmoothL1=0.926 [Epoch 184] Training cost: 335.776, CrossEntropy=2.164, SmoothL1=0.926 [Epoch 184] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.259 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.378 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.586 person=34.6 bicycle=16.9 car=20.1 motorcycle=28.1 airplane=46.1 bus=49.9 train=54.1 truck=21.7 boat=11.1 traffic light=8.3 fire hydrant=45.1 stop sign=46.1 parking meter=32.6 bench=13.7 bird=15.7 cat=54.9 dog=46.6 horse=41.5 sheep=33.0 cow=32.2 elephant=45.4 bear=57.0 zebra=48.9 giraffe=49.6 backpack=4.2 umbrella=22.1 handbag=3.4 tie=13.9 suitcase=18.8 frisbee=31.8 skis=11.4 snowboard=12.0 sports ball=18.0 kite=16.9 baseball bat=9.7 baseball glove=13.8 skateboard=27.7 surfboard=18.3 tennis racket=25.8 bottle=13.4 wine glass=12.5 cup=18.9 fork=15.1 knife=5.5 spoon=4.2 bowl=24.4 banana=14.8 apple=10.5 sandwich=29.0 orange=20.6 broccoli=13.2 carrot=9.8 hot dog=22.6 pizza=36.1 donut=27.3 cake=20.8 chair=13.3 couch=34.1 potted plant=13.7 bed=35.0 dining table=20.1 toilet=48.8 tv=42.4 laptop=43.7 mouse=33.0 remote=7.1 keyboard=33.8 cell phone=16.0 microwave=36.1 oven=28.0 toaster=5.5 sink=23.4 refrigerator=37.6 book=4.9 clock=30.1 vase=16.9 scissors=19.8 teddy bear=31.9 hair drier=0.0 toothbrush=7.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 185][Batch 99], Speed: 356.632 samples/sec, CrossEntropy=2.174, SmoothL1=0.949 [Epoch 185][Batch 199], Speed: 352.115 samples/sec, CrossEntropy=2.161, SmoothL1=0.937 [Epoch 185][Batch 299], Speed: 357.340 samples/sec, CrossEntropy=2.149, SmoothL1=0.931 [Epoch 185][Batch 399], Speed: 352.469 samples/sec, CrossEntropy=2.144, SmoothL1=0.922 [Epoch 185][Batch 499], Speed: 363.662 samples/sec, CrossEntropy=2.159, SmoothL1=0.925 [Epoch 185][Batch 599], Speed: 353.289 samples/sec, CrossEntropy=2.154, SmoothL1=0.918 [Epoch 185][Batch 699], Speed: 347.488 samples/sec, CrossEntropy=2.156, SmoothL1=0.919 [Epoch 185][Batch 799], Speed: 342.409 samples/sec, CrossEntropy=2.157, SmoothL1=0.921 [Epoch 185][Batch 899], Speed: 350.139 samples/sec, CrossEntropy=2.160, SmoothL1=0.922 [Epoch 185][Batch 999], Speed: 347.353 samples/sec, CrossEntropy=2.160, SmoothL1=0.922 [Epoch 185][Batch 1099], Speed: 349.347 samples/sec, CrossEntropy=2.160, SmoothL1=0.923 [Epoch 185][Batch 1199], Speed: 351.773 samples/sec, CrossEntropy=2.164, SmoothL1=0.925 [Epoch 185][Batch 1299], Speed: 363.150 samples/sec, CrossEntropy=2.162, SmoothL1=0.926 [Epoch 185][Batch 1399], Speed: 354.719 samples/sec, CrossEntropy=2.159, SmoothL1=0.925 [Epoch 185][Batch 1499], Speed: 345.465 samples/sec, CrossEntropy=2.160, SmoothL1=0.925 [Epoch 185][Batch 1599], Speed: 362.238 samples/sec, CrossEntropy=2.164, SmoothL1=0.926 [Epoch 185][Batch 1699], Speed: 357.237 samples/sec, CrossEntropy=2.165, SmoothL1=0.926 [Epoch 185][Batch 1799], Speed: 352.568 samples/sec, CrossEntropy=2.165, SmoothL1=0.927 [Epoch 185] Training cost: 333.705, CrossEntropy=2.163, SmoothL1=0.926 [Epoch 185] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.263 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.439 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.585 person=34.5 bicycle=16.5 car=20.3 motorcycle=27.9 airplane=45.6 bus=49.6 train=53.9 truck=21.5 boat=11.6 traffic light=7.8 fire hydrant=45.4 stop sign=47.0 parking meter=33.5 bench=13.3 bird=15.7 cat=53.8 dog=46.4 horse=41.4 sheep=33.1 cow=31.9 elephant=46.9 bear=58.3 zebra=49.0 giraffe=50.8 backpack=3.9 umbrella=22.4 handbag=3.7 tie=14.0 suitcase=18.3 frisbee=31.9 skis=11.0 snowboard=11.7 sports ball=18.0 kite=16.6 baseball bat=10.1 baseball glove=13.5 skateboard=27.4 surfboard=18.5 tennis racket=26.3 bottle=13.5 wine glass=12.8 cup=19.0 fork=15.0 knife=5.6 spoon=4.6 bowl=24.5 banana=14.4 apple=10.8 sandwich=29.5 orange=20.5 broccoli=13.4 carrot=10.5 hot dog=22.4 pizza=36.8 donut=27.0 cake=20.6 chair=13.1 couch=33.5 potted plant=13.4 bed=34.8 dining table=20.8 toilet=48.7 tv=42.1 laptop=44.8 mouse=32.5 remote=7.5 keyboard=32.8 cell phone=16.4 microwave=35.3 oven=26.3 toaster=8.8 sink=22.9 refrigerator=38.1 book=4.9 clock=30.7 vase=17.0 scissors=20.2 teddy bear=32.1 hair drier=0.0 toothbrush=6.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 186][Batch 99], Speed: 344.726 samples/sec, CrossEntropy=2.141, SmoothL1=0.925 [Epoch 186][Batch 199], Speed: 347.320 samples/sec, CrossEntropy=2.151, SmoothL1=0.924 [Epoch 186][Batch 299], Speed: 351.047 samples/sec, CrossEntropy=2.149, SmoothL1=0.922 [Epoch 186][Batch 399], Speed: 356.818 samples/sec, CrossEntropy=2.151, SmoothL1=0.920 [Epoch 186][Batch 499], Speed: 345.790 samples/sec, CrossEntropy=2.143, SmoothL1=0.918 [Epoch 186][Batch 599], Speed: 347.104 samples/sec, CrossEntropy=2.145, SmoothL1=0.920 [Epoch 186][Batch 699], Speed: 361.878 samples/sec, CrossEntropy=2.151, SmoothL1=0.920 [Epoch 186][Batch 799], Speed: 352.519 samples/sec, CrossEntropy=2.152, SmoothL1=0.921 [Epoch 186][Batch 899], Speed: 356.176 samples/sec, CrossEntropy=2.146, SmoothL1=0.916 [Epoch 186][Batch 999], Speed: 354.279 samples/sec, CrossEntropy=2.146, SmoothL1=0.914 [Epoch 186][Batch 1099], Speed: 338.976 samples/sec, CrossEntropy=2.151, SmoothL1=0.917 [Epoch 186][Batch 1199], Speed: 359.174 samples/sec, CrossEntropy=2.151, SmoothL1=0.918 [Epoch 186][Batch 1299], Speed: 361.418 samples/sec, CrossEntropy=2.150, SmoothL1=0.917 [Epoch 186][Batch 1399], Speed: 346.669 samples/sec, CrossEntropy=2.148, SmoothL1=0.917 [Epoch 186][Batch 1499], Speed: 350.680 samples/sec, CrossEntropy=2.149, SmoothL1=0.918 [Epoch 186][Batch 1599], Speed: 359.025 samples/sec, CrossEntropy=2.152, SmoothL1=0.920 [Epoch 186][Batch 1699], Speed: 363.186 samples/sec, CrossEntropy=2.152, SmoothL1=0.920 [Epoch 186][Batch 1799], Speed: 350.003 samples/sec, CrossEntropy=2.149, SmoothL1=0.918 [Epoch 186] Training cost: 335.324, CrossEntropy=2.148, SmoothL1=0.917 [Epoch 186] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.439 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.334 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.347 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.583 person=34.6 bicycle=17.2 car=20.3 motorcycle=28.3 airplane=46.1 bus=49.5 train=53.9 truck=22.1 boat=11.3 traffic light=8.3 fire hydrant=45.6 stop sign=46.8 parking meter=33.4 bench=13.5 bird=15.9 cat=52.1 dog=47.1 horse=41.9 sheep=32.9 cow=32.0 elephant=46.5 bear=57.0 zebra=48.7 giraffe=49.7 backpack=4.3 umbrella=22.1 handbag=3.6 tie=14.4 suitcase=18.8 frisbee=32.5 skis=10.9 snowboard=12.3 sports ball=18.2 kite=16.9 baseball bat=9.8 baseball glove=13.3 skateboard=27.1 surfboard=18.6 tennis racket=26.5 bottle=13.6 wine glass=12.9 cup=19.1 fork=16.1 knife=5.4 spoon=4.8 bowl=24.5 banana=14.4 apple=9.7 sandwich=28.4 orange=20.7 broccoli=13.6 carrot=11.1 hot dog=22.4 pizza=36.1 donut=27.5 cake=20.9 chair=13.5 couch=33.5 potted plant=13.9 bed=34.1 dining table=21.4 toilet=46.5 tv=41.6 laptop=44.8 mouse=32.8 remote=8.1 keyboard=33.4 cell phone=16.4 microwave=37.0 oven=28.2 toaster=10.4 sink=24.0 refrigerator=38.3 book=4.8 clock=30.2 vase=16.7 scissors=19.5 teddy bear=32.2 hair drier=0.0 toothbrush=7.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 187][Batch 99], Speed: 359.775 samples/sec, CrossEntropy=2.177, SmoothL1=0.916 [Epoch 187][Batch 199], Speed: 352.972 samples/sec, CrossEntropy=2.185, SmoothL1=0.925 [Epoch 187][Batch 299], Speed: 340.934 samples/sec, CrossEntropy=2.163, SmoothL1=0.911 [Epoch 187][Batch 399], Speed: 351.657 samples/sec, CrossEntropy=2.152, SmoothL1=0.906 [Epoch 187][Batch 499], Speed: 350.579 samples/sec, CrossEntropy=2.153, SmoothL1=0.906 [Epoch 187][Batch 599], Speed: 356.027 samples/sec, CrossEntropy=2.153, SmoothL1=0.906 [Epoch 187][Batch 699], Speed: 346.972 samples/sec, CrossEntropy=2.162, SmoothL1=0.915 [Epoch 187][Batch 799], Speed: 349.715 samples/sec, CrossEntropy=2.160, SmoothL1=0.915 [Epoch 187][Batch 899], Speed: 350.330 samples/sec, CrossEntropy=2.165, SmoothL1=0.918 [Epoch 187][Batch 999], Speed: 364.493 samples/sec, CrossEntropy=2.163, SmoothL1=0.916 [Epoch 187][Batch 1099], Speed: 361.651 samples/sec, CrossEntropy=2.164, SmoothL1=0.919 [Epoch 187][Batch 1199], Speed: 360.398 samples/sec, CrossEntropy=2.164, SmoothL1=0.920 [Epoch 187][Batch 1299], Speed: 348.955 samples/sec, CrossEntropy=2.162, SmoothL1=0.918 [Epoch 187][Batch 1399], Speed: 351.259 samples/sec, CrossEntropy=2.161, SmoothL1=0.919 [Epoch 187][Batch 1499], Speed: 353.939 samples/sec, CrossEntropy=2.160, SmoothL1=0.919 [Epoch 187][Batch 1599], Speed: 346.999 samples/sec, CrossEntropy=2.159, SmoothL1=0.920 [Epoch 187][Batch 1699], Speed: 355.072 samples/sec, CrossEntropy=2.159, SmoothL1=0.919 [Epoch 187][Batch 1799], Speed: 359.640 samples/sec, CrossEntropy=2.158, SmoothL1=0.917 [Epoch 187] Training cost: 335.608, CrossEntropy=2.158, SmoothL1=0.917 [Epoch 187] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.260 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.434 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.583 person=34.6 bicycle=16.4 car=20.3 motorcycle=27.9 airplane=46.2 bus=50.6 train=53.6 truck=21.5 boat=11.4 traffic light=8.1 fire hydrant=44.2 stop sign=46.0 parking meter=33.9 bench=13.7 bird=16.2 cat=52.8 dog=47.2 horse=42.0 sheep=33.7 cow=31.8 elephant=46.2 bear=54.9 zebra=48.3 giraffe=49.8 backpack=4.1 umbrella=22.2 handbag=3.7 tie=14.5 suitcase=18.8 frisbee=31.9 skis=11.0 snowboard=11.6 sports ball=18.4 kite=17.0 baseball bat=9.7 baseball glove=13.5 skateboard=27.1 surfboard=18.5 tennis racket=26.4 bottle=13.4 wine glass=13.0 cup=19.1 fork=15.7 knife=5.5 spoon=4.8 bowl=24.5 banana=14.3 apple=9.8 sandwich=28.6 orange=20.4 broccoli=13.7 carrot=10.9 hot dog=22.7 pizza=36.9 donut=27.4 cake=20.6 chair=13.3 couch=33.8 potted plant=14.1 bed=33.6 dining table=21.5 toilet=47.5 tv=42.0 laptop=43.9 mouse=32.5 remote=7.9 keyboard=32.9 cell phone=16.1 microwave=35.7 oven=26.7 toaster=7.6 sink=23.8 refrigerator=38.4 book=4.9 clock=30.0 vase=16.8 scissors=20.0 teddy bear=33.3 hair drier=0.0 toothbrush=7.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 188][Batch 99], Speed: 346.776 samples/sec, CrossEntropy=2.148, SmoothL1=0.911 [Epoch 188][Batch 199], Speed: 344.723 samples/sec, CrossEntropy=2.136, SmoothL1=0.903 [Epoch 188][Batch 299], Speed: 362.004 samples/sec, CrossEntropy=2.139, SmoothL1=0.901 [Epoch 188][Batch 399], Speed: 354.557 samples/sec, CrossEntropy=2.150, SmoothL1=0.914 [Epoch 188][Batch 499], Speed: 357.767 samples/sec, CrossEntropy=2.156, SmoothL1=0.921 [Epoch 188][Batch 599], Speed: 354.824 samples/sec, CrossEntropy=2.156, SmoothL1=0.916 [Epoch 188][Batch 699], Speed: 341.672 samples/sec, CrossEntropy=2.157, SmoothL1=0.920 [Epoch 188][Batch 799], Speed: 352.583 samples/sec, CrossEntropy=2.159, SmoothL1=0.921 [Epoch 188][Batch 899], Speed: 359.976 samples/sec, CrossEntropy=2.164, SmoothL1=0.923 [Epoch 188][Batch 999], Speed: 351.225 samples/sec, CrossEntropy=2.163, SmoothL1=0.923 [Epoch 188][Batch 1099], Speed: 348.224 samples/sec, CrossEntropy=2.160, SmoothL1=0.922 [Epoch 188][Batch 1199], Speed: 348.180 samples/sec, CrossEntropy=2.159, SmoothL1=0.921 [Epoch 188][Batch 1299], Speed: 360.735 samples/sec, CrossEntropy=2.157, SmoothL1=0.920 [Epoch 188][Batch 1399], Speed: 354.678 samples/sec, CrossEntropy=2.156, SmoothL1=0.920 [Epoch 188][Batch 1499], Speed: 346.931 samples/sec, CrossEntropy=2.157, SmoothL1=0.920 [Epoch 188][Batch 1599], Speed: 352.054 samples/sec, CrossEntropy=2.156, SmoothL1=0.921 [Epoch 188][Batch 1699], Speed: 349.542 samples/sec, CrossEntropy=2.157, SmoothL1=0.923 [Epoch 188][Batch 1799], Speed: 347.295 samples/sec, CrossEntropy=2.157, SmoothL1=0.924 [Epoch 188] Training cost: 334.711, CrossEntropy=2.156, SmoothL1=0.923 [Epoch 188] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.412 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.435 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.580 person=34.5 bicycle=16.7 car=20.1 motorcycle=27.9 airplane=46.4 bus=50.6 train=54.5 truck=21.6 boat=11.7 traffic light=8.4 fire hydrant=45.2 stop sign=46.9 parking meter=34.0 bench=13.4 bird=16.4 cat=53.6 dog=45.9 horse=41.4 sheep=33.0 cow=32.5 elephant=46.5 bear=56.7 zebra=48.7 giraffe=49.1 backpack=4.2 umbrella=22.1 handbag=3.8 tie=14.9 suitcase=18.9 frisbee=32.1 skis=11.1 snowboard=12.6 sports ball=18.3 kite=17.1 baseball bat=9.7 baseball glove=13.4 skateboard=26.4 surfboard=18.4 tennis racket=26.3 bottle=13.6 wine glass=13.0 cup=19.2 fork=15.8 knife=5.8 spoon=4.7 bowl=24.6 banana=14.3 apple=10.3 sandwich=28.7 orange=21.0 broccoli=13.3 carrot=10.3 hot dog=22.5 pizza=37.1 donut=27.9 cake=20.8 chair=13.2 couch=33.2 potted plant=13.4 bed=33.8 dining table=20.8 toilet=46.8 tv=42.3 laptop=44.2 mouse=32.8 remote=7.5 keyboard=32.6 cell phone=16.0 microwave=36.6 oven=28.5 toaster=7.8 sink=23.4 refrigerator=38.0 book=4.8 clock=30.1 vase=16.6 scissors=20.0 teddy bear=32.3 hair drier=0.0 toothbrush=6.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 189][Batch 99], Speed: 346.516 samples/sec, CrossEntropy=2.152, SmoothL1=0.916 [Epoch 189][Batch 199], Speed: 345.502 samples/sec, CrossEntropy=2.157, SmoothL1=0.924 [Epoch 189][Batch 299], Speed: 349.576 samples/sec, CrossEntropy=2.158, SmoothL1=0.925 [Epoch 189][Batch 399], Speed: 359.108 samples/sec, CrossEntropy=2.152, SmoothL1=0.925 [Epoch 189][Batch 499], Speed: 363.196 samples/sec, CrossEntropy=2.154, SmoothL1=0.925 [Epoch 189][Batch 599], Speed: 353.942 samples/sec, CrossEntropy=2.156, SmoothL1=0.928 [Epoch 189][Batch 699], Speed: 352.012 samples/sec, CrossEntropy=2.157, SmoothL1=0.928 [Epoch 189][Batch 799], Speed: 353.511 samples/sec, CrossEntropy=2.156, SmoothL1=0.927 [Epoch 189][Batch 899], Speed: 350.310 samples/sec, CrossEntropy=2.155, SmoothL1=0.925 [Epoch 189][Batch 999], Speed: 358.807 samples/sec, CrossEntropy=2.156, SmoothL1=0.924 [Epoch 189][Batch 1099], Speed: 357.776 samples/sec, CrossEntropy=2.159, SmoothL1=0.924 [Epoch 189][Batch 1199], Speed: 364.649 samples/sec, CrossEntropy=2.154, SmoothL1=0.923 [Epoch 189][Batch 1299], Speed: 352.463 samples/sec, CrossEntropy=2.157, SmoothL1=0.924 [Epoch 189][Batch 1399], Speed: 362.636 samples/sec, CrossEntropy=2.158, SmoothL1=0.922 [Epoch 189][Batch 1499], Speed: 355.015 samples/sec, CrossEntropy=2.154, SmoothL1=0.921 [Epoch 189][Batch 1599], Speed: 348.530 samples/sec, CrossEntropy=2.156, SmoothL1=0.920 [Epoch 189][Batch 1699], Speed: 350.369 samples/sec, CrossEntropy=2.156, SmoothL1=0.921 [Epoch 189][Batch 1799], Speed: 360.302 samples/sec, CrossEntropy=2.154, SmoothL1=0.920 [Epoch 189] Training cost: 335.220, CrossEntropy=2.153, SmoothL1=0.919 [Epoch 189] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.259 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.439 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.579 person=34.4 bicycle=16.9 car=20.2 motorcycle=28.1 airplane=46.1 bus=49.6 train=54.1 truck=22.1 boat=11.2 traffic light=8.2 fire hydrant=45.4 stop sign=45.3 parking meter=32.5 bench=13.3 bird=16.1 cat=54.0 dog=46.5 horse=42.1 sheep=33.2 cow=32.3 elephant=47.0 bear=57.9 zebra=48.5 giraffe=49.6 backpack=4.0 umbrella=22.9 handbag=3.7 tie=14.6 suitcase=18.3 frisbee=32.5 skis=10.9 snowboard=12.4 sports ball=17.6 kite=17.2 baseball bat=9.8 baseball glove=13.3 skateboard=27.3 surfboard=18.0 tennis racket=26.7 bottle=13.2 wine glass=13.0 cup=19.0 fork=16.1 knife=5.4 spoon=4.8 bowl=24.8 banana=14.3 apple=10.1 sandwich=27.9 orange=20.3 broccoli=13.8 carrot=10.4 hot dog=23.0 pizza=36.4 donut=27.6 cake=20.7 chair=13.3 couch=33.2 potted plant=13.4 bed=34.8 dining table=21.0 toilet=47.0 tv=41.4 laptop=44.7 mouse=31.8 remote=7.4 keyboard=32.0 cell phone=16.0 microwave=36.0 oven=27.5 toaster=9.1 sink=23.8 refrigerator=38.6 book=4.7 clock=29.8 vase=16.8 scissors=19.6 teddy bear=32.5 hair drier=0.0 toothbrush=6.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 190][Batch 99], Speed: 351.985 samples/sec, CrossEntropy=2.153, SmoothL1=0.902 [Epoch 190][Batch 199], Speed: 355.013 samples/sec, CrossEntropy=2.162, SmoothL1=0.919 [Epoch 190][Batch 299], Speed: 361.059 samples/sec, CrossEntropy=2.173, SmoothL1=0.933 [Epoch 190][Batch 399], Speed: 361.986 samples/sec, CrossEntropy=2.161, SmoothL1=0.925 [Epoch 190][Batch 499], Speed: 352.060 samples/sec, CrossEntropy=2.159, SmoothL1=0.931 [Epoch 190][Batch 599], Speed: 344.360 samples/sec, CrossEntropy=2.153, SmoothL1=0.924 [Epoch 190][Batch 699], Speed: 362.314 samples/sec, CrossEntropy=2.154, SmoothL1=0.927 [Epoch 190][Batch 799], Speed: 352.959 samples/sec, CrossEntropy=2.155, SmoothL1=0.927 [Epoch 190][Batch 899], Speed: 351.337 samples/sec, CrossEntropy=2.156, SmoothL1=0.927 [Epoch 190][Batch 999], Speed: 361.356 samples/sec, CrossEntropy=2.157, SmoothL1=0.927 [Epoch 190][Batch 1099], Speed: 345.026 samples/sec, CrossEntropy=2.159, SmoothL1=0.928 [Epoch 190][Batch 1199], Speed: 357.565 samples/sec, CrossEntropy=2.156, SmoothL1=0.925 [Epoch 190][Batch 1299], Speed: 359.269 samples/sec, CrossEntropy=2.155, SmoothL1=0.925 [Epoch 190][Batch 1399], Speed: 347.181 samples/sec, CrossEntropy=2.153, SmoothL1=0.924 [Epoch 190][Batch 1499], Speed: 338.167 samples/sec, CrossEntropy=2.153, SmoothL1=0.925 [Epoch 190][Batch 1599], Speed: 351.165 samples/sec, CrossEntropy=2.152, SmoothL1=0.924 [Epoch 190][Batch 1699], Speed: 356.082 samples/sec, CrossEntropy=2.152, SmoothL1=0.923 [Epoch 190][Batch 1799], Speed: 355.808 samples/sec, CrossEntropy=2.150, SmoothL1=0.922 [Epoch 190] Training cost: 334.755, CrossEntropy=2.149, SmoothL1=0.921 [Epoch 190] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.260 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.434 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.580 person=34.5 bicycle=16.6 car=20.3 motorcycle=28.1 airplane=44.8 bus=49.9 train=53.8 truck=22.0 boat=11.8 traffic light=8.4 fire hydrant=45.3 stop sign=46.1 parking meter=31.7 bench=13.6 bird=15.8 cat=54.6 dog=47.5 horse=41.9 sheep=33.0 cow=32.0 elephant=46.6 bear=57.7 zebra=48.7 giraffe=49.8 backpack=3.9 umbrella=22.0 handbag=3.8 tie=14.5 suitcase=17.8 frisbee=32.4 skis=10.7 snowboard=11.7 sports ball=17.9 kite=17.4 baseball bat=9.6 baseball glove=13.3 skateboard=28.2 surfboard=18.4 tennis racket=26.2 bottle=13.4 wine glass=12.7 cup=19.3 fork=16.2 knife=5.9 spoon=5.1 bowl=24.7 banana=14.7 apple=10.1 sandwich=29.1 orange=20.6 broccoli=13.6 carrot=10.0 hot dog=23.0 pizza=36.5 donut=27.0 cake=21.6 chair=13.4 couch=34.0 potted plant=13.4 bed=34.1 dining table=21.1 toilet=48.2 tv=42.0 laptop=44.5 mouse=32.4 remote=7.8 keyboard=32.5 cell phone=16.5 microwave=36.1 oven=26.4 toaster=7.4 sink=23.4 refrigerator=39.3 book=4.8 clock=30.1 vase=17.2 scissors=19.6 teddy bear=32.6 hair drier=0.0 toothbrush=6.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 191][Batch 99], Speed: 354.954 samples/sec, CrossEntropy=2.183, SmoothL1=0.937 [Epoch 191][Batch 199], Speed: 355.796 samples/sec, CrossEntropy=2.154, SmoothL1=0.926 [Epoch 191][Batch 299], Speed: 351.044 samples/sec, CrossEntropy=2.155, SmoothL1=0.925 [Epoch 191][Batch 399], Speed: 363.751 samples/sec, CrossEntropy=2.148, SmoothL1=0.916 [Epoch 191][Batch 499], Speed: 360.777 samples/sec, CrossEntropy=2.146, SmoothL1=0.914 [Epoch 191][Batch 599], Speed: 355.263 samples/sec, CrossEntropy=2.150, SmoothL1=0.920 [Epoch 191][Batch 699], Speed: 350.266 samples/sec, CrossEntropy=2.150, SmoothL1=0.917 [Epoch 191][Batch 799], Speed: 352.640 samples/sec, CrossEntropy=2.146, SmoothL1=0.914 [Epoch 191][Batch 899], Speed: 351.054 samples/sec, CrossEntropy=2.148, SmoothL1=0.914 [Epoch 191][Batch 999], Speed: 350.293 samples/sec, CrossEntropy=2.148, SmoothL1=0.914 [Epoch 191][Batch 1099], Speed: 357.004 samples/sec, CrossEntropy=2.150, SmoothL1=0.918 [Epoch 191][Batch 1199], Speed: 346.923 samples/sec, CrossEntropy=2.150, SmoothL1=0.919 [Epoch 191][Batch 1299], Speed: 353.187 samples/sec, CrossEntropy=2.148, SmoothL1=0.918 [Epoch 191][Batch 1399], Speed: 355.789 samples/sec, CrossEntropy=2.152, SmoothL1=0.918 [Epoch 191][Batch 1499], Speed: 353.347 samples/sec, CrossEntropy=2.149, SmoothL1=0.918 [Epoch 191][Batch 1599], Speed: 351.104 samples/sec, CrossEntropy=2.149, SmoothL1=0.919 [Epoch 191][Batch 1699], Speed: 354.638 samples/sec, CrossEntropy=2.148, SmoothL1=0.918 [Epoch 191][Batch 1799], Speed: 351.865 samples/sec, CrossEntropy=2.149, SmoothL1=0.919 [Epoch 191] Training cost: 334.386, CrossEntropy=2.152, SmoothL1=0.920 [Epoch 191] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.260 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.378 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.585 person=34.4 bicycle=16.8 car=20.5 motorcycle=27.8 airplane=46.0 bus=50.2 train=54.1 truck=20.9 boat=11.1 traffic light=8.1 fire hydrant=45.2 stop sign=46.9 parking meter=33.9 bench=13.3 bird=15.7 cat=53.6 dog=46.5 horse=42.5 sheep=33.2 cow=31.7 elephant=46.9 bear=55.9 zebra=48.5 giraffe=49.4 backpack=4.1 umbrella=22.4 handbag=3.7 tie=14.9 suitcase=18.2 frisbee=32.4 skis=10.8 snowboard=13.1 sports ball=17.8 kite=17.0 baseball bat=9.8 baseball glove=14.2 skateboard=27.8 surfboard=18.8 tennis racket=26.3 bottle=13.4 wine glass=12.9 cup=19.1 fork=15.6 knife=5.9 spoon=4.3 bowl=24.6 banana=14.7 apple=10.3 sandwich=28.2 orange=20.6 broccoli=13.9 carrot=10.6 hot dog=22.9 pizza=36.6 donut=27.0 cake=20.7 chair=13.0 couch=33.5 potted plant=13.3 bed=34.1 dining table=21.2 toilet=47.1 tv=41.9 laptop=43.0 mouse=32.0 remote=7.8 keyboard=33.4 cell phone=16.4 microwave=35.5 oven=27.2 toaster=9.7 sink=23.2 refrigerator=37.9 book=4.7 clock=30.2 vase=17.1 scissors=20.5 teddy bear=33.0 hair drier=0.0 toothbrush=6.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 192][Batch 99], Speed: 361.813 samples/sec, CrossEntropy=2.110, SmoothL1=0.878 [Epoch 192][Batch 199], Speed: 359.757 samples/sec, CrossEntropy=2.121, SmoothL1=0.893 [Epoch 192][Batch 299], Speed: 347.436 samples/sec, CrossEntropy=2.134, SmoothL1=0.899 [Epoch 192][Batch 399], Speed: 348.866 samples/sec, CrossEntropy=2.131, SmoothL1=0.904 [Epoch 192][Batch 499], Speed: 352.393 samples/sec, CrossEntropy=2.139, SmoothL1=0.911 [Epoch 192][Batch 599], Speed: 353.384 samples/sec, CrossEntropy=2.143, SmoothL1=0.914 [Epoch 192][Batch 699], Speed: 364.361 samples/sec, CrossEntropy=2.143, SmoothL1=0.915 [Epoch 192][Batch 799], Speed: 358.931 samples/sec, CrossEntropy=2.142, SmoothL1=0.911 [Epoch 192][Batch 899], Speed: 358.168 samples/sec, CrossEntropy=2.142, SmoothL1=0.913 [Epoch 192][Batch 999], Speed: 352.816 samples/sec, CrossEntropy=2.144, SmoothL1=0.912 [Epoch 192][Batch 1099], Speed: 360.693 samples/sec, CrossEntropy=2.146, SmoothL1=0.917 [Epoch 192][Batch 1199], Speed: 356.020 samples/sec, CrossEntropy=2.145, SmoothL1=0.915 [Epoch 192][Batch 1299], Speed: 355.429 samples/sec, CrossEntropy=2.144, SmoothL1=0.915 [Epoch 192][Batch 1399], Speed: 360.200 samples/sec, CrossEntropy=2.144, SmoothL1=0.918 [Epoch 192][Batch 1499], Speed: 351.315 samples/sec, CrossEntropy=2.148, SmoothL1=0.920 [Epoch 192][Batch 1599], Speed: 356.860 samples/sec, CrossEntropy=2.149, SmoothL1=0.922 [Epoch 192][Batch 1699], Speed: 359.126 samples/sec, CrossEntropy=2.149, SmoothL1=0.921 [Epoch 192][Batch 1799], Speed: 362.223 samples/sec, CrossEntropy=2.148, SmoothL1=0.920 [Epoch 192] Training cost: 335.027, CrossEntropy=2.149, SmoothL1=0.921 [Epoch 192] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.440 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.377 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.586 person=34.6 bicycle=16.7 car=20.5 motorcycle=28.0 airplane=45.5 bus=50.6 train=54.1 truck=21.9 boat=11.0 traffic light=7.9 fire hydrant=45.5 stop sign=47.7 parking meter=32.5 bench=13.3 bird=16.5 cat=53.7 dog=46.9 horse=42.3 sheep=33.7 cow=31.9 elephant=46.3 bear=54.7 zebra=48.0 giraffe=49.0 backpack=4.1 umbrella=22.2 handbag=3.4 tie=15.4 suitcase=18.3 frisbee=32.8 skis=11.3 snowboard=12.4 sports ball=17.4 kite=17.1 baseball bat=9.6 baseball glove=13.6 skateboard=27.4 surfboard=18.5 tennis racket=25.6 bottle=13.2 wine glass=12.7 cup=18.7 fork=15.3 knife=5.6 spoon=4.6 bowl=24.2 banana=14.4 apple=10.8 sandwich=27.2 orange=19.8 broccoli=13.1 carrot=10.7 hot dog=22.6 pizza=36.8 donut=27.1 cake=20.4 chair=13.1 couch=34.2 potted plant=13.5 bed=34.9 dining table=21.0 toilet=47.1 tv=41.7 laptop=43.5 mouse=31.9 remote=7.3 keyboard=34.0 cell phone=16.3 microwave=35.9 oven=27.5 toaster=7.1 sink=23.5 refrigerator=38.6 book=4.5 clock=30.1 vase=17.6 scissors=20.9 teddy bear=32.7 hair drier=8.9 toothbrush=7.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 193][Batch 99], Speed: 362.987 samples/sec, CrossEntropy=2.161, SmoothL1=0.924 [Epoch 193][Batch 199], Speed: 346.462 samples/sec, CrossEntropy=2.144, SmoothL1=0.912 [Epoch 193][Batch 299], Speed: 347.007 samples/sec, CrossEntropy=2.144, SmoothL1=0.915 [Epoch 193][Batch 399], Speed: 357.872 samples/sec, CrossEntropy=2.151, SmoothL1=0.922 [Epoch 193][Batch 499], Speed: 348.734 samples/sec, CrossEntropy=2.152, SmoothL1=0.921 [Epoch 193][Batch 599], Speed: 355.102 samples/sec, CrossEntropy=2.157, SmoothL1=0.926 [Epoch 193][Batch 699], Speed: 351.567 samples/sec, CrossEntropy=2.155, SmoothL1=0.924 [Epoch 193][Batch 799], Speed: 359.404 samples/sec, CrossEntropy=2.153, SmoothL1=0.924 [Epoch 193][Batch 899], Speed: 346.140 samples/sec, CrossEntropy=2.152, SmoothL1=0.922 [Epoch 193][Batch 999], Speed: 357.363 samples/sec, CrossEntropy=2.155, SmoothL1=0.925 [Epoch 193][Batch 1099], Speed: 353.964 samples/sec, CrossEntropy=2.154, SmoothL1=0.924 [Epoch 193][Batch 1199], Speed: 359.594 samples/sec, CrossEntropy=2.154, SmoothL1=0.925 [Epoch 193][Batch 1299], Speed: 359.219 samples/sec, CrossEntropy=2.152, SmoothL1=0.925 [Epoch 193][Batch 1399], Speed: 356.046 samples/sec, CrossEntropy=2.151, SmoothL1=0.924 [Epoch 193][Batch 1499], Speed: 351.124 samples/sec, CrossEntropy=2.149, SmoothL1=0.922 [Epoch 193][Batch 1599], Speed: 350.414 samples/sec, CrossEntropy=2.148, SmoothL1=0.921 [Epoch 193][Batch 1699], Speed: 358.590 samples/sec, CrossEntropy=2.149, SmoothL1=0.922 [Epoch 193][Batch 1799], Speed: 360.642 samples/sec, CrossEntropy=2.151, SmoothL1=0.923 [Epoch 193] Training cost: 335.217, CrossEntropy=2.151, SmoothL1=0.923 [Epoch 193] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.439 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.079 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.583 person=34.5 bicycle=17.4 car=20.5 motorcycle=27.9 airplane=45.8 bus=50.3 train=53.7 truck=21.5 boat=11.4 traffic light=8.2 fire hydrant=46.0 stop sign=48.0 parking meter=32.1 bench=13.6 bird=15.9 cat=52.6 dog=46.9 horse=42.6 sheep=32.7 cow=32.0 elephant=46.7 bear=58.1 zebra=48.2 giraffe=49.6 backpack=4.1 umbrella=22.4 handbag=3.5 tie=14.7 suitcase=18.8 frisbee=32.1 skis=11.3 snowboard=11.5 sports ball=17.5 kite=17.1 baseball bat=9.1 baseball glove=13.8 skateboard=27.1 surfboard=18.5 tennis racket=25.6 bottle=13.4 wine glass=13.1 cup=18.8 fork=16.0 knife=5.4 spoon=4.6 bowl=24.3 banana=14.4 apple=10.1 sandwich=28.5 orange=20.6 broccoli=13.2 carrot=10.7 hot dog=23.0 pizza=36.3 donut=27.1 cake=20.8 chair=13.0 couch=33.9 potted plant=13.2 bed=35.3 dining table=21.2 toilet=46.5 tv=42.0 laptop=44.7 mouse=32.4 remote=7.4 keyboard=32.9 cell phone=16.5 microwave=34.4 oven=27.5 toaster=8.6 sink=23.0 refrigerator=38.7 book=4.7 clock=29.8 vase=16.4 scissors=20.8 teddy bear=32.8 hair drier=4.5 toothbrush=6.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 194][Batch 99], Speed: 349.435 samples/sec, CrossEntropy=2.129, SmoothL1=0.905 [Epoch 194][Batch 199], Speed: 346.573 samples/sec, CrossEntropy=2.142, SmoothL1=0.925 [Epoch 194][Batch 299], Speed: 349.953 samples/sec, CrossEntropy=2.131, SmoothL1=0.917 [Epoch 194][Batch 399], Speed: 350.022 samples/sec, CrossEntropy=2.120, SmoothL1=0.909 [Epoch 194][Batch 499], Speed: 359.910 samples/sec, CrossEntropy=2.121, SmoothL1=0.908 [Epoch 194][Batch 599], Speed: 355.852 samples/sec, CrossEntropy=2.131, SmoothL1=0.910 [Epoch 194][Batch 699], Speed: 355.009 samples/sec, CrossEntropy=2.127, SmoothL1=0.906 [Epoch 194][Batch 799], Speed: 354.387 samples/sec, CrossEntropy=2.133, SmoothL1=0.909 [Epoch 194][Batch 899], Speed: 352.488 samples/sec, CrossEntropy=2.130, SmoothL1=0.907 [Epoch 194][Batch 999], Speed: 357.576 samples/sec, CrossEntropy=2.132, SmoothL1=0.908 [Epoch 194][Batch 1099], Speed: 340.809 samples/sec, CrossEntropy=2.133, SmoothL1=0.911 [Epoch 194][Batch 1199], Speed: 355.641 samples/sec, CrossEntropy=2.132, SmoothL1=0.908 [Epoch 194][Batch 1299], Speed: 350.131 samples/sec, CrossEntropy=2.131, SmoothL1=0.907 [Epoch 194][Batch 1399], Speed: 361.194 samples/sec, CrossEntropy=2.131, SmoothL1=0.909 [Epoch 194][Batch 1499], Speed: 360.637 samples/sec, CrossEntropy=2.132, SmoothL1=0.908 [Epoch 194][Batch 1599], Speed: 360.767 samples/sec, CrossEntropy=2.133, SmoothL1=0.908 [Epoch 194][Batch 1699], Speed: 362.919 samples/sec, CrossEntropy=2.135, SmoothL1=0.911 [Epoch 194][Batch 1799], Speed: 366.892 samples/sec, CrossEntropy=2.134, SmoothL1=0.910 [Epoch 194] Training cost: 334.522, CrossEntropy=2.135, SmoothL1=0.911 [Epoch 194] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.247 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.412 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.259 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.435 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.232 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.331 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.079 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.378 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.575 person=34.5 bicycle=16.8 car=20.5 motorcycle=27.4 airplane=45.5 bus=51.0 train=55.0 truck=21.8 boat=11.0 traffic light=8.2 fire hydrant=44.9 stop sign=46.7 parking meter=33.4 bench=13.6 bird=16.1 cat=53.8 dog=47.1 horse=41.7 sheep=33.3 cow=31.9 elephant=47.1 bear=56.5 zebra=48.2 giraffe=49.9 backpack=4.0 umbrella=22.3 handbag=3.4 tie=14.8 suitcase=18.9 frisbee=31.3 skis=11.3 snowboard=11.9 sports ball=17.8 kite=17.0 baseball bat=9.6 baseball glove=13.5 skateboard=27.3 surfboard=18.4 tennis racket=24.8 bottle=13.3 wine glass=13.3 cup=19.2 fork=15.7 knife=5.6 spoon=4.7 bowl=25.0 banana=14.7 apple=10.8 sandwich=28.5 orange=20.6 broccoli=13.5 carrot=10.0 hot dog=21.9 pizza=35.7 donut=26.8 cake=20.7 chair=13.1 couch=33.7 potted plant=13.8 bed=34.7 dining table=20.6 toilet=47.5 tv=41.9 laptop=44.3 mouse=32.5 remote=7.5 keyboard=33.0 cell phone=15.8 microwave=33.8 oven=28.4 toaster=3.6 sink=23.7 refrigerator=39.0 book=4.6 clock=30.1 vase=16.7 scissors=20.9 teddy bear=31.8 hair drier=0.0 toothbrush=6.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.7 [Epoch 195][Batch 99], Speed: 358.705 samples/sec, CrossEntropy=2.149, SmoothL1=0.930 [Epoch 195][Batch 199], Speed: 345.821 samples/sec, CrossEntropy=2.152, SmoothL1=0.924 [Epoch 195][Batch 299], Speed: 349.455 samples/sec, CrossEntropy=2.139, SmoothL1=0.915 [Epoch 195][Batch 399], Speed: 364.176 samples/sec, CrossEntropy=2.134, SmoothL1=0.909 [Epoch 195][Batch 499], Speed: 350.798 samples/sec, CrossEntropy=2.137, SmoothL1=0.916 [Epoch 195][Batch 599], Speed: 345.955 samples/sec, CrossEntropy=2.143, SmoothL1=0.916 [Epoch 195][Batch 699], Speed: 356.714 samples/sec, CrossEntropy=2.144, SmoothL1=0.916 [Epoch 195][Batch 799], Speed: 351.968 samples/sec, CrossEntropy=2.146, SmoothL1=0.918 [Epoch 195][Batch 899], Speed: 353.614 samples/sec, CrossEntropy=2.133, SmoothL1=0.910 [Epoch 195][Batch 999], Speed: 360.854 samples/sec, CrossEntropy=2.137, SmoothL1=0.912 [Epoch 195][Batch 1099], Speed: 350.257 samples/sec, CrossEntropy=2.132, SmoothL1=0.909 [Epoch 195][Batch 1199], Speed: 339.720 samples/sec, CrossEntropy=2.132, SmoothL1=0.908 [Epoch 195][Batch 1299], Speed: 351.463 samples/sec, CrossEntropy=2.132, SmoothL1=0.908 [Epoch 195][Batch 1399], Speed: 350.938 samples/sec, CrossEntropy=2.129, SmoothL1=0.906 [Epoch 195][Batch 1499], Speed: 358.158 samples/sec, CrossEntropy=2.131, SmoothL1=0.907 [Epoch 195][Batch 1599], Speed: 346.288 samples/sec, CrossEntropy=2.135, SmoothL1=0.911 [Epoch 195][Batch 1699], Speed: 350.165 samples/sec, CrossEntropy=2.137, SmoothL1=0.912 [Epoch 195][Batch 1799], Speed: 358.974 samples/sec, CrossEntropy=2.137, SmoothL1=0.911 [Epoch 195] Training cost: 334.794, CrossEntropy=2.135, SmoothL1=0.910 [Epoch 195] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.413 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.435 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.330 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.583 person=34.4 bicycle=16.8 car=20.3 motorcycle=28.2 airplane=44.7 bus=51.2 train=54.3 truck=22.4 boat=11.1 traffic light=8.3 fire hydrant=45.6 stop sign=46.1 parking meter=33.0 bench=13.5 bird=16.0 cat=53.6 dog=47.3 horse=41.6 sheep=33.1 cow=31.7 elephant=46.5 bear=58.2 zebra=48.2 giraffe=48.2 backpack=4.1 umbrella=22.5 handbag=3.3 tie=14.3 suitcase=18.4 frisbee=31.6 skis=11.0 snowboard=11.6 sports ball=17.6 kite=16.7 baseball bat=10.1 baseball glove=13.3 skateboard=27.1 surfboard=18.8 tennis racket=26.2 bottle=13.6 wine glass=13.0 cup=19.0 fork=16.2 knife=5.3 spoon=5.3 bowl=24.4 banana=15.0 apple=9.6 sandwich=28.4 orange=19.8 broccoli=13.5 carrot=10.1 hot dog=22.1 pizza=37.3 donut=27.2 cake=21.6 chair=13.2 couch=33.3 potted plant=13.2 bed=34.8 dining table=20.5 toilet=47.6 tv=42.5 laptop=43.8 mouse=32.5 remote=7.3 keyboard=33.1 cell phone=16.3 microwave=35.8 oven=28.1 toaster=7.1 sink=22.8 refrigerator=38.9 book=4.6 clock=30.7 vase=16.5 scissors=21.2 teddy bear=32.9 hair drier=0.0 toothbrush=6.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 196][Batch 99], Speed: 345.986 samples/sec, CrossEntropy=2.145, SmoothL1=0.919 [Epoch 196][Batch 199], Speed: 350.832 samples/sec, CrossEntropy=2.138, SmoothL1=0.919 [Epoch 196][Batch 299], Speed: 351.831 samples/sec, CrossEntropy=2.137, SmoothL1=0.911 [Epoch 196][Batch 399], Speed: 352.335 samples/sec, CrossEntropy=2.144, SmoothL1=0.908 [Epoch 196][Batch 499], Speed: 358.567 samples/sec, CrossEntropy=2.152, SmoothL1=0.909 [Epoch 196][Batch 599], Speed: 355.749 samples/sec, CrossEntropy=2.150, SmoothL1=0.911 [Epoch 196][Batch 699], Speed: 350.536 samples/sec, CrossEntropy=2.150, SmoothL1=0.911 [Epoch 196][Batch 799], Speed: 355.623 samples/sec, CrossEntropy=2.145, SmoothL1=0.908 [Epoch 196][Batch 899], Speed: 354.979 samples/sec, CrossEntropy=2.148, SmoothL1=0.909 [Epoch 196][Batch 999], Speed: 351.322 samples/sec, CrossEntropy=2.151, SmoothL1=0.911 [Epoch 196][Batch 1099], Speed: 357.172 samples/sec, CrossEntropy=2.147, SmoothL1=0.909 [Epoch 196][Batch 1199], Speed: 350.455 samples/sec, CrossEntropy=2.146, SmoothL1=0.909 [Epoch 196][Batch 1299], Speed: 348.232 samples/sec, CrossEntropy=2.145, SmoothL1=0.910 [Epoch 196][Batch 1399], Speed: 351.252 samples/sec, CrossEntropy=2.145, SmoothL1=0.910 [Epoch 196][Batch 1499], Speed: 351.492 samples/sec, CrossEntropy=2.143, SmoothL1=0.908 [Epoch 196][Batch 1599], Speed: 352.861 samples/sec, CrossEntropy=2.141, SmoothL1=0.907 [Epoch 196][Batch 1699], Speed: 352.025 samples/sec, CrossEntropy=2.141, SmoothL1=0.907 [Epoch 196][Batch 1799], Speed: 359.399 samples/sec, CrossEntropy=2.141, SmoothL1=0.908 [Epoch 196] Training cost: 335.381, CrossEntropy=2.143, SmoothL1=0.909 [Epoch 196] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.260 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.436 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.331 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.079 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.582 person=34.6 bicycle=16.9 car=20.4 motorcycle=27.5 airplane=44.9 bus=49.4 train=53.8 truck=22.1 boat=11.4 traffic light=8.1 fire hydrant=45.6 stop sign=47.4 parking meter=33.1 bench=13.5 bird=16.2 cat=55.0 dog=47.1 horse=41.3 sheep=33.3 cow=32.4 elephant=46.8 bear=57.1 zebra=47.8 giraffe=49.2 backpack=4.1 umbrella=22.4 handbag=3.5 tie=14.4 suitcase=18.4 frisbee=31.6 skis=11.2 snowboard=11.1 sports ball=16.9 kite=17.1 baseball bat=10.1 baseball glove=13.2 skateboard=27.2 surfboard=18.7 tennis racket=26.0 bottle=13.2 wine glass=13.1 cup=18.9 fork=16.0 knife=5.7 spoon=4.9 bowl=24.8 banana=14.4 apple=9.8 sandwich=28.5 orange=20.4 broccoli=13.5 carrot=10.7 hot dog=22.8 pizza=36.6 donut=27.2 cake=21.0 chair=13.4 couch=33.8 potted plant=13.6 bed=35.3 dining table=21.2 toilet=48.1 tv=42.2 laptop=43.9 mouse=32.3 remote=7.5 keyboard=33.8 cell phone=16.6 microwave=34.8 oven=28.2 toaster=7.4 sink=23.2 refrigerator=38.2 book=4.7 clock=30.5 vase=16.8 scissors=19.7 teddy bear=33.2 hair drier=0.0 toothbrush=6.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 197][Batch 99], Speed: 355.106 samples/sec, CrossEntropy=2.140, SmoothL1=0.905 [Epoch 197][Batch 199], Speed: 341.641 samples/sec, CrossEntropy=2.135, SmoothL1=0.903 [Epoch 197][Batch 299], Speed: 359.539 samples/sec, CrossEntropy=2.121, SmoothL1=0.902 [Epoch 197][Batch 399], Speed: 358.632 samples/sec, CrossEntropy=2.130, SmoothL1=0.907 [Epoch 197][Batch 499], Speed: 366.191 samples/sec, CrossEntropy=2.129, SmoothL1=0.906 [Epoch 197][Batch 599], Speed: 355.247 samples/sec, CrossEntropy=2.127, SmoothL1=0.908 [Epoch 197][Batch 699], Speed: 356.801 samples/sec, CrossEntropy=2.130, SmoothL1=0.912 [Epoch 197][Batch 799], Speed: 339.015 samples/sec, CrossEntropy=2.136, SmoothL1=0.916 [Epoch 197][Batch 899], Speed: 355.743 samples/sec, CrossEntropy=2.135, SmoothL1=0.914 [Epoch 197][Batch 999], Speed: 347.669 samples/sec, CrossEntropy=2.135, SmoothL1=0.913 [Epoch 197][Batch 1099], Speed: 354.366 samples/sec, CrossEntropy=2.130, SmoothL1=0.910 [Epoch 197][Batch 1199], Speed: 351.038 samples/sec, CrossEntropy=2.131, SmoothL1=0.910 [Epoch 197][Batch 1299], Speed: 344.375 samples/sec, CrossEntropy=2.132, SmoothL1=0.909 [Epoch 197][Batch 1399], Speed: 348.172 samples/sec, CrossEntropy=2.131, SmoothL1=0.908 [Epoch 197][Batch 1499], Speed: 356.467 samples/sec, CrossEntropy=2.130, SmoothL1=0.908 [Epoch 197][Batch 1599], Speed: 355.384 samples/sec, CrossEntropy=2.132, SmoothL1=0.909 [Epoch 197][Batch 1699], Speed: 351.843 samples/sec, CrossEntropy=2.132, SmoothL1=0.910 [Epoch 197][Batch 1799], Speed: 346.550 samples/sec, CrossEntropy=2.133, SmoothL1=0.912 [Epoch 197] Training cost: 335.911, CrossEntropy=2.131, SmoothL1=0.911 [Epoch 197] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.447 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.588 person=34.5 bicycle=17.5 car=20.3 motorcycle=27.4 airplane=44.5 bus=50.6 train=54.0 truck=21.9 boat=11.6 traffic light=8.2 fire hydrant=45.2 stop sign=46.8 parking meter=32.7 bench=13.6 bird=16.5 cat=54.5 dog=47.6 horse=41.7 sheep=33.9 cow=31.8 elephant=46.6 bear=55.9 zebra=49.3 giraffe=49.8 backpack=3.9 umbrella=22.7 handbag=3.7 tie=14.7 suitcase=18.4 frisbee=32.8 skis=11.5 snowboard=11.8 sports ball=17.7 kite=17.3 baseball bat=9.8 baseball glove=13.3 skateboard=28.4 surfboard=18.8 tennis racket=25.7 bottle=13.4 wine glass=13.3 cup=18.7 fork=15.7 knife=5.4 spoon=4.8 bowl=24.4 banana=14.3 apple=10.9 sandwich=28.5 orange=20.6 broccoli=13.4 carrot=10.3 hot dog=22.8 pizza=37.2 donut=27.7 cake=20.7 chair=13.2 couch=33.4 potted plant=13.4 bed=34.6 dining table=19.6 toilet=47.0 tv=42.0 laptop=44.5 mouse=32.6 remote=7.4 keyboard=33.6 cell phone=16.0 microwave=34.3 oven=27.3 toaster=9.2 sink=22.7 refrigerator=38.6 book=4.9 clock=30.0 vase=17.0 scissors=19.4 teddy bear=32.3 hair drier=0.0 toothbrush=7.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 198][Batch 99], Speed: 365.010 samples/sec, CrossEntropy=2.126, SmoothL1=0.936 [Epoch 198][Batch 199], Speed: 356.106 samples/sec, CrossEntropy=2.131, SmoothL1=0.924 [Epoch 198][Batch 299], Speed: 356.189 samples/sec, CrossEntropy=2.137, SmoothL1=0.920 [Epoch 198][Batch 399], Speed: 353.042 samples/sec, CrossEntropy=2.134, SmoothL1=0.915 [Epoch 198][Batch 499], Speed: 347.770 samples/sec, CrossEntropy=2.142, SmoothL1=0.920 [Epoch 198][Batch 599], Speed: 354.367 samples/sec, CrossEntropy=2.149, SmoothL1=0.920 [Epoch 198][Batch 699], Speed: 351.257 samples/sec, CrossEntropy=2.141, SmoothL1=0.916 [Epoch 198][Batch 799], Speed: 362.071 samples/sec, CrossEntropy=2.145, SmoothL1=0.915 [Epoch 198][Batch 899], Speed: 345.412 samples/sec, CrossEntropy=2.143, SmoothL1=0.914 [Epoch 198][Batch 999], Speed: 351.207 samples/sec, CrossEntropy=2.145, SmoothL1=0.917 [Epoch 198][Batch 1099], Speed: 361.810 samples/sec, CrossEntropy=2.145, SmoothL1=0.915 [Epoch 198][Batch 1199], Speed: 363.756 samples/sec, CrossEntropy=2.141, SmoothL1=0.914 [Epoch 198][Batch 1299], Speed: 350.121 samples/sec, CrossEntropy=2.140, SmoothL1=0.913 [Epoch 198][Batch 1399], Speed: 356.389 samples/sec, CrossEntropy=2.139, SmoothL1=0.914 [Epoch 198][Batch 1499], Speed: 351.865 samples/sec, CrossEntropy=2.136, SmoothL1=0.913 [Epoch 198][Batch 1599], Speed: 345.097 samples/sec, CrossEntropy=2.135, SmoothL1=0.911 [Epoch 198][Batch 1699], Speed: 347.473 samples/sec, CrossEntropy=2.137, SmoothL1=0.912 [Epoch 198][Batch 1799], Speed: 351.476 samples/sec, CrossEntropy=2.136, SmoothL1=0.911 [Epoch 198] Training cost: 335.068, CrossEntropy=2.133, SmoothL1=0.910 [Epoch 198] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.447 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.078 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.587 person=34.5 bicycle=16.9 car=20.3 motorcycle=27.7 airplane=46.0 bus=50.6 train=52.5 truck=22.2 boat=11.5 traffic light=8.1 fire hydrant=44.7 stop sign=47.6 parking meter=32.7 bench=13.5 bird=15.9 cat=54.0 dog=46.8 horse=42.2 sheep=33.0 cow=31.9 elephant=46.2 bear=56.3 zebra=49.1 giraffe=49.8 backpack=3.9 umbrella=22.4 handbag=3.5 tie=14.8 suitcase=18.7 frisbee=32.3 skis=11.9 snowboard=11.5 sports ball=18.2 kite=17.4 baseball bat=10.0 baseball glove=14.0 skateboard=28.1 surfboard=18.4 tennis racket=26.1 bottle=13.1 wine glass=13.3 cup=19.0 fork=16.2 knife=5.7 spoon=4.9 bowl=25.2 banana=14.2 apple=10.6 sandwich=28.4 orange=20.3 broccoli=13.5 carrot=10.1 hot dog=22.4 pizza=37.1 donut=27.7 cake=20.6 chair=13.4 couch=34.1 potted plant=13.5 bed=34.2 dining table=21.1 toilet=46.6 tv=42.4 laptop=44.2 mouse=32.3 remote=6.9 keyboard=34.1 cell phone=16.5 microwave=35.4 oven=27.9 toaster=9.7 sink=22.8 refrigerator=37.5 book=4.7 clock=30.1 vase=17.0 scissors=20.8 teddy bear=31.9 hair drier=4.0 toothbrush=6.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 199][Batch 99], Speed: 351.380 samples/sec, CrossEntropy=2.175, SmoothL1=0.940 [Epoch 199][Batch 199], Speed: 363.332 samples/sec, CrossEntropy=2.144, SmoothL1=0.920 [Epoch 199][Batch 299], Speed: 361.721 samples/sec, CrossEntropy=2.129, SmoothL1=0.915 [Epoch 199][Batch 399], Speed: 350.021 samples/sec, CrossEntropy=2.131, SmoothL1=0.916 [Epoch 199][Batch 499], Speed: 353.092 samples/sec, CrossEntropy=2.131, SmoothL1=0.920 [Epoch 199][Batch 599], Speed: 360.131 samples/sec, CrossEntropy=2.140, SmoothL1=0.922 [Epoch 199][Batch 699], Speed: 355.457 samples/sec, CrossEntropy=2.143, SmoothL1=0.923 [Epoch 199][Batch 799], Speed: 347.630 samples/sec, CrossEntropy=2.143, SmoothL1=0.920 [Epoch 199][Batch 899], Speed: 351.457 samples/sec, CrossEntropy=2.148, SmoothL1=0.922 [Epoch 199][Batch 999], Speed: 363.251 samples/sec, CrossEntropy=2.147, SmoothL1=0.921 [Epoch 199][Batch 1099], Speed: 336.497 samples/sec, CrossEntropy=2.144, SmoothL1=0.921 [Epoch 199][Batch 1199], Speed: 359.720 samples/sec, CrossEntropy=2.141, SmoothL1=0.920 [Epoch 199][Batch 1299], Speed: 349.443 samples/sec, CrossEntropy=2.141, SmoothL1=0.920 [Epoch 199][Batch 1399], Speed: 344.620 samples/sec, CrossEntropy=2.141, SmoothL1=0.919 [Epoch 199][Batch 1499], Speed: 361.020 samples/sec, CrossEntropy=2.141, SmoothL1=0.918 [Epoch 199][Batch 1599], Speed: 343.956 samples/sec, CrossEntropy=2.141, SmoothL1=0.921 [Epoch 199][Batch 1699], Speed: 364.501 samples/sec, CrossEntropy=2.139, SmoothL1=0.920 [Epoch 199][Batch 1799], Speed: 356.926 samples/sec, CrossEntropy=2.141, SmoothL1=0.919 [Epoch 200] Set learning rate to 1e-05 [Epoch 200] Set learning rate to 1e-05 [Epoch 200] Set learning rate to 1e-05 [Epoch 199] Training cost: 335.518, CrossEntropy=2.141, SmoothL1=0.918 [Epoch 199] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.260 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.049 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.435 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.331 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.573 person=34.4 bicycle=17.1 car=20.6 motorcycle=27.7 airplane=45.6 bus=50.9 train=53.6 truck=21.3 boat=10.9 traffic light=8.4 fire hydrant=46.5 stop sign=46.5 parking meter=32.9 bench=13.4 bird=16.1 cat=54.5 dog=46.9 horse=42.6 sheep=33.4 cow=32.2 elephant=46.0 bear=56.9 zebra=48.0 giraffe=49.2 backpack=4.0 umbrella=22.9 handbag=3.5 tie=14.7 suitcase=18.3 frisbee=32.1 skis=11.2 snowboard=11.2 sports ball=18.3 kite=17.3 baseball bat=9.7 baseball glove=14.0 skateboard=27.0 surfboard=17.8 tennis racket=25.4 bottle=13.2 wine glass=12.8 cup=18.8 fork=15.2 knife=5.6 spoon=4.8 bowl=24.5 banana=14.3 apple=10.6 sandwich=28.5 orange=19.9 broccoli=13.4 carrot=10.1 hot dog=22.8 pizza=37.1 donut=27.8 cake=20.9 chair=13.3 couch=33.5 potted plant=13.3 bed=34.9 dining table=20.9 toilet=46.1 tv=42.3 laptop=43.4 mouse=32.3 remote=7.5 keyboard=33.7 cell phone=16.7 microwave=36.0 oven=28.1 toaster=7.3 sink=22.7 refrigerator=37.3 book=4.6 clock=30.3 vase=16.6 scissors=20.7 teddy bear=32.7 hair drier=0.0 toothbrush=8.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.8 [Epoch 200] Set learning rate to 1e-05 [Epoch 200][Batch 99], Speed: 360.362 samples/sec, CrossEntropy=2.128, SmoothL1=0.896 [Epoch 200][Batch 199], Speed: 349.974 samples/sec, CrossEntropy=2.139, SmoothL1=0.911 [Epoch 200][Batch 299], Speed: 346.242 samples/sec, CrossEntropy=2.133, SmoothL1=0.913 [Epoch 200][Batch 399], Speed: 348.268 samples/sec, CrossEntropy=2.135, SmoothL1=0.916 [Epoch 200][Batch 499], Speed: 355.807 samples/sec, CrossEntropy=2.138, SmoothL1=0.921 [Epoch 200][Batch 599], Speed: 363.070 samples/sec, CrossEntropy=2.131, SmoothL1=0.916 [Epoch 200][Batch 699], Speed: 356.035 samples/sec, CrossEntropy=2.130, SmoothL1=0.915 [Epoch 200][Batch 799], Speed: 349.590 samples/sec, CrossEntropy=2.135, SmoothL1=0.918 [Epoch 200][Batch 899], Speed: 359.777 samples/sec, CrossEntropy=2.133, SmoothL1=0.915 [Epoch 200][Batch 999], Speed: 350.777 samples/sec, CrossEntropy=2.131, SmoothL1=0.913 [Epoch 200][Batch 1099], Speed: 354.628 samples/sec, CrossEntropy=2.131, SmoothL1=0.917 [Epoch 200][Batch 1199], Speed: 362.019 samples/sec, CrossEntropy=2.130, SmoothL1=0.916 [Epoch 200][Batch 1299], Speed: 357.588 samples/sec, CrossEntropy=2.131, SmoothL1=0.916 [Epoch 200][Batch 1399], Speed: 347.726 samples/sec, CrossEntropy=2.128, SmoothL1=0.914 [Epoch 200][Batch 1499], Speed: 355.453 samples/sec, CrossEntropy=2.127, SmoothL1=0.913 [Epoch 200][Batch 1599], Speed: 359.270 samples/sec, CrossEntropy=2.128, SmoothL1=0.912 [Epoch 200][Batch 1699], Speed: 348.979 samples/sec, CrossEntropy=2.127, SmoothL1=0.912 [Epoch 200][Batch 1799], Speed: 351.666 samples/sec, CrossEntropy=2.127, SmoothL1=0.912 [Epoch 200] Training cost: 335.118, CrossEntropy=2.127, SmoothL1=0.912 [Epoch 200] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.416 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.438 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.579 person=34.5 bicycle=17.5 car=20.6 motorcycle=27.4 airplane=46.1 bus=50.5 train=53.7 truck=21.8 boat=11.1 traffic light=8.5 fire hydrant=45.8 stop sign=47.6 parking meter=33.0 bench=13.2 bird=15.7 cat=54.9 dog=46.4 horse=42.3 sheep=32.9 cow=31.9 elephant=46.3 bear=56.4 zebra=48.5 giraffe=49.3 backpack=4.2 umbrella=22.8 handbag=3.6 tie=14.8 suitcase=18.0 frisbee=31.7 skis=11.0 snowboard=10.8 sports ball=17.9 kite=17.2 baseball bat=9.9 baseball glove=14.0 skateboard=27.3 surfboard=18.2 tennis racket=25.4 bottle=13.3 wine glass=12.9 cup=18.9 fork=15.5 knife=5.6 spoon=4.6 bowl=24.8 banana=14.7 apple=9.9 sandwich=28.7 orange=20.3 broccoli=13.2 carrot=10.4 hot dog=22.9 pizza=37.0 donut=27.7 cake=21.0 chair=13.3 couch=34.1 potted plant=13.6 bed=34.8 dining table=21.0 toilet=46.7 tv=42.7 laptop=43.7 mouse=32.9 remote=7.5 keyboard=33.8 cell phone=16.4 microwave=36.4 oven=28.3 toaster=7.3 sink=23.6 refrigerator=38.2 book=4.7 clock=30.4 vase=16.7 scissors=19.7 teddy bear=32.3 hair drier=8.9 toothbrush=7.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 201][Batch 99], Speed: 338.380 samples/sec, CrossEntropy=2.129, SmoothL1=0.912 [Epoch 201][Batch 199], Speed: 351.759 samples/sec, CrossEntropy=2.134, SmoothL1=0.917 [Epoch 201][Batch 299], Speed: 363.625 samples/sec, CrossEntropy=2.123, SmoothL1=0.909 [Epoch 201][Batch 399], Speed: 357.566 samples/sec, CrossEntropy=2.124, SmoothL1=0.909 [Epoch 201][Batch 499], Speed: 347.923 samples/sec, CrossEntropy=2.121, SmoothL1=0.901 [Epoch 201][Batch 599], Speed: 352.366 samples/sec, CrossEntropy=2.115, SmoothL1=0.900 [Epoch 201][Batch 699], Speed: 365.159 samples/sec, CrossEntropy=2.116, SmoothL1=0.900 [Epoch 201][Batch 799], Speed: 349.399 samples/sec, CrossEntropy=2.115, SmoothL1=0.900 [Epoch 201][Batch 899], Speed: 354.479 samples/sec, CrossEntropy=2.121, SmoothL1=0.904 [Epoch 201][Batch 999], Speed: 341.226 samples/sec, CrossEntropy=2.120, SmoothL1=0.902 [Epoch 201][Batch 1099], Speed: 359.694 samples/sec, CrossEntropy=2.121, SmoothL1=0.904 [Epoch 201][Batch 1199], Speed: 345.649 samples/sec, CrossEntropy=2.118, SmoothL1=0.904 [Epoch 201][Batch 1299], Speed: 351.452 samples/sec, CrossEntropy=2.117, SmoothL1=0.903 [Epoch 201][Batch 1399], Speed: 339.509 samples/sec, CrossEntropy=2.117, SmoothL1=0.904 [Epoch 201][Batch 1499], Speed: 353.589 samples/sec, CrossEntropy=2.117, SmoothL1=0.903 [Epoch 201][Batch 1599], Speed: 341.596 samples/sec, CrossEntropy=2.118, SmoothL1=0.905 [Epoch 201][Batch 1699], Speed: 361.204 samples/sec, CrossEntropy=2.119, SmoothL1=0.905 [Epoch 201][Batch 1799], Speed: 359.005 samples/sec, CrossEntropy=2.121, SmoothL1=0.906 [Epoch 201] Training cost: 334.934, CrossEntropy=2.120, SmoothL1=0.906 [Epoch 201] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.448 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.334 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.347 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.585 person=34.5 bicycle=17.5 car=20.7 motorcycle=27.3 airplane=45.5 bus=50.5 train=54.2 truck=21.8 boat=11.2 traffic light=8.5 fire hydrant=46.2 stop sign=47.5 parking meter=33.6 bench=13.2 bird=15.9 cat=54.8 dog=46.6 horse=42.1 sheep=33.5 cow=32.1 elephant=46.5 bear=56.7 zebra=49.1 giraffe=49.8 backpack=4.1 umbrella=22.9 handbag=3.6 tie=14.8 suitcase=17.9 frisbee=32.1 skis=11.5 snowboard=11.1 sports ball=18.4 kite=17.7 baseball bat=9.8 baseball glove=14.2 skateboard=27.4 surfboard=18.3 tennis racket=25.6 bottle=13.6 wine glass=13.0 cup=18.9 fork=15.8 knife=5.4 spoon=4.9 bowl=25.1 banana=14.7 apple=10.2 sandwich=28.9 orange=20.4 broccoli=13.1 carrot=10.0 hot dog=23.3 pizza=37.6 donut=27.8 cake=20.3 chair=13.2 couch=34.0 potted plant=13.3 bed=35.0 dining table=20.9 toilet=47.3 tv=42.3 laptop=44.2 mouse=33.2 remote=7.6 keyboard=33.4 cell phone=16.6 microwave=35.1 oven=28.0 toaster=8.6 sink=23.4 refrigerator=37.9 book=4.8 clock=30.3 vase=16.8 scissors=20.1 teddy bear=31.9 hair drier=5.0 toothbrush=8.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 202][Batch 99], Speed: 352.274 samples/sec, CrossEntropy=2.099, SmoothL1=0.879 [Epoch 202][Batch 199], Speed: 351.561 samples/sec, CrossEntropy=2.103, SmoothL1=0.895 [Epoch 202][Batch 299], Speed: 350.251 samples/sec, CrossEntropy=2.115, SmoothL1=0.904 [Epoch 202][Batch 399], Speed: 350.535 samples/sec, CrossEntropy=2.120, SmoothL1=0.904 [Epoch 202][Batch 499], Speed: 345.759 samples/sec, CrossEntropy=2.118, SmoothL1=0.909 [Epoch 202][Batch 599], Speed: 343.722 samples/sec, CrossEntropy=2.119, SmoothL1=0.910 [Epoch 202][Batch 699], Speed: 356.222 samples/sec, CrossEntropy=2.120, SmoothL1=0.909 [Epoch 202][Batch 799], Speed: 352.477 samples/sec, CrossEntropy=2.120, SmoothL1=0.910 [Epoch 202][Batch 899], Speed: 349.524 samples/sec, CrossEntropy=2.116, SmoothL1=0.906 [Epoch 202][Batch 999], Speed: 354.366 samples/sec, CrossEntropy=2.117, SmoothL1=0.908 [Epoch 202][Batch 1099], Speed: 348.309 samples/sec, CrossEntropy=2.117, SmoothL1=0.907 [Epoch 202][Batch 1199], Speed: 346.075 samples/sec, CrossEntropy=2.121, SmoothL1=0.910 [Epoch 202][Batch 1299], Speed: 352.726 samples/sec, CrossEntropy=2.122, SmoothL1=0.911 [Epoch 202][Batch 1399], Speed: 358.522 samples/sec, CrossEntropy=2.122, SmoothL1=0.912 [Epoch 202][Batch 1499], Speed: 362.506 samples/sec, CrossEntropy=2.120, SmoothL1=0.913 [Epoch 202][Batch 1599], Speed: 358.826 samples/sec, CrossEntropy=2.119, SmoothL1=0.913 [Epoch 202][Batch 1699], Speed: 347.073 samples/sec, CrossEntropy=2.121, SmoothL1=0.915 [Epoch 202][Batch 1799], Speed: 360.887 samples/sec, CrossEntropy=2.122, SmoothL1=0.914 [Epoch 202] Training cost: 334.650, CrossEntropy=2.120, SmoothL1=0.913 [Epoch 202] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.251 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.268 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.444 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.336 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.349 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.384 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.591 person=34.6 bicycle=17.0 car=20.7 motorcycle=27.7 airplane=45.1 bus=50.5 train=54.8 truck=22.0 boat=11.5 traffic light=8.4 fire hydrant=46.4 stop sign=47.1 parking meter=33.5 bench=13.7 bird=16.1 cat=54.8 dog=47.7 horse=41.7 sheep=33.2 cow=32.0 elephant=46.4 bear=57.7 zebra=49.0 giraffe=49.7 backpack=4.1 umbrella=22.8 handbag=3.7 tie=15.0 suitcase=18.2 frisbee=32.0 skis=11.4 snowboard=11.4 sports ball=18.2 kite=17.6 baseball bat=9.6 baseball glove=14.1 skateboard=27.7 surfboard=18.4 tennis racket=25.9 bottle=13.4 wine glass=13.0 cup=19.0 fork=15.4 knife=5.5 spoon=4.7 bowl=25.1 banana=14.6 apple=10.2 sandwich=29.0 orange=19.8 broccoli=13.2 carrot=10.1 hot dog=23.6 pizza=37.0 donut=27.7 cake=20.4 chair=13.2 couch=34.1 potted plant=13.3 bed=34.1 dining table=20.7 toilet=47.5 tv=42.3 laptop=44.4 mouse=32.9 remote=7.5 keyboard=33.9 cell phone=16.6 microwave=36.1 oven=27.9 toaster=9.1 sink=23.7 refrigerator=38.4 book=4.8 clock=30.2 vase=16.7 scissors=19.9 teddy bear=32.1 hair drier=5.0 toothbrush=7.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.1 [Epoch 203][Batch 99], Speed: 361.095 samples/sec, CrossEntropy=2.127, SmoothL1=0.934 [Epoch 203][Batch 199], Speed: 364.204 samples/sec, CrossEntropy=2.139, SmoothL1=0.927 [Epoch 203][Batch 299], Speed: 349.960 samples/sec, CrossEntropy=2.131, SmoothL1=0.916 [Epoch 203][Batch 399], Speed: 354.394 samples/sec, CrossEntropy=2.133, SmoothL1=0.913 [Epoch 203][Batch 499], Speed: 362.612 samples/sec, CrossEntropy=2.131, SmoothL1=0.907 [Epoch 203][Batch 599], Speed: 362.673 samples/sec, CrossEntropy=2.128, SmoothL1=0.907 [Epoch 203][Batch 699], Speed: 353.686 samples/sec, CrossEntropy=2.127, SmoothL1=0.907 [Epoch 203][Batch 799], Speed: 360.947 samples/sec, CrossEntropy=2.122, SmoothL1=0.904 [Epoch 203][Batch 899], Speed: 358.737 samples/sec, CrossEntropy=2.119, SmoothL1=0.904 [Epoch 203][Batch 999], Speed: 348.989 samples/sec, CrossEntropy=2.117, SmoothL1=0.903 [Epoch 203][Batch 1099], Speed: 341.015 samples/sec, CrossEntropy=2.116, SmoothL1=0.904 [Epoch 203][Batch 1199], Speed: 357.731 samples/sec, CrossEntropy=2.119, SmoothL1=0.905 [Epoch 203][Batch 1299], Speed: 345.497 samples/sec, CrossEntropy=2.119, SmoothL1=0.905 [Epoch 203][Batch 1399], Speed: 362.824 samples/sec, CrossEntropy=2.119, SmoothL1=0.907 [Epoch 203][Batch 1499], Speed: 352.076 samples/sec, CrossEntropy=2.117, SmoothL1=0.905 [Epoch 203][Batch 1599], Speed: 361.670 samples/sec, CrossEntropy=2.115, SmoothL1=0.904 [Epoch 203][Batch 1699], Speed: 354.869 samples/sec, CrossEntropy=2.118, SmoothL1=0.905 [Epoch 203][Batch 1799], Speed: 344.497 samples/sec, CrossEntropy=2.117, SmoothL1=0.905 [Epoch 203] Training cost: 334.585, CrossEntropy=2.117, SmoothL1=0.906 [Epoch 203] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.444 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.236 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.335 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.348 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.383 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.585 person=34.6 bicycle=17.3 car=20.6 motorcycle=27.4 airplane=45.3 bus=50.5 train=53.8 truck=21.9 boat=11.3 traffic light=8.5 fire hydrant=46.2 stop sign=47.5 parking meter=34.1 bench=13.3 bird=15.8 cat=55.0 dog=47.2 horse=42.5 sheep=33.4 cow=31.8 elephant=46.3 bear=57.1 zebra=48.9 giraffe=49.5 backpack=4.0 umbrella=22.8 handbag=3.7 tie=14.7 suitcase=18.1 frisbee=32.2 skis=11.4 snowboard=11.1 sports ball=18.2 kite=17.5 baseball bat=10.0 baseball glove=14.2 skateboard=27.4 surfboard=18.2 tennis racket=26.1 bottle=13.5 wine glass=13.0 cup=18.8 fork=15.8 knife=5.6 spoon=4.9 bowl=25.1 banana=14.8 apple=10.3 sandwich=28.9 orange=20.6 broccoli=13.2 carrot=10.5 hot dog=23.5 pizza=36.9 donut=27.5 cake=20.8 chair=13.2 couch=34.0 potted plant=13.2 bed=34.7 dining table=20.8 toilet=47.4 tv=42.3 laptop=44.4 mouse=33.3 remote=7.5 keyboard=33.5 cell phone=16.4 microwave=35.5 oven=27.9 toaster=8.6 sink=23.3 refrigerator=37.6 book=4.8 clock=29.9 vase=16.7 scissors=20.1 teddy bear=32.4 hair drier=5.0 toothbrush=7.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 204][Batch 99], Speed: 347.010 samples/sec, CrossEntropy=2.098, SmoothL1=0.873 [Epoch 204][Batch 199], Speed: 351.882 samples/sec, CrossEntropy=2.107, SmoothL1=0.896 [Epoch 204][Batch 299], Speed: 355.104 samples/sec, CrossEntropy=2.105, SmoothL1=0.894 [Epoch 204][Batch 399], Speed: 358.841 samples/sec, CrossEntropy=2.113, SmoothL1=0.905 [Epoch 204][Batch 499], Speed: 354.313 samples/sec, CrossEntropy=2.112, SmoothL1=0.903 [Epoch 204][Batch 599], Speed: 362.954 samples/sec, CrossEntropy=2.110, SmoothL1=0.904 [Epoch 204][Batch 699], Speed: 347.726 samples/sec, CrossEntropy=2.111, SmoothL1=0.904 [Epoch 204][Batch 799], Speed: 355.562 samples/sec, CrossEntropy=2.111, SmoothL1=0.903 [Epoch 204][Batch 899], Speed: 348.639 samples/sec, CrossEntropy=2.113, SmoothL1=0.905 [Epoch 204][Batch 999], Speed: 356.778 samples/sec, CrossEntropy=2.111, SmoothL1=0.905 [Epoch 204][Batch 1099], Speed: 348.565 samples/sec, CrossEntropy=2.112, SmoothL1=0.904 [Epoch 204][Batch 1199], Speed: 350.430 samples/sec, CrossEntropy=2.113, SmoothL1=0.903 [Epoch 204][Batch 1299], Speed: 349.450 samples/sec, CrossEntropy=2.111, SmoothL1=0.902 [Epoch 204][Batch 1399], Speed: 346.784 samples/sec, CrossEntropy=2.113, SmoothL1=0.902 [Epoch 204][Batch 1499], Speed: 357.359 samples/sec, CrossEntropy=2.112, SmoothL1=0.902 [Epoch 204][Batch 1599], Speed: 347.688 samples/sec, CrossEntropy=2.110, SmoothL1=0.900 [Epoch 204][Batch 1699], Speed: 350.525 samples/sec, CrossEntropy=2.109, SmoothL1=0.900 [Epoch 204][Batch 1799], Speed: 349.630 samples/sec, CrossEntropy=2.110, SmoothL1=0.901 [Epoch 204] Training cost: 334.991, CrossEntropy=2.111, SmoothL1=0.902 [Epoch 204] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.416 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.438 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.382 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.575 person=34.6 bicycle=17.3 car=20.6 motorcycle=27.6 airplane=45.6 bus=50.5 train=54.7 truck=22.1 boat=11.4 traffic light=8.6 fire hydrant=46.6 stop sign=47.3 parking meter=33.9 bench=13.4 bird=16.1 cat=54.3 dog=47.2 horse=42.4 sheep=33.4 cow=31.9 elephant=46.6 bear=57.4 zebra=49.0 giraffe=50.2 backpack=4.0 umbrella=22.7 handbag=3.7 tie=15.3 suitcase=17.7 frisbee=32.3 skis=11.6 snowboard=11.7 sports ball=18.1 kite=17.9 baseball bat=10.0 baseball glove=14.0 skateboard=27.4 surfboard=18.5 tennis racket=26.2 bottle=13.5 wine glass=13.2 cup=19.0 fork=15.7 knife=5.6 spoon=5.0 bowl=25.0 banana=14.6 apple=9.7 sandwich=29.0 orange=20.0 broccoli=13.1 carrot=10.2 hot dog=23.3 pizza=37.5 donut=27.5 cake=20.5 chair=13.3 couch=34.3 potted plant=13.1 bed=35.7 dining table=20.9 toilet=47.5 tv=42.4 laptop=44.3 mouse=33.2 remote=7.6 keyboard=33.1 cell phone=16.5 microwave=35.1 oven=27.8 toaster=7.6 sink=23.1 refrigerator=38.3 book=4.9 clock=30.4 vase=16.9 scissors=20.6 teddy bear=31.8 hair drier=0.0 toothbrush=7.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 205][Batch 99], Speed: 345.952 samples/sec, CrossEntropy=2.132, SmoothL1=0.927 [Epoch 205][Batch 199], Speed: 342.654 samples/sec, CrossEntropy=2.099, SmoothL1=0.906 [Epoch 205][Batch 299], Speed: 358.764 samples/sec, CrossEntropy=2.100, SmoothL1=0.904 [Epoch 205][Batch 399], Speed: 347.877 samples/sec, CrossEntropy=2.102, SmoothL1=0.904 [Epoch 205][Batch 499], Speed: 351.302 samples/sec, CrossEntropy=2.098, SmoothL1=0.902 [Epoch 205][Batch 599], Speed: 359.365 samples/sec, CrossEntropy=2.109, SmoothL1=0.902 [Epoch 205][Batch 699], Speed: 358.392 samples/sec, CrossEntropy=2.107, SmoothL1=0.900 [Epoch 205][Batch 799], Speed: 350.300 samples/sec, CrossEntropy=2.109, SmoothL1=0.902 [Epoch 205][Batch 899], Speed: 352.919 samples/sec, CrossEntropy=2.109, SmoothL1=0.902 [Epoch 205][Batch 999], Speed: 349.050 samples/sec, CrossEntropy=2.109, SmoothL1=0.902 [Epoch 205][Batch 1099], Speed: 347.381 samples/sec, CrossEntropy=2.113, SmoothL1=0.904 [Epoch 205][Batch 1199], Speed: 353.398 samples/sec, CrossEntropy=2.112, SmoothL1=0.903 [Epoch 205][Batch 1299], Speed: 360.829 samples/sec, CrossEntropy=2.106, SmoothL1=0.901 [Epoch 205][Batch 1399], Speed: 351.445 samples/sec, CrossEntropy=2.108, SmoothL1=0.902 [Epoch 205][Batch 1499], Speed: 350.213 samples/sec, CrossEntropy=2.106, SmoothL1=0.900 [Epoch 205][Batch 1599], Speed: 362.549 samples/sec, CrossEntropy=2.105, SmoothL1=0.900 [Epoch 205][Batch 1699], Speed: 354.457 samples/sec, CrossEntropy=2.103, SmoothL1=0.898 [Epoch 205][Batch 1799], Speed: 354.670 samples/sec, CrossEntropy=2.104, SmoothL1=0.899 [Epoch 205] Training cost: 335.101, CrossEntropy=2.103, SmoothL1=0.899 [Epoch 205] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.416 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.334 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.382 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.580 person=34.6 bicycle=17.3 car=20.4 motorcycle=27.4 airplane=45.7 bus=50.2 train=54.3 truck=22.1 boat=11.3 traffic light=8.6 fire hydrant=46.5 stop sign=46.9 parking meter=33.1 bench=13.4 bird=16.2 cat=54.4 dog=47.3 horse=42.0 sheep=33.4 cow=32.0 elephant=46.7 bear=57.3 zebra=48.5 giraffe=49.4 backpack=4.0 umbrella=22.6 handbag=3.5 tie=14.7 suitcase=18.1 frisbee=32.4 skis=11.5 snowboard=11.5 sports ball=17.9 kite=17.4 baseball bat=9.7 baseball glove=14.0 skateboard=27.4 surfboard=18.2 tennis racket=25.8 bottle=13.3 wine glass=13.4 cup=19.0 fork=15.8 knife=5.6 spoon=4.7 bowl=24.8 banana=14.6 apple=10.2 sandwich=28.9 orange=20.1 broccoli=12.9 carrot=10.3 hot dog=23.2 pizza=36.9 donut=27.7 cake=20.6 chair=13.2 couch=34.0 potted plant=12.9 bed=35.0 dining table=20.6 toilet=47.8 tv=42.0 laptop=44.4 mouse=33.5 remote=7.2 keyboard=33.9 cell phone=16.6 microwave=36.2 oven=27.9 toaster=7.3 sink=23.0 refrigerator=37.2 book=4.9 clock=30.1 vase=16.7 scissors=19.8 teddy bear=32.2 hair drier=4.0 toothbrush=7.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 206][Batch 99], Speed: 345.451 samples/sec, CrossEntropy=2.097, SmoothL1=0.925 [Epoch 206][Batch 199], Speed: 345.447 samples/sec, CrossEntropy=2.108, SmoothL1=0.925 [Epoch 206][Batch 299], Speed: 341.201 samples/sec, CrossEntropy=2.122, SmoothL1=0.920 [Epoch 206][Batch 399], Speed: 351.076 samples/sec, CrossEntropy=2.112, SmoothL1=0.918 [Epoch 206][Batch 499], Speed: 349.579 samples/sec, CrossEntropy=2.117, SmoothL1=0.919 [Epoch 206][Batch 599], Speed: 351.048 samples/sec, CrossEntropy=2.115, SmoothL1=0.916 [Epoch 206][Batch 699], Speed: 362.476 samples/sec, CrossEntropy=2.119, SmoothL1=0.914 [Epoch 206][Batch 799], Speed: 362.618 samples/sec, CrossEntropy=2.119, SmoothL1=0.911 [Epoch 206][Batch 899], Speed: 351.612 samples/sec, CrossEntropy=2.121, SmoothL1=0.913 [Epoch 206][Batch 999], Speed: 346.587 samples/sec, CrossEntropy=2.126, SmoothL1=0.915 [Epoch 206][Batch 1099], Speed: 359.211 samples/sec, CrossEntropy=2.122, SmoothL1=0.912 [Epoch 206][Batch 1199], Speed: 360.720 samples/sec, CrossEntropy=2.122, SmoothL1=0.911 [Epoch 206][Batch 1299], Speed: 350.271 samples/sec, CrossEntropy=2.122, SmoothL1=0.911 [Epoch 206][Batch 1399], Speed: 349.193 samples/sec, CrossEntropy=2.119, SmoothL1=0.910 [Epoch 206][Batch 1499], Speed: 351.312 samples/sec, CrossEntropy=2.119, SmoothL1=0.910 [Epoch 206][Batch 1599], Speed: 342.671 samples/sec, CrossEntropy=2.118, SmoothL1=0.909 [Epoch 206][Batch 1699], Speed: 349.224 samples/sec, CrossEntropy=2.116, SmoothL1=0.908 [Epoch 206][Batch 1799], Speed: 347.020 samples/sec, CrossEntropy=2.115, SmoothL1=0.908 [Epoch 206] Training cost: 334.384, CrossEntropy=2.116, SmoothL1=0.908 [Epoch 206] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.251 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.268 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.445 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.237 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.336 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.349 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.382 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.594 person=34.6 bicycle=17.6 car=20.5 motorcycle=27.5 airplane=46.1 bus=50.9 train=54.6 truck=22.0 boat=11.2 traffic light=8.5 fire hydrant=46.1 stop sign=47.6 parking meter=33.8 bench=13.5 bird=15.9 cat=54.3 dog=47.2 horse=42.2 sheep=33.5 cow=31.7 elephant=47.1 bear=58.1 zebra=48.9 giraffe=49.9 backpack=4.1 umbrella=22.9 handbag=3.5 tie=14.8 suitcase=18.3 frisbee=31.9 skis=11.4 snowboard=11.7 sports ball=18.1 kite=17.5 baseball bat=10.1 baseball glove=14.1 skateboard=27.7 surfboard=18.3 tennis racket=26.0 bottle=13.4 wine glass=13.0 cup=18.9 fork=15.8 knife=5.3 spoon=4.9 bowl=25.2 banana=14.8 apple=10.2 sandwich=28.7 orange=20.5 broccoli=13.0 carrot=10.1 hot dog=23.1 pizza=37.0 donut=27.7 cake=20.9 chair=13.0 couch=34.2 potted plant=13.4 bed=34.9 dining table=20.8 toilet=47.5 tv=42.1 laptop=44.6 mouse=33.3 remote=7.3 keyboard=33.6 cell phone=16.4 microwave=36.2 oven=28.1 toaster=10.1 sink=23.2 refrigerator=38.5 book=4.8 clock=30.1 vase=16.9 scissors=19.5 teddy bear=31.8 hair drier=4.0 toothbrush=7.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.1 [Epoch 207][Batch 99], Speed: 342.473 samples/sec, CrossEntropy=2.109, SmoothL1=0.909 [Epoch 207][Batch 199], Speed: 348.046 samples/sec, CrossEntropy=2.116, SmoothL1=0.902 [Epoch 207][Batch 299], Speed: 351.967 samples/sec, CrossEntropy=2.104, SmoothL1=0.893 [Epoch 207][Batch 399], Speed: 350.410 samples/sec, CrossEntropy=2.109, SmoothL1=0.897 [Epoch 207][Batch 499], Speed: 349.248 samples/sec, CrossEntropy=2.112, SmoothL1=0.904 [Epoch 207][Batch 599], Speed: 348.851 samples/sec, CrossEntropy=2.118, SmoothL1=0.904 [Epoch 207][Batch 699], Speed: 348.279 samples/sec, CrossEntropy=2.111, SmoothL1=0.903 [Epoch 207][Batch 799], Speed: 350.964 samples/sec, CrossEntropy=2.110, SmoothL1=0.901 [Epoch 207][Batch 899], Speed: 350.707 samples/sec, CrossEntropy=2.106, SmoothL1=0.899 [Epoch 207][Batch 999], Speed: 348.910 samples/sec, CrossEntropy=2.106, SmoothL1=0.900 [Epoch 207][Batch 1099], Speed: 358.128 samples/sec, CrossEntropy=2.107, SmoothL1=0.898 [Epoch 207][Batch 1199], Speed: 354.243 samples/sec, CrossEntropy=2.109, SmoothL1=0.902 [Epoch 207][Batch 1299], Speed: 355.652 samples/sec, CrossEntropy=2.107, SmoothL1=0.901 [Epoch 207][Batch 1399], Speed: 349.573 samples/sec, CrossEntropy=2.106, SmoothL1=0.901 [Epoch 207][Batch 1499], Speed: 354.446 samples/sec, CrossEntropy=2.105, SmoothL1=0.902 [Epoch 207][Batch 1599], Speed: 364.924 samples/sec, CrossEntropy=2.104, SmoothL1=0.901 [Epoch 207][Batch 1699], Speed: 351.344 samples/sec, CrossEntropy=2.104, SmoothL1=0.900 [Epoch 207][Batch 1799], Speed: 341.962 samples/sec, CrossEntropy=2.108, SmoothL1=0.901 [Epoch 207] Training cost: 335.295, CrossEntropy=2.107, SmoothL1=0.900 [Epoch 207] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.436 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.580 person=34.5 bicycle=17.3 car=20.5 motorcycle=27.6 airplane=46.2 bus=50.5 train=55.0 truck=21.7 boat=11.1 traffic light=8.4 fire hydrant=46.3 stop sign=47.5 parking meter=33.6 bench=13.4 bird=15.8 cat=55.2 dog=47.4 horse=42.1 sheep=33.3 cow=32.0 elephant=46.4 bear=56.8 zebra=48.4 giraffe=49.9 backpack=4.2 umbrella=22.6 handbag=3.6 tie=14.8 suitcase=18.2 frisbee=32.2 skis=11.4 snowboard=11.8 sports ball=17.9 kite=17.7 baseball bat=10.0 baseball glove=14.2 skateboard=27.2 surfboard=18.5 tennis racket=25.9 bottle=13.3 wine glass=13.0 cup=18.8 fork=15.6 knife=5.6 spoon=4.6 bowl=25.0 banana=14.7 apple=10.3 sandwich=28.7 orange=20.1 broccoli=12.9 carrot=10.2 hot dog=23.2 pizza=37.0 donut=27.7 cake=20.2 chair=13.0 couch=33.5 potted plant=13.3 bed=34.6 dining table=20.9 toilet=47.9 tv=42.3 laptop=44.4 mouse=33.4 remote=7.5 keyboard=34.0 cell phone=16.5 microwave=35.3 oven=27.9 toaster=7.3 sink=22.9 refrigerator=38.0 book=4.9 clock=30.1 vase=16.7 scissors=19.2 teddy bear=32.3 hair drier=0.0 toothbrush=7.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 208][Batch 99], Speed: 359.061 samples/sec, CrossEntropy=2.096, SmoothL1=0.899 [Epoch 208][Batch 199], Speed: 360.100 samples/sec, CrossEntropy=2.108, SmoothL1=0.903 [Epoch 208][Batch 299], Speed: 356.737 samples/sec, CrossEntropy=2.133, SmoothL1=0.914 [Epoch 208][Batch 399], Speed: 358.638 samples/sec, CrossEntropy=2.140, SmoothL1=0.916 [Epoch 208][Batch 499], Speed: 347.393 samples/sec, CrossEntropy=2.147, SmoothL1=0.926 [Epoch 208][Batch 599], Speed: 359.442 samples/sec, CrossEntropy=2.134, SmoothL1=0.920 [Epoch 208][Batch 699], Speed: 359.412 samples/sec, CrossEntropy=2.134, SmoothL1=0.919 [Epoch 208][Batch 799], Speed: 347.047 samples/sec, CrossEntropy=2.131, SmoothL1=0.917 [Epoch 208][Batch 899], Speed: 340.870 samples/sec, CrossEntropy=2.133, SmoothL1=0.917 [Epoch 208][Batch 999], Speed: 353.815 samples/sec, CrossEntropy=2.134, SmoothL1=0.916 [Epoch 208][Batch 1099], Speed: 352.095 samples/sec, CrossEntropy=2.130, SmoothL1=0.912 [Epoch 208][Batch 1199], Speed: 343.656 samples/sec, CrossEntropy=2.134, SmoothL1=0.915 [Epoch 208][Batch 1299], Speed: 359.439 samples/sec, CrossEntropy=2.130, SmoothL1=0.914 [Epoch 208][Batch 1399], Speed: 355.618 samples/sec, CrossEntropy=2.127, SmoothL1=0.912 [Epoch 208][Batch 1499], Speed: 341.166 samples/sec, CrossEntropy=2.123, SmoothL1=0.912 [Epoch 208][Batch 1599], Speed: 351.727 samples/sec, CrossEntropy=2.120, SmoothL1=0.909 [Epoch 208][Batch 1699], Speed: 354.627 samples/sec, CrossEntropy=2.118, SmoothL1=0.909 [Epoch 208][Batch 1799], Speed: 358.827 samples/sec, CrossEntropy=2.118, SmoothL1=0.908 [Epoch 208] Training cost: 335.022, CrossEntropy=2.117, SmoothL1=0.908 [Epoch 208] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.447 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.236 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.336 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.348 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.594 person=34.5 bicycle=17.4 car=20.5 motorcycle=27.3 airplane=46.0 bus=50.6 train=54.6 truck=22.4 boat=11.2 traffic light=8.3 fire hydrant=46.3 stop sign=46.8 parking meter=33.7 bench=13.6 bird=15.8 cat=54.7 dog=47.2 horse=42.1 sheep=33.5 cow=32.1 elephant=46.3 bear=57.4 zebra=48.6 giraffe=49.7 backpack=4.2 umbrella=22.5 handbag=3.5 tie=14.8 suitcase=18.3 frisbee=32.5 skis=11.3 snowboard=11.8 sports ball=18.1 kite=17.6 baseball bat=9.5 baseball glove=13.9 skateboard=27.7 surfboard=18.4 tennis racket=25.7 bottle=13.4 wine glass=13.1 cup=18.7 fork=15.6 knife=5.8 spoon=4.7 bowl=24.9 banana=14.8 apple=10.2 sandwich=28.3 orange=20.3 broccoli=13.1 carrot=10.4 hot dog=23.0 pizza=37.0 donut=27.4 cake=20.8 chair=13.2 couch=34.0 potted plant=13.2 bed=34.5 dining table=20.4 toilet=47.7 tv=42.5 laptop=44.5 mouse=33.6 remote=7.7 keyboard=33.6 cell phone=16.5 microwave=36.8 oven=28.2 toaster=10.5 sink=22.9 refrigerator=38.0 book=4.7 clock=30.5 vase=16.8 scissors=20.2 teddy bear=31.8 hair drier=2.0 toothbrush=6.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 209][Batch 99], Speed: 358.282 samples/sec, CrossEntropy=2.109, SmoothL1=0.928 [Epoch 209][Batch 199], Speed: 346.774 samples/sec, CrossEntropy=2.101, SmoothL1=0.900 [Epoch 209][Batch 299], Speed: 348.331 samples/sec, CrossEntropy=2.094, SmoothL1=0.899 [Epoch 209][Batch 399], Speed: 350.333 samples/sec, CrossEntropy=2.101, SmoothL1=0.899 [Epoch 209][Batch 499], Speed: 363.140 samples/sec, CrossEntropy=2.098, SmoothL1=0.897 [Epoch 209][Batch 599], Speed: 359.287 samples/sec, CrossEntropy=2.096, SmoothL1=0.896 [Epoch 209][Batch 699], Speed: 357.238 samples/sec, CrossEntropy=2.101, SmoothL1=0.896 [Epoch 209][Batch 799], Speed: 358.267 samples/sec, CrossEntropy=2.104, SmoothL1=0.898 [Epoch 209][Batch 899], Speed: 356.195 samples/sec, CrossEntropy=2.107, SmoothL1=0.900 [Epoch 209][Batch 999], Speed: 343.040 samples/sec, CrossEntropy=2.105, SmoothL1=0.898 [Epoch 209][Batch 1099], Speed: 350.738 samples/sec, CrossEntropy=2.104, SmoothL1=0.900 [Epoch 209][Batch 1199], Speed: 354.080 samples/sec, CrossEntropy=2.103, SmoothL1=0.898 [Epoch 209][Batch 1299], Speed: 350.962 samples/sec, CrossEntropy=2.105, SmoothL1=0.900 [Epoch 209][Batch 1399], Speed: 357.392 samples/sec, CrossEntropy=2.106, SmoothL1=0.900 [Epoch 209][Batch 1499], Speed: 359.032 samples/sec, CrossEntropy=2.109, SmoothL1=0.902 [Epoch 209][Batch 1599], Speed: 342.614 samples/sec, CrossEntropy=2.111, SmoothL1=0.903 [Epoch 209][Batch 1699], Speed: 366.359 samples/sec, CrossEntropy=2.113, SmoothL1=0.904 [Epoch 209][Batch 1799], Speed: 342.241 samples/sec, CrossEntropy=2.113, SmoothL1=0.903 [Epoch 209] Training cost: 335.460, CrossEntropy=2.113, SmoothL1=0.903 [Epoch 209] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.418 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.445 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.236 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.336 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.349 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.383 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.592 person=34.4 bicycle=17.2 car=20.5 motorcycle=27.4 airplane=45.7 bus=50.5 train=54.3 truck=22.3 boat=11.3 traffic light=8.5 fire hydrant=46.3 stop sign=47.0 parking meter=33.9 bench=13.5 bird=15.9 cat=55.0 dog=47.4 horse=42.1 sheep=33.3 cow=31.8 elephant=46.6 bear=57.9 zebra=48.8 giraffe=49.3 backpack=4.2 umbrella=22.5 handbag=3.6 tie=14.8 suitcase=18.3 frisbee=32.4 skis=11.9 snowboard=12.3 sports ball=18.2 kite=17.4 baseball bat=9.9 baseball glove=13.9 skateboard=27.7 surfboard=18.2 tennis racket=26.3 bottle=13.5 wine glass=13.2 cup=19.0 fork=16.0 knife=5.6 spoon=4.6 bowl=24.8 banana=14.8 apple=10.3 sandwich=28.8 orange=20.2 broccoli=13.0 carrot=10.1 hot dog=22.6 pizza=37.0 donut=27.6 cake=20.5 chair=13.1 couch=34.2 potted plant=13.1 bed=34.1 dining table=20.6 toilet=47.5 tv=42.5 laptop=44.3 mouse=33.1 remote=7.6 keyboard=34.1 cell phone=16.7 microwave=36.0 oven=28.0 toaster=10.5 sink=22.9 refrigerator=37.9 book=4.8 clock=30.2 vase=16.7 scissors=19.4 teddy bear=31.9 hair drier=3.0 toothbrush=6.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 210][Batch 99], Speed: 358.933 samples/sec, CrossEntropy=2.131, SmoothL1=0.898 [Epoch 210][Batch 199], Speed: 350.372 samples/sec, CrossEntropy=2.108, SmoothL1=0.900 [Epoch 210][Batch 299], Speed: 344.079 samples/sec, CrossEntropy=2.105, SmoothL1=0.895 [Epoch 210][Batch 399], Speed: 352.260 samples/sec, CrossEntropy=2.107, SmoothL1=0.899 [Epoch 210][Batch 499], Speed: 352.232 samples/sec, CrossEntropy=2.110, SmoothL1=0.898 [Epoch 210][Batch 599], Speed: 358.124 samples/sec, CrossEntropy=2.110, SmoothL1=0.901 [Epoch 210][Batch 699], Speed: 344.401 samples/sec, CrossEntropy=2.113, SmoothL1=0.906 [Epoch 210][Batch 799], Speed: 359.355 samples/sec, CrossEntropy=2.115, SmoothL1=0.907 [Epoch 210][Batch 899], Speed: 358.202 samples/sec, CrossEntropy=2.112, SmoothL1=0.902 [Epoch 210][Batch 999], Speed: 349.922 samples/sec, CrossEntropy=2.113, SmoothL1=0.904 [Epoch 210][Batch 1099], Speed: 360.895 samples/sec, CrossEntropy=2.112, SmoothL1=0.903 [Epoch 210][Batch 1199], Speed: 356.388 samples/sec, CrossEntropy=2.116, SmoothL1=0.906 [Epoch 210][Batch 1299], Speed: 347.887 samples/sec, CrossEntropy=2.114, SmoothL1=0.904 [Epoch 210][Batch 1399], Speed: 357.162 samples/sec, CrossEntropy=2.115, SmoothL1=0.906 [Epoch 210][Batch 1499], Speed: 347.495 samples/sec, CrossEntropy=2.114, SmoothL1=0.905 [Epoch 210][Batch 1599], Speed: 359.657 samples/sec, CrossEntropy=2.114, SmoothL1=0.904 [Epoch 210][Batch 1699], Speed: 358.884 samples/sec, CrossEntropy=2.110, SmoothL1=0.903 [Epoch 210][Batch 1799], Speed: 349.712 samples/sec, CrossEntropy=2.109, SmoothL1=0.902 [Epoch 210] Training cost: 334.876, CrossEntropy=2.109, SmoothL1=0.901 [Epoch 210] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.439 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.335 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.348 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.382 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.589 person=34.4 bicycle=17.1 car=20.5 motorcycle=27.9 airplane=46.2 bus=50.9 train=54.2 truck=22.0 boat=11.3 traffic light=8.5 fire hydrant=46.6 stop sign=47.1 parking meter=33.1 bench=13.5 bird=16.1 cat=54.6 dog=47.3 horse=42.3 sheep=33.6 cow=31.9 elephant=46.1 bear=56.4 zebra=48.5 giraffe=49.0 backpack=4.0 umbrella=22.6 handbag=3.6 tie=14.7 suitcase=18.6 frisbee=32.1 skis=11.5 snowboard=11.8 sports ball=17.9 kite=17.5 baseball bat=10.1 baseball glove=14.4 skateboard=27.8 surfboard=18.3 tennis racket=26.5 bottle=13.2 wine glass=13.1 cup=19.1 fork=15.7 knife=5.5 spoon=4.9 bowl=24.9 banana=15.0 apple=9.8 sandwich=28.0 orange=20.3 broccoli=13.0 carrot=10.1 hot dog=22.4 pizza=36.9 donut=27.6 cake=21.2 chair=13.2 couch=34.3 potted plant=12.8 bed=34.5 dining table=20.7 toilet=47.7 tv=42.3 laptop=44.5 mouse=33.0 remote=7.5 keyboard=33.5 cell phone=16.5 microwave=35.5 oven=28.3 toaster=8.3 sink=23.2 refrigerator=38.3 book=4.7 clock=30.3 vase=16.8 scissors=19.7 teddy bear=32.2 hair drier=3.0 toothbrush=6.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 211][Batch 99], Speed: 344.830 samples/sec, CrossEntropy=2.102, SmoothL1=0.882 [Epoch 211][Batch 199], Speed: 349.458 samples/sec, CrossEntropy=2.111, SmoothL1=0.892 [Epoch 211][Batch 299], Speed: 349.193 samples/sec, CrossEntropy=2.119, SmoothL1=0.901 [Epoch 211][Batch 399], Speed: 353.527 samples/sec, CrossEntropy=2.117, SmoothL1=0.895 [Epoch 211][Batch 499], Speed: 353.737 samples/sec, CrossEntropy=2.113, SmoothL1=0.894 [Epoch 211][Batch 599], Speed: 353.828 samples/sec, CrossEntropy=2.117, SmoothL1=0.901 [Epoch 211][Batch 699], Speed: 352.271 samples/sec, CrossEntropy=2.111, SmoothL1=0.899 [Epoch 211][Batch 799], Speed: 351.278 samples/sec, CrossEntropy=2.111, SmoothL1=0.901 [Epoch 211][Batch 899], Speed: 361.814 samples/sec, CrossEntropy=2.108, SmoothL1=0.901 [Epoch 211][Batch 999], Speed: 354.227 samples/sec, CrossEntropy=2.108, SmoothL1=0.901 [Epoch 211][Batch 1099], Speed: 349.634 samples/sec, CrossEntropy=2.114, SmoothL1=0.902 [Epoch 211][Batch 1199], Speed: 346.033 samples/sec, CrossEntropy=2.116, SmoothL1=0.903 [Epoch 211][Batch 1299], Speed: 346.797 samples/sec, CrossEntropy=2.110, SmoothL1=0.900 [Epoch 211][Batch 1399], Speed: 358.269 samples/sec, CrossEntropy=2.110, SmoothL1=0.900 [Epoch 211][Batch 1499], Speed: 358.103 samples/sec, CrossEntropy=2.108, SmoothL1=0.899 [Epoch 211][Batch 1599], Speed: 352.547 samples/sec, CrossEntropy=2.108, SmoothL1=0.898 [Epoch 211][Batch 1699], Speed: 362.909 samples/sec, CrossEntropy=2.109, SmoothL1=0.899 [Epoch 211][Batch 1799], Speed: 346.282 samples/sec, CrossEntropy=2.110, SmoothL1=0.900 [Epoch 211] Training cost: 334.675, CrossEntropy=2.112, SmoothL1=0.901 [Epoch 211] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.251 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.418 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.446 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.236 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.336 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.349 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.382 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.595 person=34.6 bicycle=17.2 car=20.6 motorcycle=27.9 airplane=45.2 bus=50.4 train=54.3 truck=22.3 boat=11.2 traffic light=8.4 fire hydrant=45.8 stop sign=47.0 parking meter=33.5 bench=13.2 bird=16.0 cat=54.6 dog=47.5 horse=41.9 sheep=33.7 cow=32.1 elephant=46.4 bear=57.9 zebra=48.6 giraffe=50.3 backpack=4.1 umbrella=22.8 handbag=3.5 tie=15.0 suitcase=18.5 frisbee=32.0 skis=11.4 snowboard=11.4 sports ball=18.0 kite=17.3 baseball bat=10.0 baseball glove=14.2 skateboard=27.7 surfboard=18.3 tennis racket=25.6 bottle=13.4 wine glass=13.1 cup=19.0 fork=15.7 knife=5.7 spoon=4.7 bowl=25.0 banana=14.4 apple=10.3 sandwich=28.5 orange=20.2 broccoli=13.1 carrot=10.4 hot dog=23.5 pizza=37.0 donut=27.8 cake=21.0 chair=13.2 couch=33.5 potted plant=13.1 bed=34.0 dining table=20.6 toilet=46.9 tv=42.1 laptop=44.6 mouse=33.2 remote=7.4 keyboard=34.2 cell phone=16.6 microwave=36.2 oven=27.8 toaster=11.3 sink=22.6 refrigerator=38.4 book=5.0 clock=30.3 vase=16.9 scissors=19.8 teddy bear=32.7 hair drier=3.0 toothbrush=7.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.1 [Epoch 212][Batch 99], Speed: 356.545 samples/sec, CrossEntropy=2.121, SmoothL1=0.906 [Epoch 212][Batch 199], Speed: 349.210 samples/sec, CrossEntropy=2.082, SmoothL1=0.894 [Epoch 212][Batch 299], Speed: 350.528 samples/sec, CrossEntropy=2.082, SmoothL1=0.894 [Epoch 212][Batch 399], Speed: 351.717 samples/sec, CrossEntropy=2.089, SmoothL1=0.897 [Epoch 212][Batch 499], Speed: 353.842 samples/sec, CrossEntropy=2.104, SmoothL1=0.903 [Epoch 212][Batch 599], Speed: 356.232 samples/sec, CrossEntropy=2.095, SmoothL1=0.899 [Epoch 212][Batch 699], Speed: 348.877 samples/sec, CrossEntropy=2.099, SmoothL1=0.902 [Epoch 212][Batch 799], Speed: 357.590 samples/sec, CrossEntropy=2.093, SmoothL1=0.901 [Epoch 212][Batch 899], Speed: 350.628 samples/sec, CrossEntropy=2.097, SmoothL1=0.901 [Epoch 212][Batch 999], Speed: 353.993 samples/sec, CrossEntropy=2.094, SmoothL1=0.901 [Epoch 212][Batch 1099], Speed: 350.195 samples/sec, CrossEntropy=2.096, SmoothL1=0.900 [Epoch 212][Batch 1199], Speed: 340.770 samples/sec, CrossEntropy=2.099, SmoothL1=0.901 [Epoch 212][Batch 1299], Speed: 346.021 samples/sec, CrossEntropy=2.102, SmoothL1=0.901 [Epoch 212][Batch 1399], Speed: 357.272 samples/sec, CrossEntropy=2.102, SmoothL1=0.903 [Epoch 212][Batch 1499], Speed: 345.114 samples/sec, CrossEntropy=2.103, SmoothL1=0.902 [Epoch 212][Batch 1599], Speed: 335.958 samples/sec, CrossEntropy=2.102, SmoothL1=0.902 [Epoch 212][Batch 1699], Speed: 352.399 samples/sec, CrossEntropy=2.100, SmoothL1=0.901 [Epoch 212][Batch 1799], Speed: 350.489 samples/sec, CrossEntropy=2.101, SmoothL1=0.901 [Epoch 212] Training cost: 336.153, CrossEntropy=2.103, SmoothL1=0.902 [Epoch 212] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.251 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.448 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.236 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.335 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.349 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.382 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.589 person=34.6 bicycle=17.4 car=20.6 motorcycle=27.9 airplane=45.6 bus=50.8 train=54.4 truck=22.4 boat=11.5 traffic light=8.5 fire hydrant=46.1 stop sign=47.6 parking meter=33.7 bench=13.4 bird=15.9 cat=55.0 dog=47.3 horse=41.9 sheep=33.8 cow=32.2 elephant=46.6 bear=56.7 zebra=48.7 giraffe=49.9 backpack=4.0 umbrella=22.9 handbag=3.6 tie=14.9 suitcase=18.6 frisbee=32.3 skis=11.6 snowboard=11.7 sports ball=18.3 kite=17.6 baseball bat=10.0 baseball glove=14.0 skateboard=27.9 surfboard=18.3 tennis racket=26.1 bottle=13.5 wine glass=13.1 cup=18.9 fork=15.6 knife=5.5 spoon=4.9 bowl=25.0 banana=14.7 apple=10.1 sandwich=29.0 orange=20.6 broccoli=13.2 carrot=10.3 hot dog=23.3 pizza=37.0 donut=27.9 cake=21.1 chair=13.1 couch=34.2 potted plant=12.7 bed=34.4 dining table=20.5 toilet=47.4 tv=42.4 laptop=44.6 mouse=32.3 remote=7.2 keyboard=33.7 cell phone=16.5 microwave=36.8 oven=28.5 toaster=11.9 sink=22.8 refrigerator=37.5 book=4.9 clock=30.3 vase=16.7 scissors=19.3 teddy bear=32.4 hair drier=0.0 toothbrush=7.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.1 [Epoch 213][Batch 99], Speed: 355.870 samples/sec, CrossEntropy=2.127, SmoothL1=0.884 [Epoch 213][Batch 199], Speed: 343.957 samples/sec, CrossEntropy=2.103, SmoothL1=0.897 [Epoch 213][Batch 299], Speed: 363.561 samples/sec, CrossEntropy=2.116, SmoothL1=0.901 [Epoch 213][Batch 399], Speed: 359.313 samples/sec, CrossEntropy=2.120, SmoothL1=0.914 [Epoch 213][Batch 499], Speed: 358.690 samples/sec, CrossEntropy=2.117, SmoothL1=0.907 [Epoch 213][Batch 599], Speed: 359.136 samples/sec, CrossEntropy=2.111, SmoothL1=0.902 [Epoch 213][Batch 699], Speed: 348.501 samples/sec, CrossEntropy=2.110, SmoothL1=0.905 [Epoch 213][Batch 799], Speed: 351.130 samples/sec, CrossEntropy=2.108, SmoothL1=0.903 [Epoch 213][Batch 899], Speed: 344.229 samples/sec, CrossEntropy=2.115, SmoothL1=0.907 [Epoch 213][Batch 999], Speed: 355.235 samples/sec, CrossEntropy=2.116, SmoothL1=0.907 [Epoch 213][Batch 1099], Speed: 344.991 samples/sec, CrossEntropy=2.112, SmoothL1=0.903 [Epoch 213][Batch 1199], Speed: 365.247 samples/sec, CrossEntropy=2.115, SmoothL1=0.903 [Epoch 213][Batch 1299], Speed: 350.067 samples/sec, CrossEntropy=2.113, SmoothL1=0.901 [Epoch 213][Batch 1399], Speed: 362.214 samples/sec, CrossEntropy=2.114, SmoothL1=0.900 [Epoch 213][Batch 1499], Speed: 351.729 samples/sec, CrossEntropy=2.114, SmoothL1=0.900 [Epoch 213][Batch 1599], Speed: 356.803 samples/sec, CrossEntropy=2.112, SmoothL1=0.898 [Epoch 213][Batch 1699], Speed: 340.571 samples/sec, CrossEntropy=2.113, SmoothL1=0.900 [Epoch 213][Batch 1799], Speed: 353.196 samples/sec, CrossEntropy=2.110, SmoothL1=0.899 [Epoch 213] Training cost: 335.121, CrossEntropy=2.108, SmoothL1=0.897 [Epoch 213] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.251 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.418 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.263 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.450 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.237 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.336 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.349 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.595 person=34.6 bicycle=17.4 car=20.4 motorcycle=27.7 airplane=45.5 bus=50.5 train=54.7 truck=22.1 boat=11.2 traffic light=8.5 fire hydrant=46.4 stop sign=47.7 parking meter=33.0 bench=13.5 bird=15.9 cat=54.2 dog=46.9 horse=42.2 sheep=33.8 cow=32.1 elephant=47.1 bear=58.1 zebra=48.8 giraffe=50.3 backpack=3.9 umbrella=22.8 handbag=3.5 tie=14.5 suitcase=18.6 frisbee=31.9 skis=11.3 snowboard=11.9 sports ball=18.3 kite=17.7 baseball bat=10.2 baseball glove=14.0 skateboard=27.1 surfboard=18.5 tennis racket=26.2 bottle=13.4 wine glass=13.3 cup=19.1 fork=15.6 knife=5.4 spoon=4.9 bowl=25.1 banana=14.7 apple=10.3 sandwich=28.7 orange=20.6 broccoli=13.1 carrot=10.4 hot dog=23.7 pizza=37.2 donut=27.7 cake=21.3 chair=13.0 couch=33.8 potted plant=13.2 bed=34.6 dining table=20.8 toilet=47.1 tv=42.2 laptop=44.6 mouse=33.1 remote=7.5 keyboard=33.6 cell phone=16.5 microwave=36.4 oven=28.1 toaster=11.6 sink=23.3 refrigerator=38.3 book=4.9 clock=30.0 vase=16.8 scissors=19.6 teddy bear=32.2 hair drier=4.0 toothbrush=7.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.1 [Epoch 214][Batch 99], Speed: 348.844 samples/sec, CrossEntropy=2.071, SmoothL1=0.902 [Epoch 214][Batch 199], Speed: 360.143 samples/sec, CrossEntropy=2.089, SmoothL1=0.898 [Epoch 214][Batch 299], Speed: 358.939 samples/sec, CrossEntropy=2.099, SmoothL1=0.908 [Epoch 214][Batch 399], Speed: 357.538 samples/sec, CrossEntropy=2.103, SmoothL1=0.909 [Epoch 214][Batch 499], Speed: 359.418 samples/sec, CrossEntropy=2.109, SmoothL1=0.912 [Epoch 214][Batch 599], Speed: 358.901 samples/sec, CrossEntropy=2.110, SmoothL1=0.909 [Epoch 214][Batch 699], Speed: 348.411 samples/sec, CrossEntropy=2.112, SmoothL1=0.908 [Epoch 214][Batch 799], Speed: 355.598 samples/sec, CrossEntropy=2.106, SmoothL1=0.905 [Epoch 214][Batch 899], Speed: 356.384 samples/sec, CrossEntropy=2.104, SmoothL1=0.905 [Epoch 214][Batch 999], Speed: 351.515 samples/sec, CrossEntropy=2.101, SmoothL1=0.901 [Epoch 214][Batch 1099], Speed: 358.126 samples/sec, CrossEntropy=2.101, SmoothL1=0.901 [Epoch 214][Batch 1199], Speed: 345.000 samples/sec, CrossEntropy=2.102, SmoothL1=0.902 [Epoch 214][Batch 1299], Speed: 366.307 samples/sec, CrossEntropy=2.103, SmoothL1=0.902 [Epoch 214][Batch 1399], Speed: 349.080 samples/sec, CrossEntropy=2.100, SmoothL1=0.897 [Epoch 214][Batch 1499], Speed: 357.221 samples/sec, CrossEntropy=2.101, SmoothL1=0.898 [Epoch 214][Batch 1599], Speed: 345.800 samples/sec, CrossEntropy=2.102, SmoothL1=0.897 [Epoch 214][Batch 1699], Speed: 347.200 samples/sec, CrossEntropy=2.103, SmoothL1=0.897 [Epoch 214][Batch 1799], Speed: 345.884 samples/sec, CrossEntropy=2.104, SmoothL1=0.897 [Epoch 214] Training cost: 335.462, CrossEntropy=2.104, SmoothL1=0.896 [Epoch 214] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.418 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.260 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.445 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.236 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.335 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.348 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.593 person=34.5 bicycle=17.1 car=20.5 motorcycle=27.3 airplane=45.6 bus=50.3 train=53.9 truck=22.3 boat=11.2 traffic light=8.4 fire hydrant=46.0 stop sign=47.0 parking meter=34.0 bench=13.4 bird=15.9 cat=55.2 dog=47.5 horse=42.1 sheep=33.5 cow=32.3 elephant=46.5 bear=56.4 zebra=48.4 giraffe=50.1 backpack=4.2 umbrella=22.6 handbag=3.6 tie=15.1 suitcase=18.6 frisbee=31.9 skis=11.3 snowboard=11.9 sports ball=17.7 kite=17.5 baseball bat=9.9 baseball glove=13.9 skateboard=27.3 surfboard=18.3 tennis racket=25.8 bottle=13.3 wine glass=13.1 cup=19.0 fork=16.0 knife=5.6 spoon=4.7 bowl=25.2 banana=14.8 apple=10.4 sandwich=28.2 orange=20.4 broccoli=13.0 carrot=10.4 hot dog=22.4 pizza=37.0 donut=27.5 cake=21.1 chair=13.0 couch=33.5 potted plant=13.0 bed=33.8 dining table=20.8 toilet=47.0 tv=41.9 laptop=44.4 mouse=32.5 remote=7.5 keyboard=33.6 cell phone=16.6 microwave=36.5 oven=27.9 toaster=10.9 sink=23.2 refrigerator=38.8 book=4.8 clock=30.0 vase=16.7 scissors=19.7 teddy bear=32.3 hair drier=2.0 toothbrush=7.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 215][Batch 99], Speed: 347.255 samples/sec, CrossEntropy=2.088, SmoothL1=0.888 [Epoch 215][Batch 199], Speed: 350.507 samples/sec, CrossEntropy=2.104, SmoothL1=0.891 [Epoch 215][Batch 299], Speed: 343.296 samples/sec, CrossEntropy=2.106, SmoothL1=0.888 [Epoch 215][Batch 399], Speed: 348.533 samples/sec, CrossEntropy=2.111, SmoothL1=0.892 [Epoch 215][Batch 499], Speed: 358.787 samples/sec, CrossEntropy=2.117, SmoothL1=0.900 [Epoch 215][Batch 599], Speed: 346.694 samples/sec, CrossEntropy=2.119, SmoothL1=0.901 [Epoch 215][Batch 699], Speed: 351.042 samples/sec, CrossEntropy=2.116, SmoothL1=0.899 [Epoch 215][Batch 799], Speed: 345.612 samples/sec, CrossEntropy=2.112, SmoothL1=0.898 [Epoch 215][Batch 899], Speed: 353.624 samples/sec, CrossEntropy=2.107, SmoothL1=0.894 [Epoch 215][Batch 999], Speed: 358.991 samples/sec, CrossEntropy=2.107, SmoothL1=0.894 [Epoch 215][Batch 1099], Speed: 349.811 samples/sec, CrossEntropy=2.107, SmoothL1=0.893 [Epoch 215][Batch 1199], Speed: 348.640 samples/sec, CrossEntropy=2.107, SmoothL1=0.893 [Epoch 215][Batch 1299], Speed: 359.128 samples/sec, CrossEntropy=2.105, SmoothL1=0.893 [Epoch 215][Batch 1399], Speed: 357.612 samples/sec, CrossEntropy=2.105, SmoothL1=0.892 [Epoch 215][Batch 1499], Speed: 349.776 samples/sec, CrossEntropy=2.105, SmoothL1=0.892 [Epoch 215][Batch 1599], Speed: 336.279 samples/sec, CrossEntropy=2.101, SmoothL1=0.889 [Epoch 215][Batch 1699], Speed: 349.853 samples/sec, CrossEntropy=2.104, SmoothL1=0.891 [Epoch 215][Batch 1799], Speed: 355.446 samples/sec, CrossEntropy=2.103, SmoothL1=0.890 [Epoch 215] Training cost: 335.209, CrossEntropy=2.103, SmoothL1=0.891 [Epoch 215] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.251 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.447 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.237 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.336 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.349 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.383 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.590 person=34.7 bicycle=17.2 car=20.5 motorcycle=28.0 airplane=45.7 bus=50.9 train=54.6 truck=22.3 boat=11.4 traffic light=8.4 fire hydrant=46.4 stop sign=47.4 parking meter=33.9 bench=13.6 bird=16.0 cat=54.4 dog=47.1 horse=41.7 sheep=33.7 cow=32.2 elephant=47.4 bear=58.2 zebra=48.7 giraffe=49.8 backpack=4.1 umbrella=22.9 handbag=3.5 tie=15.0 suitcase=18.6 frisbee=32.5 skis=11.6 snowboard=12.3 sports ball=18.3 kite=17.3 baseball bat=10.1 baseball glove=13.9 skateboard=27.7 surfboard=18.3 tennis racket=25.5 bottle=13.4 wine glass=13.2 cup=19.1 fork=15.9 knife=5.5 spoon=4.9 bowl=25.4 banana=15.0 apple=10.2 sandwich=28.8 orange=20.2 broccoli=13.2 carrot=10.6 hot dog=23.0 pizza=36.9 donut=27.6 cake=21.5 chair=13.2 couch=33.6 potted plant=13.5 bed=34.8 dining table=20.8 toilet=47.9 tv=42.2 laptop=44.4 mouse=33.4 remote=7.3 keyboard=33.7 cell phone=16.7 microwave=36.4 oven=28.5 toaster=10.2 sink=23.0 refrigerator=38.0 book=4.9 clock=30.4 vase=16.9 scissors=19.8 teddy bear=31.8 hair drier=0.0 toothbrush=7.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.1 [Epoch 216][Batch 99], Speed: 350.914 samples/sec, CrossEntropy=2.091, SmoothL1=0.887 [Epoch 216][Batch 199], Speed: 344.427 samples/sec, CrossEntropy=2.099, SmoothL1=0.900 [Epoch 216][Batch 299], Speed: 350.000 samples/sec, CrossEntropy=2.108, SmoothL1=0.901 [Epoch 216][Batch 399], Speed: 353.406 samples/sec, CrossEntropy=2.097, SmoothL1=0.893 [Epoch 216][Batch 499], Speed: 354.172 samples/sec, CrossEntropy=2.089, SmoothL1=0.887 [Epoch 216][Batch 599], Speed: 348.012 samples/sec, CrossEntropy=2.096, SmoothL1=0.889 [Epoch 216][Batch 699], Speed: 364.721 samples/sec, CrossEntropy=2.104, SmoothL1=0.893 [Epoch 216][Batch 799], Speed: 345.141 samples/sec, CrossEntropy=2.103, SmoothL1=0.892 [Epoch 216][Batch 899], Speed: 355.945 samples/sec, CrossEntropy=2.105, SmoothL1=0.894 [Epoch 216][Batch 999], Speed: 351.852 samples/sec, CrossEntropy=2.109, SmoothL1=0.896 [Epoch 216][Batch 1099], Speed: 358.568 samples/sec, CrossEntropy=2.109, SmoothL1=0.898 [Epoch 216][Batch 1199], Speed: 344.533 samples/sec, CrossEntropy=2.109, SmoothL1=0.897 [Epoch 216][Batch 1299], Speed: 357.520 samples/sec, CrossEntropy=2.109, SmoothL1=0.897 [Epoch 216][Batch 1399], Speed: 345.239 samples/sec, CrossEntropy=2.104, SmoothL1=0.895 [Epoch 216][Batch 1499], Speed: 356.977 samples/sec, CrossEntropy=2.107, SmoothL1=0.896 [Epoch 216][Batch 1599], Speed: 362.655 samples/sec, CrossEntropy=2.105, SmoothL1=0.896 [Epoch 216][Batch 1699], Speed: 348.105 samples/sec, CrossEntropy=2.105, SmoothL1=0.897 [Epoch 216][Batch 1799], Speed: 360.554 samples/sec, CrossEntropy=2.104, SmoothL1=0.896 [Epoch 216] Training cost: 334.491, CrossEntropy=2.101, SmoothL1=0.894 [Epoch 216] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.416 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.263 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.440 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.334 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.347 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.382 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.581 person=34.6 bicycle=17.2 car=20.5 motorcycle=27.6 airplane=45.6 bus=50.7 train=54.2 truck=22.4 boat=11.3 traffic light=8.4 fire hydrant=46.4 stop sign=47.7 parking meter=33.1 bench=13.5 bird=16.2 cat=54.6 dog=47.6 horse=41.7 sheep=33.6 cow=32.2 elephant=47.0 bear=58.4 zebra=48.8 giraffe=50.1 backpack=4.1 umbrella=22.9 handbag=3.6 tie=14.8 suitcase=18.6 frisbee=32.4 skis=11.6 snowboard=12.2 sports ball=18.3 kite=17.5 baseball bat=9.6 baseball glove=14.0 skateboard=27.3 surfboard=18.5 tennis racket=25.9 bottle=13.3 wine glass=13.1 cup=19.0 fork=15.8 knife=5.7 spoon=4.9 bowl=24.7 banana=14.7 apple=10.2 sandwich=28.2 orange=20.2 broccoli=13.1 carrot=10.5 hot dog=23.3 pizza=36.6 donut=27.9 cake=20.5 chair=13.2 couch=34.0 potted plant=12.9 bed=35.3 dining table=21.0 toilet=47.8 tv=42.7 laptop=44.5 mouse=33.5 remote=7.4 keyboard=33.3 cell phone=16.5 microwave=36.2 oven=27.9 toaster=8.1 sink=22.8 refrigerator=37.7 book=4.9 clock=29.9 vase=16.8 scissors=19.4 teddy bear=32.4 hair drier=0.0 toothbrush=7.6 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 217][Batch 99], Speed: 360.905 samples/sec, CrossEntropy=2.139, SmoothL1=0.931 [Epoch 217][Batch 199], Speed: 345.496 samples/sec, CrossEntropy=2.099, SmoothL1=0.896 [Epoch 217][Batch 299], Speed: 348.652 samples/sec, CrossEntropy=2.102, SmoothL1=0.887 [Epoch 217][Batch 399], Speed: 353.909 samples/sec, CrossEntropy=2.098, SmoothL1=0.884 [Epoch 217][Batch 499], Speed: 349.006 samples/sec, CrossEntropy=2.104, SmoothL1=0.889 [Epoch 217][Batch 599], Speed: 350.183 samples/sec, CrossEntropy=2.094, SmoothL1=0.886 [Epoch 217][Batch 699], Speed: 352.469 samples/sec, CrossEntropy=2.100, SmoothL1=0.889 [Epoch 217][Batch 799], Speed: 361.639 samples/sec, CrossEntropy=2.102, SmoothL1=0.890 [Epoch 217][Batch 899], Speed: 351.919 samples/sec, CrossEntropy=2.102, SmoothL1=0.892 [Epoch 217][Batch 999], Speed: 362.414 samples/sec, CrossEntropy=2.105, SmoothL1=0.892 [Epoch 217][Batch 1099], Speed: 352.122 samples/sec, CrossEntropy=2.105, SmoothL1=0.894 [Epoch 217][Batch 1199], Speed: 348.033 samples/sec, CrossEntropy=2.104, SmoothL1=0.894 [Epoch 217][Batch 1299], Speed: 357.312 samples/sec, CrossEntropy=2.105, SmoothL1=0.893 [Epoch 217][Batch 1399], Speed: 351.310 samples/sec, CrossEntropy=2.103, SmoothL1=0.890 [Epoch 217][Batch 1499], Speed: 352.085 samples/sec, CrossEntropy=2.106, SmoothL1=0.893 [Epoch 217][Batch 1599], Speed: 347.615 samples/sec, CrossEntropy=2.106, SmoothL1=0.895 [Epoch 217][Batch 1699], Speed: 352.797 samples/sec, CrossEntropy=2.106, SmoothL1=0.897 [Epoch 217][Batch 1799], Speed: 352.256 samples/sec, CrossEntropy=2.109, SmoothL1=0.898 [Epoch 217] Training cost: 334.739, CrossEntropy=2.109, SmoothL1=0.899 [Epoch 217] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.416 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.440 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.236 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.335 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.348 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.584 person=34.6 bicycle=17.4 car=20.5 motorcycle=27.5 airplane=45.5 bus=51.0 train=55.1 truck=22.2 boat=11.3 traffic light=8.3 fire hydrant=45.9 stop sign=47.3 parking meter=33.0 bench=13.7 bird=16.0 cat=55.1 dog=47.7 horse=41.9 sheep=33.6 cow=31.9 elephant=47.1 bear=59.2 zebra=48.9 giraffe=50.6 backpack=4.0 umbrella=22.5 handbag=3.5 tie=14.9 suitcase=18.2 frisbee=32.2 skis=11.7 snowboard=11.9 sports ball=18.2 kite=17.7 baseball bat=9.9 baseball glove=14.2 skateboard=26.8 surfboard=18.3 tennis racket=26.2 bottle=13.4 wine glass=13.1 cup=18.9 fork=16.0 knife=5.4 spoon=4.8 bowl=24.9 banana=15.0 apple=10.4 sandwich=28.8 orange=20.4 broccoli=12.7 carrot=10.5 hot dog=23.6 pizza=37.0 donut=27.8 cake=20.6 chair=13.0 couch=34.0 potted plant=12.7 bed=35.2 dining table=20.6 toilet=47.0 tv=42.2 laptop=44.4 mouse=32.7 remote=7.4 keyboard=33.6 cell phone=16.6 microwave=35.5 oven=27.6 toaster=8.9 sink=22.9 refrigerator=37.8 book=4.7 clock=30.3 vase=16.7 scissors=20.3 teddy bear=32.8 hair drier=0.0 toothbrush=7.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 218][Batch 99], Speed: 351.144 samples/sec, CrossEntropy=2.090, SmoothL1=0.896 [Epoch 218][Batch 199], Speed: 357.799 samples/sec, CrossEntropy=2.085, SmoothL1=0.891 [Epoch 218][Batch 299], Speed: 359.121 samples/sec, CrossEntropy=2.092, SmoothL1=0.895 [Epoch 218][Batch 399], Speed: 353.295 samples/sec, CrossEntropy=2.101, SmoothL1=0.899 [Epoch 218][Batch 499], Speed: 360.046 samples/sec, CrossEntropy=2.108, SmoothL1=0.901 [Epoch 218][Batch 599], Speed: 363.398 samples/sec, CrossEntropy=2.113, SmoothL1=0.903 [Epoch 218][Batch 699], Speed: 355.482 samples/sec, CrossEntropy=2.110, SmoothL1=0.902 [Epoch 218][Batch 799], Speed: 363.033 samples/sec, CrossEntropy=2.111, SmoothL1=0.901 [Epoch 218][Batch 899], Speed: 351.680 samples/sec, CrossEntropy=2.109, SmoothL1=0.902 [Epoch 218][Batch 999], Speed: 338.484 samples/sec, CrossEntropy=2.109, SmoothL1=0.901 [Epoch 218][Batch 1099], Speed: 342.262 samples/sec, CrossEntropy=2.112, SmoothL1=0.902 [Epoch 218][Batch 1199], Speed: 344.847 samples/sec, CrossEntropy=2.114, SmoothL1=0.903 [Epoch 218][Batch 1299], Speed: 344.285 samples/sec, CrossEntropy=2.113, SmoothL1=0.904 [Epoch 218][Batch 1399], Speed: 355.593 samples/sec, CrossEntropy=2.114, SmoothL1=0.906 [Epoch 218][Batch 1499], Speed: 351.165 samples/sec, CrossEntropy=2.114, SmoothL1=0.906 [Epoch 218][Batch 1599], Speed: 353.693 samples/sec, CrossEntropy=2.112, SmoothL1=0.905 [Epoch 218][Batch 1699], Speed: 351.221 samples/sec, CrossEntropy=2.113, SmoothL1=0.906 [Epoch 218][Batch 1799], Speed: 349.390 samples/sec, CrossEntropy=2.113, SmoothL1=0.905 [Epoch 218] Training cost: 335.083, CrossEntropy=2.112, SmoothL1=0.906 [Epoch 218] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.251 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.418 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.263 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.446 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.237 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.336 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.349 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.595 person=34.7 bicycle=17.4 car=20.5 motorcycle=27.9 airplane=45.2 bus=50.7 train=54.6 truck=22.4 boat=11.2 traffic light=8.3 fire hydrant=46.5 stop sign=47.0 parking meter=33.8 bench=13.4 bird=16.1 cat=54.5 dog=47.3 horse=42.2 sheep=33.3 cow=31.8 elephant=47.0 bear=57.5 zebra=48.2 giraffe=50.2 backpack=4.1 umbrella=22.7 handbag=3.5 tie=15.0 suitcase=18.6 frisbee=32.4 skis=11.7 snowboard=11.8 sports ball=18.2 kite=17.6 baseball bat=10.2 baseball glove=14.1 skateboard=27.5 surfboard=18.4 tennis racket=25.9 bottle=13.4 wine glass=13.0 cup=19.0 fork=15.8 knife=5.7 spoon=4.8 bowl=25.1 banana=14.3 apple=10.3 sandwich=28.9 orange=20.7 broccoli=13.0 carrot=10.4 hot dog=23.6 pizza=37.0 donut=28.0 cake=21.1 chair=13.3 couch=33.9 potted plant=13.0 bed=34.8 dining table=20.9 toilet=46.9 tv=42.6 laptop=44.8 mouse=33.0 remote=7.2 keyboard=34.0 cell phone=16.6 microwave=36.2 oven=28.0 toaster=10.9 sink=22.9 refrigerator=38.0 book=4.8 clock=30.1 vase=16.5 scissors=19.3 teddy bear=32.1 hair drier=3.0 toothbrush=7.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.1 [Epoch 219][Batch 99], Speed: 350.098 samples/sec, CrossEntropy=2.098, SmoothL1=0.879 [Epoch 219][Batch 199], Speed: 350.563 samples/sec, CrossEntropy=2.101, SmoothL1=0.885 [Epoch 219][Batch 299], Speed: 362.609 samples/sec, CrossEntropy=2.122, SmoothL1=0.906 [Epoch 219][Batch 399], Speed: 349.565 samples/sec, CrossEntropy=2.120, SmoothL1=0.905 [Epoch 219][Batch 499], Speed: 338.394 samples/sec, CrossEntropy=2.118, SmoothL1=0.902 [Epoch 219][Batch 599], Speed: 355.673 samples/sec, CrossEntropy=2.107, SmoothL1=0.894 [Epoch 219][Batch 699], Speed: 354.581 samples/sec, CrossEntropy=2.101, SmoothL1=0.890 [Epoch 219][Batch 799], Speed: 348.019 samples/sec, CrossEntropy=2.104, SmoothL1=0.892 [Epoch 219][Batch 899], Speed: 356.497 samples/sec, CrossEntropy=2.105, SmoothL1=0.892 [Epoch 219][Batch 999], Speed: 345.996 samples/sec, CrossEntropy=2.107, SmoothL1=0.895 [Epoch 219][Batch 1099], Speed: 349.564 samples/sec, CrossEntropy=2.106, SmoothL1=0.894 [Epoch 219][Batch 1199], Speed: 349.729 samples/sec, CrossEntropy=2.111, SmoothL1=0.898 [Epoch 219][Batch 1299], Speed: 351.856 samples/sec, CrossEntropy=2.111, SmoothL1=0.897 [Epoch 219][Batch 1399], Speed: 345.110 samples/sec, CrossEntropy=2.114, SmoothL1=0.899 [Epoch 219][Batch 1499], Speed: 350.357 samples/sec, CrossEntropy=2.114, SmoothL1=0.899 [Epoch 219][Batch 1599], Speed: 354.409 samples/sec, CrossEntropy=2.117, SmoothL1=0.902 [Epoch 219][Batch 1699], Speed: 347.901 samples/sec, CrossEntropy=2.118, SmoothL1=0.900 [Epoch 219][Batch 1799], Speed: 359.127 samples/sec, CrossEntropy=2.119, SmoothL1=0.900 [Epoch 219] Training cost: 335.247, CrossEntropy=2.119, SmoothL1=0.900 [Epoch 219] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.447 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.236 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.335 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.348 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.589 person=34.6 bicycle=17.1 car=20.5 motorcycle=27.7 airplane=45.8 bus=51.1 train=54.7 truck=22.2 boat=11.3 traffic light=8.3 fire hydrant=45.9 stop sign=47.0 parking meter=33.5 bench=13.3 bird=15.9 cat=54.4 dog=47.5 horse=42.1 sheep=33.3 cow=32.0 elephant=46.8 bear=57.2 zebra=48.4 giraffe=49.7 backpack=4.1 umbrella=22.6 handbag=3.5 tie=14.8 suitcase=18.5 frisbee=32.1 skis=11.4 snowboard=12.0 sports ball=17.9 kite=17.2 baseball bat=9.5 baseball glove=14.2 skateboard=27.8 surfboard=18.5 tennis racket=25.9 bottle=13.2 wine glass=13.2 cup=19.1 fork=16.1 knife=5.6 spoon=4.8 bowl=24.9 banana=14.8 apple=10.3 sandwich=28.2 orange=20.9 broccoli=13.0 carrot=10.5 hot dog=23.4 pizza=36.9 donut=27.7 cake=21.0 chair=13.1 couch=33.8 potted plant=13.1 bed=34.0 dining table=20.6 toilet=46.7 tv=42.2 laptop=44.6 mouse=33.0 remote=7.3 keyboard=33.8 cell phone=16.6 microwave=36.5 oven=28.3 toaster=11.8 sink=23.1 refrigerator=38.2 book=4.8 clock=30.4 vase=16.7 scissors=19.6 teddy bear=32.4 hair drier=1.5 toothbrush=7.0 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 220][Batch 99], Speed: 344.842 samples/sec, CrossEntropy=2.098, SmoothL1=0.891 [Epoch 220][Batch 199], Speed: 353.136 samples/sec, CrossEntropy=2.102, SmoothL1=0.894 [Epoch 220][Batch 299], Speed: 348.778 samples/sec, CrossEntropy=2.106, SmoothL1=0.896 [Epoch 220][Batch 399], Speed: 357.373 samples/sec, CrossEntropy=2.098, SmoothL1=0.894 [Epoch 220][Batch 499], Speed: 363.136 samples/sec, CrossEntropy=2.091, SmoothL1=0.888 [Epoch 220][Batch 599], Speed: 357.221 samples/sec, CrossEntropy=2.093, SmoothL1=0.891 [Epoch 220][Batch 699], Speed: 360.860 samples/sec, CrossEntropy=2.089, SmoothL1=0.885 [Epoch 220][Batch 799], Speed: 357.234 samples/sec, CrossEntropy=2.089, SmoothL1=0.888 [Epoch 220][Batch 899], Speed: 339.951 samples/sec, CrossEntropy=2.088, SmoothL1=0.885 [Epoch 220][Batch 999], Speed: 358.193 samples/sec, CrossEntropy=2.088, SmoothL1=0.885 [Epoch 220][Batch 1099], Speed: 358.278 samples/sec, CrossEntropy=2.094, SmoothL1=0.890 [Epoch 220][Batch 1199], Speed: 353.725 samples/sec, CrossEntropy=2.099, SmoothL1=0.893 [Epoch 220][Batch 1299], Speed: 359.133 samples/sec, CrossEntropy=2.099, SmoothL1=0.893 [Epoch 220][Batch 1399], Speed: 360.494 samples/sec, CrossEntropy=2.099, SmoothL1=0.895 [Epoch 220][Batch 1499], Speed: 347.258 samples/sec, CrossEntropy=2.100, SmoothL1=0.894 [Epoch 220][Batch 1599], Speed: 356.442 samples/sec, CrossEntropy=2.100, SmoothL1=0.893 [Epoch 220][Batch 1699], Speed: 354.940 samples/sec, CrossEntropy=2.101, SmoothL1=0.895 [Epoch 220][Batch 1799], Speed: 352.867 samples/sec, CrossEntropy=2.099, SmoothL1=0.894 [Epoch 220] Training cost: 335.126, CrossEntropy=2.101, SmoothL1=0.895 [Epoch 220] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.416 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.440 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.334 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.347 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.585 person=34.6 bicycle=17.1 car=20.6 motorcycle=27.7 airplane=45.4 bus=50.8 train=54.3 truck=22.6 boat=11.2 traffic light=8.6 fire hydrant=46.6 stop sign=47.2 parking meter=33.2 bench=13.4 bird=15.7 cat=54.7 dog=47.3 horse=42.3 sheep=33.4 cow=32.2 elephant=47.0 bear=56.8 zebra=48.2 giraffe=49.6 backpack=4.1 umbrella=22.6 handbag=3.5 tie=15.0 suitcase=18.4 frisbee=31.9 skis=11.4 snowboard=12.5 sports ball=18.0 kite=17.5 baseball bat=9.6 baseball glove=13.9 skateboard=27.2 surfboard=18.5 tennis racket=26.1 bottle=13.2 wine glass=13.0 cup=19.2 fork=16.1 knife=5.6 spoon=4.9 bowl=24.8 banana=14.7 apple=10.3 sandwich=28.6 orange=20.3 broccoli=12.7 carrot=10.5 hot dog=23.5 pizza=37.3 donut=27.6 cake=20.6 chair=13.1 couch=33.9 potted plant=13.0 bed=34.1 dining table=20.7 toilet=46.4 tv=42.3 laptop=44.6 mouse=33.0 remote=7.6 keyboard=33.6 cell phone=16.3 microwave=36.9 oven=27.9 toaster=8.8 sink=23.0 refrigerator=38.5 book=4.7 clock=30.4 vase=16.7 scissors=20.0 teddy bear=32.6 hair drier=0.0 toothbrush=6.7 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 221][Batch 99], Speed: 355.946 samples/sec, CrossEntropy=2.121, SmoothL1=0.927 [Epoch 221][Batch 199], Speed: 348.440 samples/sec, CrossEntropy=2.118, SmoothL1=0.911 [Epoch 221][Batch 299], Speed: 352.569 samples/sec, CrossEntropy=2.104, SmoothL1=0.895 [Epoch 221][Batch 399], Speed: 353.094 samples/sec, CrossEntropy=2.099, SmoothL1=0.896 [Epoch 221][Batch 499], Speed: 357.774 samples/sec, CrossEntropy=2.099, SmoothL1=0.898 [Epoch 221][Batch 599], Speed: 345.607 samples/sec, CrossEntropy=2.101, SmoothL1=0.898 [Epoch 221][Batch 699], Speed: 349.373 samples/sec, CrossEntropy=2.104, SmoothL1=0.899 [Epoch 221][Batch 799], Speed: 352.169 samples/sec, CrossEntropy=2.107, SmoothL1=0.901 [Epoch 221][Batch 899], Speed: 360.017 samples/sec, CrossEntropy=2.107, SmoothL1=0.901 [Epoch 221][Batch 999], Speed: 356.585 samples/sec, CrossEntropy=2.110, SmoothL1=0.905 [Epoch 221][Batch 1099], Speed: 348.778 samples/sec, CrossEntropy=2.110, SmoothL1=0.904 [Epoch 221][Batch 1199], Speed: 367.351 samples/sec, CrossEntropy=2.106, SmoothL1=0.901 [Epoch 221][Batch 1299], Speed: 344.488 samples/sec, CrossEntropy=2.103, SmoothL1=0.901 [Epoch 221][Batch 1399], Speed: 358.294 samples/sec, CrossEntropy=2.103, SmoothL1=0.903 [Epoch 221][Batch 1499], Speed: 347.539 samples/sec, CrossEntropy=2.102, SmoothL1=0.904 [Epoch 221][Batch 1599], Speed: 350.641 samples/sec, CrossEntropy=2.101, SmoothL1=0.903 [Epoch 221][Batch 1699], Speed: 347.098 samples/sec, CrossEntropy=2.102, SmoothL1=0.905 [Epoch 221][Batch 1799], Speed: 356.157 samples/sec, CrossEntropy=2.103, SmoothL1=0.905 [Epoch 221] Training cost: 334.673, CrossEntropy=2.103, SmoothL1=0.905 [Epoch 221] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.260 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.438 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.334 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.347 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.382 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.583 person=34.6 bicycle=17.3 car=20.5 motorcycle=28.0 airplane=45.5 bus=50.8 train=54.5 truck=22.0 boat=11.2 traffic light=8.5 fire hydrant=46.4 stop sign=47.2 parking meter=33.2 bench=13.5 bird=16.1 cat=54.5 dog=47.1 horse=42.3 sheep=33.5 cow=32.0 elephant=46.3 bear=55.9 zebra=48.5 giraffe=49.4 backpack=4.2 umbrella=22.7 handbag=3.5 tie=14.8 suitcase=18.0 frisbee=32.2 skis=11.4 snowboard=11.7 sports ball=18.2 kite=17.1 baseball bat=9.9 baseball glove=14.0 skateboard=27.6 surfboard=18.6 tennis racket=25.9 bottle=13.4 wine glass=13.0 cup=19.0 fork=16.0 knife=5.5 spoon=4.8 bowl=25.1 banana=14.9 apple=10.1 sandwich=28.6 orange=20.4 broccoli=13.1 carrot=10.5 hot dog=22.8 pizza=36.8 donut=27.8 cake=21.2 chair=13.0 couch=34.5 potted plant=13.1 bed=34.2 dining table=20.6 toilet=47.3 tv=42.6 laptop=44.6 mouse=33.3 remote=7.4 keyboard=33.1 cell phone=16.4 microwave=35.9 oven=27.8 toaster=9.2 sink=23.0 refrigerator=38.7 book=4.7 clock=30.4 vase=16.6 scissors=19.7 teddy bear=32.3 hair drier=0.7 toothbrush=6.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 222][Batch 99], Speed: 341.979 samples/sec, CrossEntropy=2.098, SmoothL1=0.914 [Epoch 222][Batch 199], Speed: 351.929 samples/sec, CrossEntropy=2.107, SmoothL1=0.898 [Epoch 222][Batch 299], Speed: 351.987 samples/sec, CrossEntropy=2.120, SmoothL1=0.910 [Epoch 222][Batch 399], Speed: 352.983 samples/sec, CrossEntropy=2.127, SmoothL1=0.911 [Epoch 222][Batch 499], Speed: 363.292 samples/sec, CrossEntropy=2.127, SmoothL1=0.915 [Epoch 222][Batch 599], Speed: 345.436 samples/sec, CrossEntropy=2.123, SmoothL1=0.914 [Epoch 222][Batch 699], Speed: 351.445 samples/sec, CrossEntropy=2.124, SmoothL1=0.915 [Epoch 222][Batch 799], Speed: 347.858 samples/sec, CrossEntropy=2.118, SmoothL1=0.913 [Epoch 222][Batch 899], Speed: 361.592 samples/sec, CrossEntropy=2.114, SmoothL1=0.910 [Epoch 222][Batch 999], Speed: 358.533 samples/sec, CrossEntropy=2.111, SmoothL1=0.909 [Epoch 222][Batch 1099], Speed: 349.115 samples/sec, CrossEntropy=2.112, SmoothL1=0.908 [Epoch 222][Batch 1199], Speed: 354.343 samples/sec, CrossEntropy=2.112, SmoothL1=0.906 [Epoch 222][Batch 1299], Speed: 351.634 samples/sec, CrossEntropy=2.111, SmoothL1=0.905 [Epoch 222][Batch 1399], Speed: 353.123 samples/sec, CrossEntropy=2.109, SmoothL1=0.904 [Epoch 222][Batch 1499], Speed: 364.292 samples/sec, CrossEntropy=2.108, SmoothL1=0.904 [Epoch 222][Batch 1599], Speed: 358.579 samples/sec, CrossEntropy=2.107, SmoothL1=0.904 [Epoch 222][Batch 1699], Speed: 358.186 samples/sec, CrossEntropy=2.106, SmoothL1=0.902 [Epoch 222][Batch 1799], Speed: 351.105 samples/sec, CrossEntropy=2.106, SmoothL1=0.901 [Epoch 222] Training cost: 334.338, CrossEntropy=2.107, SmoothL1=0.902 [Epoch 222] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.251 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.263 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.443 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.236 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.335 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.348 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.588 person=34.5 bicycle=17.5 car=20.5 motorcycle=27.9 airplane=45.5 bus=50.9 train=55.2 truck=22.3 boat=11.2 traffic light=8.5 fire hydrant=46.2 stop sign=47.8 parking meter=33.2 bench=13.4 bird=15.9 cat=54.5 dog=47.6 horse=41.9 sheep=33.7 cow=32.1 elephant=46.5 bear=56.9 zebra=48.5 giraffe=50.2 backpack=4.0 umbrella=22.6 handbag=3.5 tie=14.8 suitcase=18.4 frisbee=32.4 skis=11.7 snowboard=11.8 sports ball=18.4 kite=17.7 baseball bat=9.3 baseball glove=14.1 skateboard=28.0 surfboard=18.5 tennis racket=26.4 bottle=13.3 wine glass=13.1 cup=19.0 fork=15.8 knife=5.8 spoon=5.0 bowl=25.1 banana=14.8 apple=10.3 sandwich=28.8 orange=20.5 broccoli=13.3 carrot=10.3 hot dog=23.2 pizza=36.9 donut=27.5 cake=21.2 chair=13.1 couch=33.9 potted plant=13.0 bed=34.5 dining table=21.0 toilet=46.9 tv=42.3 laptop=44.8 mouse=33.6 remote=7.2 keyboard=33.7 cell phone=16.5 microwave=35.4 oven=28.3 toaster=10.9 sink=22.9 refrigerator=38.2 book=4.7 clock=30.2 vase=16.7 scissors=19.5 teddy bear=32.3 hair drier=0.0 toothbrush=7.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.1 [Epoch 223][Batch 99], Speed: 346.108 samples/sec, CrossEntropy=2.152, SmoothL1=0.914 [Epoch 223][Batch 199], Speed: 358.441 samples/sec, CrossEntropy=2.134, SmoothL1=0.899 [Epoch 223][Batch 299], Speed: 348.477 samples/sec, CrossEntropy=2.127, SmoothL1=0.900 [Epoch 223][Batch 399], Speed: 349.561 samples/sec, CrossEntropy=2.112, SmoothL1=0.899 [Epoch 223][Batch 499], Speed: 348.469 samples/sec, CrossEntropy=2.104, SmoothL1=0.901 [Epoch 223][Batch 599], Speed: 357.370 samples/sec, CrossEntropy=2.106, SmoothL1=0.901 [Epoch 223][Batch 699], Speed: 365.555 samples/sec, CrossEntropy=2.104, SmoothL1=0.901 [Epoch 223][Batch 799], Speed: 355.453 samples/sec, CrossEntropy=2.101, SmoothL1=0.901 [Epoch 223][Batch 899], Speed: 363.709 samples/sec, CrossEntropy=2.100, SmoothL1=0.902 [Epoch 223][Batch 999], Speed: 357.743 samples/sec, CrossEntropy=2.098, SmoothL1=0.897 [Epoch 223][Batch 1099], Speed: 360.224 samples/sec, CrossEntropy=2.098, SmoothL1=0.899 [Epoch 223][Batch 1199], Speed: 348.594 samples/sec, CrossEntropy=2.097, SmoothL1=0.900 [Epoch 223][Batch 1299], Speed: 354.007 samples/sec, CrossEntropy=2.098, SmoothL1=0.900 [Epoch 223][Batch 1399], Speed: 362.633 samples/sec, CrossEntropy=2.100, SmoothL1=0.900 [Epoch 223][Batch 1499], Speed: 349.963 samples/sec, CrossEntropy=2.099, SmoothL1=0.902 [Epoch 223][Batch 1599], Speed: 351.871 samples/sec, CrossEntropy=2.100, SmoothL1=0.902 [Epoch 223][Batch 1699], Speed: 355.188 samples/sec, CrossEntropy=2.099, SmoothL1=0.900 [Epoch 223][Batch 1799], Speed: 359.074 samples/sec, CrossEntropy=2.100, SmoothL1=0.900 [Epoch 223] Training cost: 334.635, CrossEntropy=2.099, SmoothL1=0.900 [Epoch 223] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.436 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.383 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.582 person=34.6 bicycle=17.3 car=20.5 motorcycle=27.9 airplane=45.5 bus=50.9 train=54.4 truck=22.2 boat=11.3 traffic light=8.5 fire hydrant=46.0 stop sign=47.7 parking meter=32.9 bench=13.3 bird=15.7 cat=55.0 dog=47.7 horse=42.2 sheep=33.8 cow=32.4 elephant=46.6 bear=57.3 zebra=48.9 giraffe=49.0 backpack=4.0 umbrella=22.5 handbag=3.5 tie=14.9 suitcase=18.4 frisbee=32.1 skis=11.6 snowboard=12.3 sports ball=18.3 kite=17.4 baseball bat=9.2 baseball glove=14.2 skateboard=27.0 surfboard=18.4 tennis racket=26.5 bottle=13.3 wine glass=13.1 cup=19.0 fork=15.9 knife=5.7 spoon=4.7 bowl=24.9 banana=14.7 apple=10.3 sandwich=28.6 orange=20.3 broccoli=12.7 carrot=10.6 hot dog=23.2 pizza=37.1 donut=27.5 cake=20.6 chair=13.1 couch=34.4 potted plant=12.7 bed=34.4 dining table=20.9 toilet=46.9 tv=42.0 laptop=44.2 mouse=33.1 remote=7.5 keyboard=33.6 cell phone=16.2 microwave=37.3 oven=28.0 toaster=7.3 sink=23.0 refrigerator=38.5 book=4.8 clock=30.4 vase=16.5 scissors=19.5 teddy bear=32.3 hair drier=0.0 toothbrush=6.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 224][Batch 99], Speed: 358.483 samples/sec, CrossEntropy=2.100, SmoothL1=0.915 [Epoch 224][Batch 199], Speed: 343.710 samples/sec, CrossEntropy=2.097, SmoothL1=0.901 [Epoch 224][Batch 299], Speed: 346.165 samples/sec, CrossEntropy=2.102, SmoothL1=0.892 [Epoch 224][Batch 399], Speed: 347.719 samples/sec, CrossEntropy=2.111, SmoothL1=0.900 [Epoch 224][Batch 499], Speed: 347.432 samples/sec, CrossEntropy=2.115, SmoothL1=0.899 [Epoch 224][Batch 599], Speed: 355.009 samples/sec, CrossEntropy=2.113, SmoothL1=0.897 [Epoch 224][Batch 699], Speed: 347.518 samples/sec, CrossEntropy=2.115, SmoothL1=0.897 [Epoch 224][Batch 799], Speed: 355.421 samples/sec, CrossEntropy=2.118, SmoothL1=0.900 [Epoch 224][Batch 899], Speed: 364.587 samples/sec, CrossEntropy=2.118, SmoothL1=0.902 [Epoch 224][Batch 999], Speed: 346.002 samples/sec, CrossEntropy=2.114, SmoothL1=0.901 [Epoch 224][Batch 1099], Speed: 357.545 samples/sec, CrossEntropy=2.110, SmoothL1=0.900 [Epoch 224][Batch 1199], Speed: 334.059 samples/sec, CrossEntropy=2.109, SmoothL1=0.898 [Epoch 224][Batch 1299], Speed: 352.666 samples/sec, CrossEntropy=2.106, SmoothL1=0.900 [Epoch 224][Batch 1399], Speed: 357.416 samples/sec, CrossEntropy=2.106, SmoothL1=0.897 [Epoch 224][Batch 1499], Speed: 351.573 samples/sec, CrossEntropy=2.105, SmoothL1=0.898 [Epoch 224][Batch 1599], Speed: 363.189 samples/sec, CrossEntropy=2.104, SmoothL1=0.897 [Epoch 224][Batch 1699], Speed: 351.594 samples/sec, CrossEntropy=2.107, SmoothL1=0.897 [Epoch 224][Batch 1799], Speed: 359.580 samples/sec, CrossEntropy=2.107, SmoothL1=0.897 [Epoch 224] Training cost: 334.717, CrossEntropy=2.108, SmoothL1=0.898 [Epoch 224] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.438 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.580 person=34.6 bicycle=17.2 car=20.6 motorcycle=27.3 airplane=45.3 bus=50.3 train=54.5 truck=21.9 boat=11.2 traffic light=8.3 fire hydrant=46.2 stop sign=47.4 parking meter=32.7 bench=13.3 bird=16.0 cat=55.2 dog=47.3 horse=42.2 sheep=33.7 cow=32.1 elephant=46.8 bear=56.4 zebra=48.5 giraffe=50.1 backpack=4.0 umbrella=22.4 handbag=3.4 tie=14.5 suitcase=18.0 frisbee=32.2 skis=11.3 snowboard=11.5 sports ball=18.1 kite=17.6 baseball bat=9.9 baseball glove=13.9 skateboard=27.6 surfboard=18.4 tennis racket=26.1 bottle=13.4 wine glass=13.1 cup=19.0 fork=15.7 knife=5.6 spoon=4.7 bowl=24.9 banana=14.7 apple=10.2 sandwich=28.7 orange=20.2 broccoli=12.8 carrot=10.1 hot dog=23.2 pizza=37.3 donut=27.4 cake=20.8 chair=13.2 couch=34.7 potted plant=13.4 bed=34.6 dining table=20.4 toilet=47.3 tv=42.4 laptop=44.4 mouse=33.4 remote=7.4 keyboard=33.4 cell phone=16.5 microwave=35.7 oven=28.1 toaster=8.3 sink=22.6 refrigerator=37.8 book=4.8 clock=30.1 vase=16.8 scissors=20.1 teddy bear=32.2 hair drier=0.0 toothbrush=6.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 225][Batch 99], Speed: 351.215 samples/sec, CrossEntropy=2.071, SmoothL1=0.899 [Epoch 225][Batch 199], Speed: 351.463 samples/sec, CrossEntropy=2.075, SmoothL1=0.890 [Epoch 225][Batch 299], Speed: 339.639 samples/sec, CrossEntropy=2.086, SmoothL1=0.895 [Epoch 225][Batch 399], Speed: 358.981 samples/sec, CrossEntropy=2.086, SmoothL1=0.891 [Epoch 225][Batch 499], Speed: 348.732 samples/sec, CrossEntropy=2.088, SmoothL1=0.892 [Epoch 225][Batch 599], Speed: 360.405 samples/sec, CrossEntropy=2.095, SmoothL1=0.899 [Epoch 225][Batch 699], Speed: 357.967 samples/sec, CrossEntropy=2.094, SmoothL1=0.898 [Epoch 225][Batch 799], Speed: 355.970 samples/sec, CrossEntropy=2.095, SmoothL1=0.897 [Epoch 225][Batch 899], Speed: 361.110 samples/sec, CrossEntropy=2.092, SmoothL1=0.896 [Epoch 225][Batch 999], Speed: 351.270 samples/sec, CrossEntropy=2.090, SmoothL1=0.895 [Epoch 225][Batch 1099], Speed: 351.208 samples/sec, CrossEntropy=2.090, SmoothL1=0.894 [Epoch 225][Batch 1199], Speed: 353.201 samples/sec, CrossEntropy=2.093, SmoothL1=0.895 [Epoch 225][Batch 1299], Speed: 353.481 samples/sec, CrossEntropy=2.093, SmoothL1=0.895 [Epoch 225][Batch 1399], Speed: 354.270 samples/sec, CrossEntropy=2.095, SmoothL1=0.896 [Epoch 225][Batch 1499], Speed: 362.420 samples/sec, CrossEntropy=2.098, SmoothL1=0.895 [Epoch 225][Batch 1599], Speed: 358.402 samples/sec, CrossEntropy=2.100, SmoothL1=0.897 [Epoch 225][Batch 1699], Speed: 360.932 samples/sec, CrossEntropy=2.101, SmoothL1=0.897 [Epoch 225][Batch 1799], Speed: 358.377 samples/sec, CrossEntropy=2.100, SmoothL1=0.895 [Epoch 225] Training cost: 334.936, CrossEntropy=2.100, SmoothL1=0.895 [Epoch 225] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.578 person=34.6 bicycle=16.8 car=20.6 motorcycle=27.9 airplane=45.6 bus=50.9 train=55.2 truck=22.2 boat=11.2 traffic light=8.6 fire hydrant=46.4 stop sign=46.8 parking meter=33.0 bench=13.5 bird=16.1 cat=54.8 dog=47.4 horse=41.9 sheep=33.4 cow=32.1 elephant=46.9 bear=56.1 zebra=48.4 giraffe=49.8 backpack=4.1 umbrella=23.0 handbag=3.5 tie=14.3 suitcase=18.3 frisbee=31.9 skis=11.5 snowboard=12.0 sports ball=18.4 kite=17.6 baseball bat=8.9 baseball glove=13.9 skateboard=27.3 surfboard=18.4 tennis racket=26.2 bottle=13.5 wine glass=13.1 cup=18.9 fork=15.6 knife=5.7 spoon=4.8 bowl=25.0 banana=14.4 apple=10.4 sandwich=28.4 orange=19.8 broccoli=13.0 carrot=10.3 hot dog=22.7 pizza=37.1 donut=27.6 cake=21.0 chair=13.0 couch=34.0 potted plant=13.1 bed=34.3 dining table=20.8 toilet=47.5 tv=42.4 laptop=44.5 mouse=33.2 remote=7.5 keyboard=33.3 cell phone=16.3 microwave=35.8 oven=27.8 toaster=7.6 sink=23.3 refrigerator=38.4 book=4.7 clock=30.6 vase=16.6 scissors=19.3 teddy bear=32.1 hair drier=0.0 toothbrush=6.5 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 226][Batch 99], Speed: 362.487 samples/sec, CrossEntropy=2.104, SmoothL1=0.911 [Epoch 226][Batch 199], Speed: 344.688 samples/sec, CrossEntropy=2.100, SmoothL1=0.903 [Epoch 226][Batch 299], Speed: 361.005 samples/sec, CrossEntropy=2.113, SmoothL1=0.908 [Epoch 226][Batch 399], Speed: 358.605 samples/sec, CrossEntropy=2.113, SmoothL1=0.903 [Epoch 226][Batch 499], Speed: 353.883 samples/sec, CrossEntropy=2.102, SmoothL1=0.898 [Epoch 226][Batch 599], Speed: 351.746 samples/sec, CrossEntropy=2.102, SmoothL1=0.900 [Epoch 226][Batch 699], Speed: 360.515 samples/sec, CrossEntropy=2.105, SmoothL1=0.903 [Epoch 226][Batch 799], Speed: 355.451 samples/sec, CrossEntropy=2.102, SmoothL1=0.903 [Epoch 226][Batch 899], Speed: 361.299 samples/sec, CrossEntropy=2.101, SmoothL1=0.900 [Epoch 226][Batch 999], Speed: 353.875 samples/sec, CrossEntropy=2.100, SmoothL1=0.898 [Epoch 226][Batch 1099], Speed: 350.577 samples/sec, CrossEntropy=2.102, SmoothL1=0.897 [Epoch 226][Batch 1199], Speed: 357.224 samples/sec, CrossEntropy=2.105, SmoothL1=0.897 [Epoch 226][Batch 1299], Speed: 352.135 samples/sec, CrossEntropy=2.103, SmoothL1=0.895 [Epoch 226][Batch 1399], Speed: 363.588 samples/sec, CrossEntropy=2.101, SmoothL1=0.894 [Epoch 226][Batch 1499], Speed: 349.959 samples/sec, CrossEntropy=2.100, SmoothL1=0.895 [Epoch 226][Batch 1599], Speed: 359.524 samples/sec, CrossEntropy=2.102, SmoothL1=0.897 [Epoch 226][Batch 1699], Speed: 360.946 samples/sec, CrossEntropy=2.105, SmoothL1=0.899 [Epoch 226][Batch 1799], Speed: 354.573 samples/sec, CrossEntropy=2.106, SmoothL1=0.901 [Epoch 226] Training cost: 334.494, CrossEntropy=2.106, SmoothL1=0.900 [Epoch 226] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.416 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.439 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.586 person=34.6 bicycle=17.3 car=20.6 motorcycle=28.0 airplane=45.3 bus=50.9 train=54.6 truck=22.4 boat=11.0 traffic light=8.3 fire hydrant=45.9 stop sign=46.9 parking meter=33.4 bench=13.7 bird=16.0 cat=54.3 dog=47.4 horse=41.8 sheep=33.2 cow=32.2 elephant=47.2 bear=56.8 zebra=48.4 giraffe=49.5 backpack=4.1 umbrella=22.8 handbag=3.5 tie=14.6 suitcase=18.3 frisbee=32.0 skis=11.4 snowboard=11.9 sports ball=18.4 kite=17.5 baseball bat=9.5 baseball glove=13.9 skateboard=27.4 surfboard=18.4 tennis racket=26.3 bottle=13.5 wine glass=13.3 cup=19.0 fork=15.7 knife=5.7 spoon=4.5 bowl=24.8 banana=14.6 apple=9.9 sandwich=28.8 orange=20.2 broccoli=13.0 carrot=10.3 hot dog=23.4 pizza=36.9 donut=27.5 cake=20.7 chair=13.2 couch=34.4 potted plant=12.9 bed=34.2 dining table=20.7 toilet=47.5 tv=42.7 laptop=44.4 mouse=32.8 remote=7.2 keyboard=33.1 cell phone=16.5 microwave=35.6 oven=28.4 toaster=8.5 sink=22.9 refrigerator=38.1 book=4.6 clock=30.2 vase=16.7 scissors=20.3 teddy bear=32.7 hair drier=0.0 toothbrush=7.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 227][Batch 99], Speed: 350.202 samples/sec, CrossEntropy=2.119, SmoothL1=0.905 [Epoch 227][Batch 199], Speed: 350.779 samples/sec, CrossEntropy=2.112, SmoothL1=0.901 [Epoch 227][Batch 299], Speed: 349.262 samples/sec, CrossEntropy=2.111, SmoothL1=0.905 [Epoch 227][Batch 399], Speed: 366.192 samples/sec, CrossEntropy=2.112, SmoothL1=0.907 [Epoch 227][Batch 499], Speed: 359.380 samples/sec, CrossEntropy=2.111, SmoothL1=0.907 [Epoch 227][Batch 599], Speed: 348.657 samples/sec, CrossEntropy=2.100, SmoothL1=0.902 [Epoch 227][Batch 699], Speed: 349.512 samples/sec, CrossEntropy=2.106, SmoothL1=0.907 [Epoch 227][Batch 799], Speed: 361.056 samples/sec, CrossEntropy=2.102, SmoothL1=0.905 [Epoch 227][Batch 899], Speed: 359.702 samples/sec, CrossEntropy=2.105, SmoothL1=0.904 [Epoch 227][Batch 999], Speed: 363.905 samples/sec, CrossEntropy=2.101, SmoothL1=0.902 [Epoch 227][Batch 1099], Speed: 363.027 samples/sec, CrossEntropy=2.102, SmoothL1=0.903 [Epoch 227][Batch 1199], Speed: 364.218 samples/sec, CrossEntropy=2.105, SmoothL1=0.903 [Epoch 227][Batch 1299], Speed: 352.351 samples/sec, CrossEntropy=2.107, SmoothL1=0.905 [Epoch 227][Batch 1399], Speed: 361.054 samples/sec, CrossEntropy=2.109, SmoothL1=0.905 [Epoch 227][Batch 1499], Speed: 361.846 samples/sec, CrossEntropy=2.108, SmoothL1=0.904 [Epoch 227][Batch 1599], Speed: 349.711 samples/sec, CrossEntropy=2.108, SmoothL1=0.903 [Epoch 227][Batch 1699], Speed: 357.674 samples/sec, CrossEntropy=2.111, SmoothL1=0.903 [Epoch 227][Batch 1799], Speed: 352.141 samples/sec, CrossEntropy=2.109, SmoothL1=0.903 [Epoch 227] Training cost: 335.395, CrossEntropy=2.111, SmoothL1=0.903 [Epoch 227] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.260 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.440 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.334 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.348 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.586 person=34.6 bicycle=17.2 car=20.6 motorcycle=27.9 airplane=45.6 bus=51.0 train=54.9 truck=22.3 boat=11.2 traffic light=8.4 fire hydrant=46.1 stop sign=46.4 parking meter=33.0 bench=13.6 bird=15.9 cat=54.6 dog=47.4 horse=41.6 sheep=33.3 cow=31.6 elephant=46.3 bear=55.3 zebra=48.6 giraffe=49.9 backpack=4.0 umbrella=22.5 handbag=3.5 tie=14.6 suitcase=18.0 frisbee=31.8 skis=11.2 snowboard=12.1 sports ball=18.1 kite=17.8 baseball bat=9.8 baseball glove=13.9 skateboard=27.4 surfboard=18.2 tennis racket=26.2 bottle=13.5 wine glass=12.9 cup=18.8 fork=15.7 knife=5.6 spoon=4.8 bowl=24.8 banana=14.7 apple=10.5 sandwich=28.5 orange=20.1 broccoli=12.9 carrot=10.0 hot dog=23.0 pizza=37.2 donut=27.4 cake=20.7 chair=13.0 couch=34.0 potted plant=13.1 bed=33.5 dining table=20.7 toilet=47.2 tv=42.1 laptop=44.4 mouse=33.2 remote=7.0 keyboard=33.2 cell phone=16.4 microwave=36.3 oven=27.4 toaster=10.6 sink=23.1 refrigerator=37.1 book=4.6 clock=30.6 vase=16.6 scissors=19.9 teddy bear=32.3 hair drier=0.0 toothbrush=7.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 228][Batch 99], Speed: 346.375 samples/sec, CrossEntropy=2.072, SmoothL1=0.887 [Epoch 228][Batch 199], Speed: 360.292 samples/sec, CrossEntropy=2.095, SmoothL1=0.889 [Epoch 228][Batch 299], Speed: 354.094 samples/sec, CrossEntropy=2.125, SmoothL1=0.909 [Epoch 228][Batch 399], Speed: 353.131 samples/sec, CrossEntropy=2.117, SmoothL1=0.907 [Epoch 228][Batch 499], Speed: 345.565 samples/sec, CrossEntropy=2.111, SmoothL1=0.903 [Epoch 228][Batch 599], Speed: 342.832 samples/sec, CrossEntropy=2.103, SmoothL1=0.900 [Epoch 228][Batch 699], Speed: 349.595 samples/sec, CrossEntropy=2.100, SmoothL1=0.900 [Epoch 228][Batch 799], Speed: 345.319 samples/sec, CrossEntropy=2.103, SmoothL1=0.901 [Epoch 228][Batch 899], Speed: 358.364 samples/sec, CrossEntropy=2.106, SmoothL1=0.904 [Epoch 228][Batch 999], Speed: 356.001 samples/sec, CrossEntropy=2.107, SmoothL1=0.904 [Epoch 228][Batch 1099], Speed: 354.331 samples/sec, CrossEntropy=2.103, SmoothL1=0.902 [Epoch 228][Batch 1199], Speed: 360.124 samples/sec, CrossEntropy=2.106, SmoothL1=0.905 [Epoch 228][Batch 1299], Speed: 359.042 samples/sec, CrossEntropy=2.106, SmoothL1=0.905 [Epoch 228][Batch 1399], Speed: 352.312 samples/sec, CrossEntropy=2.106, SmoothL1=0.903 [Epoch 228][Batch 1499], Speed: 351.357 samples/sec, CrossEntropy=2.109, SmoothL1=0.904 [Epoch 228][Batch 1599], Speed: 346.865 samples/sec, CrossEntropy=2.108, SmoothL1=0.903 [Epoch 228][Batch 1699], Speed: 365.795 samples/sec, CrossEntropy=2.108, SmoothL1=0.902 [Epoch 228][Batch 1799], Speed: 349.049 samples/sec, CrossEntropy=2.109, SmoothL1=0.903 [Epoch 228] Training cost: 334.842, CrossEntropy=2.109, SmoothL1=0.902 [Epoch 228] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.439 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.581 person=34.5 bicycle=16.9 car=20.5 motorcycle=27.9 airplane=45.9 bus=50.7 train=54.6 truck=22.3 boat=11.3 traffic light=8.5 fire hydrant=45.9 stop sign=46.6 parking meter=32.8 bench=13.6 bird=15.7 cat=54.7 dog=47.5 horse=42.0 sheep=33.2 cow=32.1 elephant=46.5 bear=57.9 zebra=47.9 giraffe=49.8 backpack=4.2 umbrella=22.4 handbag=3.4 tie=14.8 suitcase=18.5 frisbee=32.5 skis=11.4 snowboard=12.4 sports ball=18.1 kite=17.3 baseball bat=9.4 baseball glove=13.8 skateboard=27.2 surfboard=18.3 tennis racket=26.3 bottle=13.2 wine glass=13.1 cup=19.0 fork=15.9 knife=5.5 spoon=4.5 bowl=24.8 banana=14.8 apple=10.2 sandwich=28.9 orange=20.4 broccoli=12.8 carrot=10.4 hot dog=23.1 pizza=36.5 donut=27.4 cake=20.5 chair=13.1 couch=34.6 potted plant=13.0 bed=34.4 dining table=20.6 toilet=47.1 tv=42.3 laptop=43.9 mouse=33.0 remote=7.3 keyboard=33.2 cell phone=16.5 microwave=36.1 oven=28.0 toaster=8.0 sink=23.0 refrigerator=38.5 book=4.7 clock=30.7 vase=16.8 scissors=20.5 teddy bear=31.8 hair drier=0.0 toothbrush=6.4 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 229][Batch 99], Speed: 350.363 samples/sec, CrossEntropy=2.080, SmoothL1=0.883 [Epoch 229][Batch 199], Speed: 351.166 samples/sec, CrossEntropy=2.116, SmoothL1=0.897 [Epoch 229][Batch 299], Speed: 358.168 samples/sec, CrossEntropy=2.107, SmoothL1=0.899 [Epoch 229][Batch 399], Speed: 349.743 samples/sec, CrossEntropy=2.112, SmoothL1=0.902 [Epoch 229][Batch 499], Speed: 346.780 samples/sec, CrossEntropy=2.111, SmoothL1=0.904 [Epoch 229][Batch 599], Speed: 350.998 samples/sec, CrossEntropy=2.113, SmoothL1=0.906 [Epoch 229][Batch 699], Speed: 349.848 samples/sec, CrossEntropy=2.110, SmoothL1=0.903 [Epoch 229][Batch 799], Speed: 346.869 samples/sec, CrossEntropy=2.105, SmoothL1=0.900 [Epoch 229][Batch 899], Speed: 351.145 samples/sec, CrossEntropy=2.107, SmoothL1=0.901 [Epoch 229][Batch 999], Speed: 357.170 samples/sec, CrossEntropy=2.104, SmoothL1=0.896 [Epoch 229][Batch 1099], Speed: 358.900 samples/sec, CrossEntropy=2.102, SmoothL1=0.894 [Epoch 229][Batch 1199], Speed: 349.810 samples/sec, CrossEntropy=2.101, SmoothL1=0.894 [Epoch 229][Batch 1299], Speed: 359.964 samples/sec, CrossEntropy=2.102, SmoothL1=0.895 [Epoch 229][Batch 1399], Speed: 357.227 samples/sec, CrossEntropy=2.101, SmoothL1=0.896 [Epoch 229][Batch 1499], Speed: 347.854 samples/sec, CrossEntropy=2.100, SmoothL1=0.896 [Epoch 229][Batch 1599], Speed: 347.251 samples/sec, CrossEntropy=2.100, SmoothL1=0.896 [Epoch 229][Batch 1699], Speed: 357.879 samples/sec, CrossEntropy=2.101, SmoothL1=0.897 [Epoch 229][Batch 1799], Speed: 355.312 samples/sec, CrossEntropy=2.099, SmoothL1=0.896 [Epoch 229] Training cost: 335.444, CrossEntropy=2.099, SmoothL1=0.896 [Epoch 229] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.438 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.578 person=34.7 bicycle=17.4 car=20.5 motorcycle=27.9 airplane=45.7 bus=51.1 train=55.1 truck=22.1 boat=11.1 traffic light=8.5 fire hydrant=46.3 stop sign=46.9 parking meter=33.2 bench=13.6 bird=16.0 cat=54.3 dog=47.7 horse=42.5 sheep=33.9 cow=32.1 elephant=47.2 bear=58.3 zebra=48.7 giraffe=50.2 backpack=4.1 umbrella=22.8 handbag=3.6 tie=14.7 suitcase=18.2 frisbee=32.5 skis=11.8 snowboard=12.6 sports ball=18.2 kite=17.7 baseball bat=9.7 baseball glove=13.8 skateboard=27.6 surfboard=18.4 tennis racket=26.2 bottle=13.4 wine glass=13.0 cup=19.1 fork=15.8 knife=5.7 spoon=4.8 bowl=24.9 banana=14.6 apple=10.3 sandwich=28.6 orange=20.2 broccoli=13.0 carrot=10.2 hot dog=23.5 pizza=37.2 donut=27.7 cake=20.6 chair=13.1 couch=34.1 potted plant=12.9 bed=34.5 dining table=21.0 toilet=47.1 tv=42.5 laptop=44.4 mouse=33.6 remote=7.5 keyboard=33.3 cell phone=16.5 microwave=36.2 oven=27.3 toaster=7.6 sink=22.7 refrigerator=38.1 book=4.7 clock=30.2 vase=16.8 scissors=19.9 teddy bear=32.2 hair drier=0.0 toothbrush=7.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 230][Batch 99], Speed: 360.123 samples/sec, CrossEntropy=2.117, SmoothL1=0.905 [Epoch 230][Batch 199], Speed: 348.782 samples/sec, CrossEntropy=2.100, SmoothL1=0.893 [Epoch 230][Batch 299], Speed: 353.157 samples/sec, CrossEntropy=2.100, SmoothL1=0.894 [Epoch 230][Batch 399], Speed: 352.768 samples/sec, CrossEntropy=2.095, SmoothL1=0.892 [Epoch 230][Batch 499], Speed: 363.023 samples/sec, CrossEntropy=2.094, SmoothL1=0.890 [Epoch 230][Batch 599], Speed: 343.633 samples/sec, CrossEntropy=2.099, SmoothL1=0.894 [Epoch 230][Batch 699], Speed: 355.945 samples/sec, CrossEntropy=2.105, SmoothL1=0.899 [Epoch 230][Batch 799], Speed: 351.782 samples/sec, CrossEntropy=2.103, SmoothL1=0.899 [Epoch 230][Batch 899], Speed: 361.666 samples/sec, CrossEntropy=2.105, SmoothL1=0.899 [Epoch 230][Batch 999], Speed: 352.677 samples/sec, CrossEntropy=2.104, SmoothL1=0.897 [Epoch 230][Batch 1099], Speed: 357.800 samples/sec, CrossEntropy=2.106, SmoothL1=0.899 [Epoch 230][Batch 1199], Speed: 357.387 samples/sec, CrossEntropy=2.107, SmoothL1=0.898 [Epoch 230][Batch 1299], Speed: 344.097 samples/sec, CrossEntropy=2.109, SmoothL1=0.900 [Epoch 230][Batch 1399], Speed: 357.395 samples/sec, CrossEntropy=2.107, SmoothL1=0.899 [Epoch 230][Batch 1499], Speed: 352.976 samples/sec, CrossEntropy=2.108, SmoothL1=0.900 [Epoch 230][Batch 1599], Speed: 353.297 samples/sec, CrossEntropy=2.108, SmoothL1=0.900 [Epoch 230][Batch 1699], Speed: 360.743 samples/sec, CrossEntropy=2.107, SmoothL1=0.900 [Epoch 230][Batch 1799], Speed: 355.756 samples/sec, CrossEntropy=2.106, SmoothL1=0.900 [Epoch 230] Training cost: 333.901, CrossEntropy=2.107, SmoothL1=0.900 [Epoch 230] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.416 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.442 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.236 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.335 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.348 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.589 person=34.5 bicycle=17.3 car=20.6 motorcycle=28.1 airplane=46.1 bus=51.0 train=54.5 truck=22.3 boat=10.9 traffic light=8.4 fire hydrant=45.8 stop sign=47.2 parking meter=33.2 bench=13.4 bird=16.1 cat=54.3 dog=47.3 horse=41.8 sheep=33.6 cow=31.9 elephant=47.2 bear=56.7 zebra=48.4 giraffe=50.0 backpack=4.1 umbrella=22.6 handbag=3.3 tie=14.6 suitcase=18.4 frisbee=32.3 skis=11.6 snowboard=11.9 sports ball=18.1 kite=17.6 baseball bat=9.7 baseball glove=13.8 skateboard=27.3 surfboard=18.5 tennis racket=26.2 bottle=13.3 wine glass=13.1 cup=18.9 fork=15.7 knife=5.5 spoon=4.9 bowl=25.0 banana=14.8 apple=10.2 sandwich=28.5 orange=19.9 broccoli=13.1 carrot=10.4 hot dog=24.0 pizza=37.2 donut=27.7 cake=20.8 chair=13.1 couch=34.7 potted plant=12.9 bed=34.2 dining table=20.9 toilet=46.8 tv=42.2 laptop=44.2 mouse=33.2 remote=7.2 keyboard=34.0 cell phone=16.6 microwave=36.1 oven=27.1 toaster=10.0 sink=23.2 refrigerator=37.7 book=4.7 clock=30.4 vase=16.7 scissors=20.1 teddy bear=32.3 hair drier=0.0 toothbrush=7.3 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 231][Batch 99], Speed: 359.577 samples/sec, CrossEntropy=2.051, SmoothL1=0.893 [Epoch 231][Batch 199], Speed: 361.410 samples/sec, CrossEntropy=2.078, SmoothL1=0.896 [Epoch 231][Batch 299], Speed: 352.093 samples/sec, CrossEntropy=2.089, SmoothL1=0.901 [Epoch 231][Batch 399], Speed: 359.546 samples/sec, CrossEntropy=2.085, SmoothL1=0.895 [Epoch 231][Batch 499], Speed: 341.535 samples/sec, CrossEntropy=2.095, SmoothL1=0.895 [Epoch 231][Batch 599], Speed: 360.255 samples/sec, CrossEntropy=2.093, SmoothL1=0.891 [Epoch 231][Batch 699], Speed: 357.591 samples/sec, CrossEntropy=2.093, SmoothL1=0.890 [Epoch 231][Batch 799], Speed: 362.615 samples/sec, CrossEntropy=2.098, SmoothL1=0.891 [Epoch 231][Batch 899], Speed: 353.403 samples/sec, CrossEntropy=2.101, SmoothL1=0.892 [Epoch 231][Batch 999], Speed: 360.890 samples/sec, CrossEntropy=2.098, SmoothL1=0.890 [Epoch 231][Batch 1099], Speed: 357.658 samples/sec, CrossEntropy=2.098, SmoothL1=0.891 [Epoch 231][Batch 1199], Speed: 352.905 samples/sec, CrossEntropy=2.100, SmoothL1=0.892 [Epoch 231][Batch 1299], Speed: 361.072 samples/sec, CrossEntropy=2.098, SmoothL1=0.890 [Epoch 231][Batch 1399], Speed: 354.751 samples/sec, CrossEntropy=2.096, SmoothL1=0.890 [Epoch 231][Batch 1499], Speed: 336.904 samples/sec, CrossEntropy=2.097, SmoothL1=0.892 [Epoch 231][Batch 1599], Speed: 351.596 samples/sec, CrossEntropy=2.096, SmoothL1=0.891 [Epoch 231][Batch 1699], Speed: 355.810 samples/sec, CrossEntropy=2.098, SmoothL1=0.892 [Epoch 231][Batch 1799], Speed: 346.968 samples/sec, CrossEntropy=2.099, SmoothL1=0.893 [Epoch 231] Training cost: 335.331, CrossEntropy=2.100, SmoothL1=0.893 [Epoch 231] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.263 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.334 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.577 person=34.6 bicycle=17.2 car=20.6 motorcycle=28.0 airplane=45.4 bus=50.8 train=55.2 truck=22.3 boat=11.3 traffic light=8.5 fire hydrant=46.4 stop sign=47.2 parking meter=33.5 bench=13.7 bird=15.9 cat=54.1 dog=47.4 horse=42.1 sheep=33.6 cow=31.9 elephant=47.3 bear=57.4 zebra=48.7 giraffe=49.4 backpack=4.0 umbrella=22.5 handbag=3.8 tie=14.9 suitcase=18.2 frisbee=32.0 skis=11.2 snowboard=12.5 sports ball=18.2 kite=17.6 baseball bat=9.5 baseball glove=13.9 skateboard=27.6 surfboard=18.7 tennis racket=26.4 bottle=13.2 wine glass=13.2 cup=19.2 fork=15.7 knife=5.6 spoon=4.8 bowl=25.0 banana=14.9 apple=10.3 sandwich=28.3 orange=20.3 broccoli=13.2 carrot=10.4 hot dog=23.0 pizza=37.2 donut=27.5 cake=21.2 chair=13.2 couch=33.9 potted plant=13.1 bed=34.1 dining table=20.3 toilet=47.5 tv=42.8 laptop=43.9 mouse=33.1 remote=7.5 keyboard=33.2 cell phone=16.5 microwave=37.0 oven=27.7 toaster=7.6 sink=23.1 refrigerator=37.7 book=4.8 clock=29.8 vase=16.5 scissors=21.3 teddy bear=32.2 hair drier=0.0 toothbrush=6.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 232][Batch 99], Speed: 353.686 samples/sec, CrossEntropy=2.096, SmoothL1=0.897 [Epoch 232][Batch 199], Speed: 348.501 samples/sec, CrossEntropy=2.126, SmoothL1=0.898 [Epoch 232][Batch 299], Speed: 349.000 samples/sec, CrossEntropy=2.133, SmoothL1=0.904 [Epoch 232][Batch 399], Speed: 361.389 samples/sec, CrossEntropy=2.121, SmoothL1=0.897 [Epoch 232][Batch 499], Speed: 347.127 samples/sec, CrossEntropy=2.123, SmoothL1=0.896 [Epoch 232][Batch 599], Speed: 346.851 samples/sec, CrossEntropy=2.118, SmoothL1=0.895 [Epoch 232][Batch 699], Speed: 353.320 samples/sec, CrossEntropy=2.111, SmoothL1=0.892 [Epoch 232][Batch 799], Speed: 353.448 samples/sec, CrossEntropy=2.111, SmoothL1=0.895 [Epoch 232][Batch 899], Speed: 354.316 samples/sec, CrossEntropy=2.111, SmoothL1=0.898 [Epoch 232][Batch 999], Speed: 343.503 samples/sec, CrossEntropy=2.113, SmoothL1=0.901 [Epoch 232][Batch 1099], Speed: 344.031 samples/sec, CrossEntropy=2.116, SmoothL1=0.901 [Epoch 232][Batch 1199], Speed: 359.633 samples/sec, CrossEntropy=2.116, SmoothL1=0.900 [Epoch 232][Batch 1299], Speed: 349.880 samples/sec, CrossEntropy=2.111, SmoothL1=0.900 [Epoch 232][Batch 1399], Speed: 363.238 samples/sec, CrossEntropy=2.113, SmoothL1=0.903 [Epoch 232][Batch 1499], Speed: 354.032 samples/sec, CrossEntropy=2.114, SmoothL1=0.904 [Epoch 232][Batch 1599], Speed: 358.705 samples/sec, CrossEntropy=2.112, SmoothL1=0.905 [Epoch 232][Batch 1699], Speed: 344.541 samples/sec, CrossEntropy=2.115, SmoothL1=0.905 [Epoch 232][Batch 1799], Speed: 349.897 samples/sec, CrossEntropy=2.112, SmoothL1=0.904 [Epoch 232] Training cost: 335.048, CrossEntropy=2.113, SmoothL1=0.904 [Epoch 232] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.436 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.234 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.584 person=34.7 bicycle=17.3 car=20.7 motorcycle=28.0 airplane=45.5 bus=51.1 train=54.8 truck=22.2 boat=11.3 traffic light=8.4 fire hydrant=46.0 stop sign=47.0 parking meter=32.8 bench=13.3 bird=15.8 cat=54.9 dog=46.9 horse=42.3 sheep=33.3 cow=32.1 elephant=47.0 bear=57.8 zebra=48.6 giraffe=50.1 backpack=4.2 umbrella=22.6 handbag=3.5 tie=14.7 suitcase=18.2 frisbee=32.6 skis=11.4 snowboard=12.1 sports ball=18.2 kite=17.6 baseball bat=9.6 baseball glove=14.0 skateboard=27.3 surfboard=18.4 tennis racket=26.3 bottle=13.2 wine glass=13.2 cup=19.1 fork=15.8 knife=5.5 spoon=4.6 bowl=25.0 banana=14.9 apple=10.1 sandwich=28.4 orange=20.4 broccoli=13.0 carrot=10.5 hot dog=23.6 pizza=36.2 donut=27.3 cake=20.8 chair=13.1 couch=34.0 potted plant=12.9 bed=34.5 dining table=20.5 toilet=46.7 tv=42.6 laptop=43.9 mouse=33.1 remote=7.2 keyboard=32.9 cell phone=16.5 microwave=37.1 oven=27.6 toaster=7.6 sink=23.1 refrigerator=38.4 book=4.8 clock=30.2 vase=16.9 scissors=20.1 teddy bear=32.3 hair drier=0.0 toothbrush=6.8 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 233][Batch 99], Speed: 349.799 samples/sec, CrossEntropy=2.129, SmoothL1=0.900 [Epoch 233][Batch 199], Speed: 359.708 samples/sec, CrossEntropy=2.123, SmoothL1=0.901 [Epoch 233][Batch 299], Speed: 358.499 samples/sec, CrossEntropy=2.123, SmoothL1=0.916 [Epoch 233][Batch 399], Speed: 345.353 samples/sec, CrossEntropy=2.123, SmoothL1=0.917 [Epoch 233][Batch 499], Speed: 355.942 samples/sec, CrossEntropy=2.129, SmoothL1=0.916 [Epoch 233][Batch 599], Speed: 352.425 samples/sec, CrossEntropy=2.129, SmoothL1=0.914 [Epoch 233][Batch 699], Speed: 348.131 samples/sec, CrossEntropy=2.126, SmoothL1=0.912 [Epoch 233][Batch 799], Speed: 354.614 samples/sec, CrossEntropy=2.122, SmoothL1=0.909 [Epoch 233][Batch 899], Speed: 355.210 samples/sec, CrossEntropy=2.118, SmoothL1=0.906 [Epoch 233][Batch 999], Speed: 353.398 samples/sec, CrossEntropy=2.110, SmoothL1=0.901 [Epoch 233][Batch 1099], Speed: 346.746 samples/sec, CrossEntropy=2.109, SmoothL1=0.900 [Epoch 233][Batch 1199], Speed: 345.826 samples/sec, CrossEntropy=2.111, SmoothL1=0.900 [Epoch 233][Batch 1299], Speed: 356.061 samples/sec, CrossEntropy=2.112, SmoothL1=0.901 [Epoch 233][Batch 1399], Speed: 350.718 samples/sec, CrossEntropy=2.114, SmoothL1=0.903 [Epoch 233][Batch 1499], Speed: 353.083 samples/sec, CrossEntropy=2.113, SmoothL1=0.901 [Epoch 233][Batch 1599], Speed: 348.555 samples/sec, CrossEntropy=2.110, SmoothL1=0.901 [Epoch 233][Batch 1699], Speed: 356.121 samples/sec, CrossEntropy=2.110, SmoothL1=0.900 [Epoch 233][Batch 1799], Speed: 345.315 samples/sec, CrossEntropy=2.109, SmoothL1=0.899 [Epoch 233] Training cost: 335.167, CrossEntropy=2.108, SmoothL1=0.898 [Epoch 233] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.416 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.263 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.440 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.582 person=34.6 bicycle=17.2 car=20.6 motorcycle=27.8 airplane=45.8 bus=50.7 train=55.1 truck=22.3 boat=11.2 traffic light=8.3 fire hydrant=46.2 stop sign=46.8 parking meter=33.1 bench=13.7 bird=15.9 cat=54.5 dog=47.3 horse=42.3 sheep=33.1 cow=31.8 elephant=47.6 bear=57.4 zebra=48.4 giraffe=49.4 backpack=4.2 umbrella=23.0 handbag=3.5 tie=14.8 suitcase=17.8 frisbee=31.6 skis=11.2 snowboard=11.6 sports ball=18.2 kite=17.7 baseball bat=9.8 baseball glove=14.0 skateboard=27.9 surfboard=18.6 tennis racket=26.0 bottle=13.3 wine glass=13.3 cup=18.9 fork=16.0 knife=5.4 spoon=4.5 bowl=24.9 banana=14.8 apple=10.4 sandwich=28.8 orange=20.2 broccoli=13.1 carrot=10.4 hot dog=23.5 pizza=37.0 donut=27.7 cake=20.6 chair=13.1 couch=34.3 potted plant=13.2 bed=35.0 dining table=20.6 toilet=47.4 tv=42.6 laptop=44.2 mouse=33.0 remote=7.2 keyboard=34.0 cell phone=16.4 microwave=36.1 oven=28.3 toaster=8.8 sink=22.9 refrigerator=37.9 book=4.8 clock=30.1 vase=16.6 scissors=19.8 teddy bear=31.9 hair drier=0.0 toothbrush=7.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 234][Batch 99], Speed: 358.120 samples/sec, CrossEntropy=2.089, SmoothL1=0.893 [Epoch 234][Batch 199], Speed: 357.244 samples/sec, CrossEntropy=2.094, SmoothL1=0.885 [Epoch 234][Batch 299], Speed: 347.677 samples/sec, CrossEntropy=2.109, SmoothL1=0.891 [Epoch 234][Batch 399], Speed: 351.681 samples/sec, CrossEntropy=2.110, SmoothL1=0.893 [Epoch 234][Batch 499], Speed: 349.283 samples/sec, CrossEntropy=2.098, SmoothL1=0.889 [Epoch 234][Batch 599], Speed: 346.048 samples/sec, CrossEntropy=2.096, SmoothL1=0.887 [Epoch 234][Batch 699], Speed: 352.791 samples/sec, CrossEntropy=2.101, SmoothL1=0.889 [Epoch 234][Batch 799], Speed: 352.642 samples/sec, CrossEntropy=2.095, SmoothL1=0.885 [Epoch 234][Batch 899], Speed: 340.401 samples/sec, CrossEntropy=2.099, SmoothL1=0.889 [Epoch 234][Batch 999], Speed: 352.484 samples/sec, CrossEntropy=2.103, SmoothL1=0.894 [Epoch 234][Batch 1099], Speed: 348.140 samples/sec, CrossEntropy=2.105, SmoothL1=0.895 [Epoch 234][Batch 1199], Speed: 353.680 samples/sec, CrossEntropy=2.103, SmoothL1=0.894 [Epoch 234][Batch 1299], Speed: 357.901 samples/sec, CrossEntropy=2.099, SmoothL1=0.893 [Epoch 234][Batch 1399], Speed: 358.402 samples/sec, CrossEntropy=2.099, SmoothL1=0.897 [Epoch 234][Batch 1499], Speed: 345.878 samples/sec, CrossEntropy=2.098, SmoothL1=0.896 [Epoch 234][Batch 1599], Speed: 351.366 samples/sec, CrossEntropy=2.097, SmoothL1=0.895 [Epoch 234][Batch 1699], Speed: 347.895 samples/sec, CrossEntropy=2.096, SmoothL1=0.893 [Epoch 234][Batch 1799], Speed: 352.213 samples/sec, CrossEntropy=2.096, SmoothL1=0.893 [Epoch 234] Training cost: 334.324, CrossEntropy=2.096, SmoothL1=0.892 [Epoch 234] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.261 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.434 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.233 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.332 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.345 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.579 person=34.5 bicycle=17.4 car=20.5 motorcycle=27.5 airplane=46.1 bus=51.0 train=55.2 truck=22.3 boat=11.5 traffic light=8.5 fire hydrant=46.3 stop sign=46.8 parking meter=32.5 bench=13.4 bird=16.3 cat=55.1 dog=47.3 horse=42.0 sheep=33.4 cow=32.2 elephant=46.6 bear=57.2 zebra=48.8 giraffe=49.5 backpack=4.1 umbrella=22.6 handbag=3.6 tie=14.8 suitcase=18.3 frisbee=32.1 skis=11.3 snowboard=11.9 sports ball=17.8 kite=17.4 baseball bat=10.2 baseball glove=13.8 skateboard=27.4 surfboard=18.7 tennis racket=26.2 bottle=13.3 wine glass=13.3 cup=19.1 fork=15.6 knife=5.6 spoon=4.5 bowl=24.9 banana=14.7 apple=10.0 sandwich=29.2 orange=19.9 broccoli=13.3 carrot=10.4 hot dog=23.3 pizza=36.7 donut=27.4 cake=20.8 chair=13.1 couch=33.9 potted plant=12.9 bed=33.9 dining table=20.7 toilet=46.7 tv=42.4 laptop=44.4 mouse=33.3 remote=7.2 keyboard=33.3 cell phone=16.6 microwave=36.4 oven=27.9 toaster=7.6 sink=23.4 refrigerator=37.7 book=4.7 clock=30.1 vase=16.6 scissors=20.2 teddy bear=32.5 hair drier=0.0 toothbrush=6.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =24.9 [Epoch 235][Batch 99], Speed: 354.601 samples/sec, CrossEntropy=2.104, SmoothL1=0.915 [Epoch 235][Batch 199], Speed: 352.118 samples/sec, CrossEntropy=2.119, SmoothL1=0.922 [Epoch 235][Batch 299], Speed: 351.147 samples/sec, CrossEntropy=2.115, SmoothL1=0.915 [Epoch 235][Batch 399], Speed: 354.448 samples/sec, CrossEntropy=2.096, SmoothL1=0.900 [Epoch 235][Batch 499], Speed: 352.456 samples/sec, CrossEntropy=2.094, SmoothL1=0.899 [Epoch 235][Batch 599], Speed: 354.166 samples/sec, CrossEntropy=2.093, SmoothL1=0.896 [Epoch 235][Batch 699], Speed: 353.641 samples/sec, CrossEntropy=2.099, SmoothL1=0.902 [Epoch 235][Batch 799], Speed: 348.494 samples/sec, CrossEntropy=2.094, SmoothL1=0.900 [Epoch 235][Batch 899], Speed: 354.916 samples/sec, CrossEntropy=2.103, SmoothL1=0.901 [Epoch 235][Batch 999], Speed: 349.857 samples/sec, CrossEntropy=2.102, SmoothL1=0.899 [Epoch 235][Batch 1099], Speed: 350.992 samples/sec, CrossEntropy=2.105, SmoothL1=0.901 [Epoch 235][Batch 1199], Speed: 349.026 samples/sec, CrossEntropy=2.101, SmoothL1=0.898 [Epoch 235][Batch 1299], Speed: 359.030 samples/sec, CrossEntropy=2.100, SmoothL1=0.896 [Epoch 235][Batch 1399], Speed: 350.730 samples/sec, CrossEntropy=2.101, SmoothL1=0.898 [Epoch 235][Batch 1499], Speed: 353.655 samples/sec, CrossEntropy=2.102, SmoothL1=0.899 [Epoch 235][Batch 1599], Speed: 347.394 samples/sec, CrossEntropy=2.102, SmoothL1=0.898 [Epoch 235][Batch 1699], Speed: 347.718 samples/sec, CrossEntropy=2.101, SmoothL1=0.899 [Epoch 235][Batch 1799], Speed: 350.658 samples/sec, CrossEntropy=2.100, SmoothL1=0.897 [Epoch 235] Training cost: 335.958, CrossEntropy=2.099, SmoothL1=0.897 [Epoch 235] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.050 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.440 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.334 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.347 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.583 person=34.7 bicycle=17.3 car=20.6 motorcycle=27.7 airplane=45.6 bus=50.7 train=55.0 truck=22.3 boat=11.1 traffic light=8.5 fire hydrant=46.1 stop sign=47.3 parking meter=33.2 bench=13.5 bird=16.0 cat=54.3 dog=47.1 horse=42.1 sheep=33.6 cow=32.3 elephant=47.5 bear=57.5 zebra=48.3 giraffe=50.3 backpack=4.2 umbrella=22.8 handbag=3.5 tie=15.1 suitcase=18.4 frisbee=31.9 skis=11.7 snowboard=12.7 sports ball=18.0 kite=17.6 baseball bat=9.6 baseball glove=13.9 skateboard=27.4 surfboard=18.5 tennis racket=26.0 bottle=13.4 wine glass=13.1 cup=19.0 fork=15.8 knife=5.5 spoon=4.9 bowl=25.0 banana=15.1 apple=10.2 sandwich=28.5 orange=20.0 broccoli=13.0 carrot=10.3 hot dog=23.4 pizza=37.1 donut=27.5 cake=20.9 chair=13.1 couch=34.3 potted plant=12.7 bed=34.4 dining table=20.9 toilet=47.0 tv=42.3 laptop=44.6 mouse=33.2 remote=7.5 keyboard=33.8 cell phone=16.6 microwave=36.1 oven=28.0 toaster=8.5 sink=23.0 refrigerator=38.4 book=4.6 clock=30.5 vase=16.7 scissors=20.2 teddy bear=31.9 hair drier=0.0 toothbrush=6.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 236][Batch 99], Speed: 352.135 samples/sec, CrossEntropy=2.094, SmoothL1=0.904 [Epoch 236][Batch 199], Speed: 347.355 samples/sec, CrossEntropy=2.085, SmoothL1=0.893 [Epoch 236][Batch 299], Speed: 358.803 samples/sec, CrossEntropy=2.087, SmoothL1=0.897 [Epoch 236][Batch 399], Speed: 361.379 samples/sec, CrossEntropy=2.088, SmoothL1=0.896 [Epoch 236][Batch 499], Speed: 346.807 samples/sec, CrossEntropy=2.083, SmoothL1=0.894 [Epoch 236][Batch 599], Speed: 340.680 samples/sec, CrossEntropy=2.091, SmoothL1=0.897 [Epoch 236][Batch 699], Speed: 342.266 samples/sec, CrossEntropy=2.091, SmoothL1=0.894 [Epoch 236][Batch 799], Speed: 357.263 samples/sec, CrossEntropy=2.096, SmoothL1=0.896 [Epoch 236][Batch 899], Speed: 346.376 samples/sec, CrossEntropy=2.102, SmoothL1=0.899 [Epoch 236][Batch 999], Speed: 356.656 samples/sec, CrossEntropy=2.101, SmoothL1=0.899 [Epoch 236][Batch 1099], Speed: 361.000 samples/sec, CrossEntropy=2.099, SmoothL1=0.899 [Epoch 236][Batch 1199], Speed: 357.031 samples/sec, CrossEntropy=2.099, SmoothL1=0.898 [Epoch 236][Batch 1299], Speed: 354.651 samples/sec, CrossEntropy=2.098, SmoothL1=0.896 [Epoch 236][Batch 1399], Speed: 353.649 samples/sec, CrossEntropy=2.097, SmoothL1=0.895 [Epoch 236][Batch 1499], Speed: 342.765 samples/sec, CrossEntropy=2.099, SmoothL1=0.897 [Epoch 236][Batch 1599], Speed: 357.226 samples/sec, CrossEntropy=2.096, SmoothL1=0.895 [Epoch 236][Batch 1699], Speed: 355.241 samples/sec, CrossEntropy=2.098, SmoothL1=0.895 [Epoch 236][Batch 1799], Speed: 356.761 samples/sec, CrossEntropy=2.098, SmoothL1=0.897 [Epoch 236] Training cost: 334.943, CrossEntropy=2.098, SmoothL1=0.897 [Epoch 236] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.441 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.236 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.335 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.348 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.589 person=34.7 bicycle=17.2 car=20.5 motorcycle=27.8 airplane=45.8 bus=50.7 train=55.2 truck=22.4 boat=11.4 traffic light=8.6 fire hydrant=46.0 stop sign=47.5 parking meter=33.2 bench=13.5 bird=15.9 cat=54.7 dog=47.6 horse=42.4 sheep=33.8 cow=32.2 elephant=47.2 bear=57.2 zebra=48.8 giraffe=49.9 backpack=4.1 umbrella=22.8 handbag=3.6 tie=14.6 suitcase=18.8 frisbee=32.1 skis=11.5 snowboard=11.8 sports ball=17.9 kite=17.4 baseball bat=9.7 baseball glove=13.9 skateboard=27.7 surfboard=18.2 tennis racket=26.3 bottle=13.5 wine glass=13.3 cup=19.1 fork=15.7 knife=5.7 spoon=4.5 bowl=24.7 banana=14.9 apple=10.3 sandwich=28.7 orange=20.1 broccoli=12.9 carrot=10.3 hot dog=23.3 pizza=36.6 donut=27.4 cake=20.6 chair=13.1 couch=33.8 potted plant=12.9 bed=34.8 dining table=20.7 toilet=47.0 tv=42.1 laptop=44.2 mouse=33.1 remote=7.2 keyboard=33.8 cell phone=16.5 microwave=36.6 oven=27.6 toaster=8.7 sink=23.1 refrigerator=39.2 book=4.7 clock=30.2 vase=17.0 scissors=20.4 teddy bear=32.1 hair drier=0.0 toothbrush=7.2 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0 [Epoch 237][Batch 99], Speed: 354.105 samples/sec, CrossEntropy=2.123, SmoothL1=0.912 [Epoch 237][Batch 199], Speed: 350.664 samples/sec, CrossEntropy=2.124, SmoothL1=0.914 [Epoch 237][Batch 299], Speed: 345.896 samples/sec, CrossEntropy=2.121, SmoothL1=0.916 [Epoch 237][Batch 399], Speed: 352.486 samples/sec, CrossEntropy=2.122, SmoothL1=0.910 [Epoch 237][Batch 499], Speed: 353.088 samples/sec, CrossEntropy=2.119, SmoothL1=0.903 [Epoch 237][Batch 599], Speed: 350.384 samples/sec, CrossEntropy=2.118, SmoothL1=0.903 [Epoch 237][Batch 699], Speed: 354.952 samples/sec, CrossEntropy=2.123, SmoothL1=0.906 [Epoch 237][Batch 799], Speed: 349.804 samples/sec, CrossEntropy=2.121, SmoothL1=0.905 [Epoch 237][Batch 899], Speed: 354.420 samples/sec, CrossEntropy=2.122, SmoothL1=0.906 [Epoch 237][Batch 999], Speed: 351.850 samples/sec, CrossEntropy=2.124, SmoothL1=0.904 [Epoch 237][Batch 1099], Speed: 346.592 samples/sec, CrossEntropy=2.125, SmoothL1=0.907 [Epoch 237][Batch 1199], Speed: 357.470 samples/sec, CrossEntropy=2.124, SmoothL1=0.907 [Epoch 237][Batch 1299], Speed: 359.776 samples/sec, CrossEntropy=2.122, SmoothL1=0.907 [Epoch 237][Batch 1399], Speed: 352.284 samples/sec, CrossEntropy=2.120, SmoothL1=0.906 [Epoch 237][Batch 1499], Speed: 362.969 samples/sec, CrossEntropy=2.118, SmoothL1=0.905 [Epoch 237][Batch 1599], Speed: 346.067 samples/sec, CrossEntropy=2.116, SmoothL1=0.906 [Epoch 237][Batch 1699], Speed: 352.022 samples/sec, CrossEntropy=2.117, SmoothL1=0.907 [Epoch 237][Batch 1799], Speed: 354.764 samples/sec, CrossEntropy=2.114, SmoothL1=0.906 [Epoch 237] Training cost: 335.373, CrossEntropy=2.114, SmoothL1=0.906 [Epoch 237] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.251 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.268 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.442 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.236 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.335 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.348 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.382 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.586 person=34.6 bicycle=17.3 car=20.6 motorcycle=28.0 airplane=45.5 bus=50.5 train=54.5 truck=22.3 boat=11.3 traffic light=8.5 fire hydrant=46.1 stop sign=47.3 parking meter=33.8 bench=13.6 bird=16.2 cat=54.4 dog=47.5 horse=42.3 sheep=33.4 cow=32.0 elephant=46.9 bear=56.5 zebra=48.5 giraffe=50.1 backpack=4.0 umbrella=22.9 handbag=3.5 tie=15.0 suitcase=18.5 frisbee=32.0 skis=11.5 snowboard=12.5 sports ball=18.1 kite=17.2 baseball bat=9.8 baseball glove=13.8 skateboard=28.2 surfboard=18.2 tennis racket=26.2 bottle=13.3 wine glass=13.3 cup=19.2 fork=15.8 knife=5.6 spoon=4.7 bowl=25.0 banana=14.9 apple=10.4 sandwich=28.4 orange=20.0 broccoli=13.0 carrot=10.5 hot dog=23.2 pizza=36.9 donut=27.2 cake=21.5 chair=13.2 couch=34.6 potted plant=12.8 bed=33.8 dining table=21.0 toilet=47.1 tv=42.7 laptop=44.6 mouse=33.1 remote=7.7 keyboard=33.1 cell phone=16.5 microwave=36.0 oven=28.1 toaster=9.0 sink=23.4 refrigerator=38.9 book=4.8 clock=30.5 vase=16.6 scissors=20.6 teddy bear=32.0 hair drier=1.5 toothbrush=6.9 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.1 [Epoch 238][Batch 99], Speed: 348.013 samples/sec, CrossEntropy=2.144, SmoothL1=0.893 [Epoch 238][Batch 199], Speed: 347.568 samples/sec, CrossEntropy=2.125, SmoothL1=0.890 [Epoch 238][Batch 299], Speed: 353.632 samples/sec, CrossEntropy=2.110, SmoothL1=0.886 [Epoch 238][Batch 399], Speed: 350.488 samples/sec, CrossEntropy=2.110, SmoothL1=0.891 [Epoch 238][Batch 499], Speed: 347.120 samples/sec, CrossEntropy=2.107, SmoothL1=0.894 [Epoch 238][Batch 599], Speed: 349.014 samples/sec, CrossEntropy=2.094, SmoothL1=0.886 [Epoch 238][Batch 699], Speed: 353.712 samples/sec, CrossEntropy=2.098, SmoothL1=0.887 [Epoch 238][Batch 799], Speed: 352.727 samples/sec, CrossEntropy=2.100, SmoothL1=0.888 [Epoch 238][Batch 899], Speed: 357.307 samples/sec, CrossEntropy=2.101, SmoothL1=0.888 [Epoch 238][Batch 999], Speed: 341.555 samples/sec, CrossEntropy=2.103, SmoothL1=0.892 [Epoch 238][Batch 1099], Speed: 352.646 samples/sec, CrossEntropy=2.100, SmoothL1=0.892 [Epoch 238][Batch 1199], Speed: 344.033 samples/sec, CrossEntropy=2.100, SmoothL1=0.892 [Epoch 238][Batch 1299], Speed: 351.342 samples/sec, CrossEntropy=2.099, SmoothL1=0.894 [Epoch 238][Batch 1399], Speed: 349.573 samples/sec, CrossEntropy=2.096, SmoothL1=0.892 [Epoch 238][Batch 1499], Speed: 349.843 samples/sec, CrossEntropy=2.095, SmoothL1=0.891 [Epoch 238][Batch 1599], Speed: 358.221 samples/sec, CrossEntropy=2.098, SmoothL1=0.894 [Epoch 238][Batch 1699], Speed: 349.367 samples/sec, CrossEntropy=2.100, SmoothL1=0.894 [Epoch 238][Batch 1799], Speed: 351.475 samples/sec, CrossEntropy=2.099, SmoothL1=0.894 [Epoch 238] Training cost: 335.139, CrossEntropy=2.099, SmoothL1=0.894 [Epoch 238] Validation: ~~~~ Summary metrics ~~~~ =Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.416 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.051 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.266 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.444 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.236 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.335 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.348 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.380 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.595 person=34.7 bicycle=17.3 car=20.6 motorcycle=27.9 airplane=45.4 bus=50.4 train=54.7 truck=22.3 boat=11.2 traffic light=8.5 fire hydrant=46.1 stop sign=47.0 parking meter=33.9 bench=13.5 bird=16.2 cat=54.2 dog=47.9 horse=42.6 sheep=33.6 cow=32.2 elephant=47.0 bear=56.9 zebra=48.4 giraffe=50.2 backpack=4.2 umbrella=22.9 handbag=3.7 tie=14.8 suitcase=18.9 frisbee=32.4 skis=11.4 snowboard=12.0 sports ball=18.1 kite=17.3 baseball bat=9.5 baseball glove=13.9 skateboard=27.6 surfboard=18.3 tennis racket=26.2 bottle=13.5 wine glass=12.9 cup=19.1 fork=16.0 knife=5.5 spoon=4.7 bowl=25.1 banana=15.1 apple=10.5 sandwich=27.7 orange=20.4 broccoli=13.0 carrot=10.3 hot dog=23.3 pizza=36.3 donut=27.2 cake=21.1 chair=13.2 couch=34.1 potted plant=12.9 bed=33.6 dining table=20.7 toilet=46.4 tv=42.2 laptop=44.5 mouse=33.1 remote=7.4 keyboard=33.1 cell phone=16.6 microwave=36.5 oven=27.9 toaster=10.7 sink=23.3 refrigerator=38.3 book=4.7 clock=30.0 vase=16.9 scissors=20.7 teddy bear=32.2 hair drier=1.0 toothbrush=7.1 ~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ =25.0