{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "timm installed but torch is required to enable it.\n" ] } ], "source": [ "# 导入相关的包\n", "from autogluon.vision import ObjectDetector" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# 加载数据\n", "dataset_train = ObjectDetector.Dataset.from_voc('train', splits='train')" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "=============================================================================\n", "WARNING: ObjectDetector is deprecated as of v0.4.0 and may contain various bugs and issues!\n", "In a future release ObjectDetector may be entirely reworked to use Torch as a backend.\n", "This future change will likely be API breaking.Users should ensure they update their code that depends on ObjectDetector when upgrading to future AutoGluon releases.\n", "For more information, refer to ObjectDetector refactor GitHub issue: https://github.com/awslabs/autogluon/issues/1559\n", "=============================================================================\n", "\n", "Presets specified: ['good_quality_fast_inference']\n", "The number of requested GPUs is greater than the number of available GPUs.Reduce the number to 4\n", "Randomly split train_data into train[2875]/validation[325] splits.\n", "Starting HPO experiments\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "1e5a2c5d1f114d9bb07a8df0cf2c1682", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/512 [00:00 != ): {\n", "root.dataset_root ~/.mxnet/datasets/ != auto\n", "root.num_workers 4 != 40\n", "root.valid.batch_size 16 != 8\n", "root.train.early_stop_baseline 0.0 != -inf\n", "root.train.early_stop_patience -1 != 20\n", "root.train.batch_size 16 != 8\n", "root.train.lr 0.001 != 0.0001\n", "root.train.epochs 20 != 50\n", "root.train.seed 233 != 721\n", "root.train.early_stop_max_value 1.0 != inf\n", "root.dataset voc_tiny != auto\n", "root.ssd.base_network vgg16_atrous != resnet50_v1\n", "root.ssd.data_shape 300 != 512\n", "}\n", "Saved config to /home/Enderfga/emotion/837f94e2/.trial_0/config.yaml\n", "Using transfer learning from ssd_512_resnet50_v1_coco, the other network parameters are ignored.\n", "Start training from [Epoch 0]\n", "[13:23:46] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)\n", "[Epoch 0][Batch 99], Speed: 0.111306 samples/sec, CrossEntropy=5.785286, SmoothL1=2.330809\n", "[Epoch 0][Batch 199], Speed: 0.193651 samples/sec, CrossEntropy=4.736356, SmoothL1=2.144847\n", "[Epoch 0][Batch 299], Speed: 0.209405 samples/sec, CrossEntropy=4.287700, SmoothL1=2.042503\n", "[Epoch 0] Training cost: 166.715992, CrossEntropy=4.107775, SmoothL1=1.994596\n", "[13:26:32] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)\n", "[Epoch 0] Validation: \n", "heightworker=0.7336105483052194\n", "nobelt=0.2643258006086081\n", "standardbelt=0.006685755538430194\n", "belt=0.2036139672915699\n", "mAP=0.3020590179359569\n", "[Epoch 0] Current best map: 0.302059 vs previous 0.000000, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 1][Batch 99], Speed: 0.129595 samples/sec, CrossEntropy=3.070952, SmoothL1=1.704495\n", "[Epoch 1][Batch 199], Speed: 0.203737 samples/sec, CrossEntropy=3.028967, SmoothL1=1.593077\n", "[Epoch 1][Batch 299], Speed: 0.204442 samples/sec, CrossEntropy=3.003710, SmoothL1=1.616829\n", "[Epoch 1] Training cost: 161.863143, CrossEntropy=2.983484, SmoothL1=1.620375\n", "[Epoch 1] Validation: \n", "heightworker=0.7418484439928016\n", "nobelt=0.3441162256139616\n", "standardbelt=0.007692992143394288\n", "belt=0.31002336533352753\n", "mAP=0.35092025677092126\n", "[Epoch 1] Current best map: 0.350920 vs previous 0.302059, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 2][Batch 99], Speed: 0.120837 samples/sec, CrossEntropy=2.865885, SmoothL1=1.661658\n", "[Epoch 2][Batch 199], Speed: 0.211732 samples/sec, CrossEntropy=2.840469, SmoothL1=1.622037\n", "[Epoch 2][Batch 299], Speed: 0.182566 samples/sec, CrossEntropy=2.801989, SmoothL1=1.589239\n", "[Epoch 2] Training cost: 162.746094, CrossEntropy=2.789041, SmoothL1=1.570847\n", "[Epoch 2] Validation: \n", "heightworker=0.778193670162095\n", "nobelt=0.3642061755424381\n", "standardbelt=0.044640175857766605\n", "belt=0.35081300129143195\n", "mAP=0.38446325571343287\n", "[Epoch 2] Current best map: 0.384463 vs previous 0.350920, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 3][Batch 99], Speed: 0.130522 samples/sec, CrossEntropy=2.695963, SmoothL1=1.551137\n", "[Epoch 3][Batch 199], Speed: 0.199582 samples/sec, CrossEntropy=2.704230, SmoothL1=1.516839\n", "[Epoch 3][Batch 299], Speed: 0.242448 samples/sec, CrossEntropy=2.702854, SmoothL1=1.511845\n", "[Epoch 3] Training cost: 145.867537, CrossEntropy=2.689105, SmoothL1=1.492657\n", "[Epoch 3] Validation: \n", "heightworker=0.8012146887153203\n", "nobelt=0.3472476776020125\n", "standardbelt=0.04390013770942894\n", "belt=0.380808732927913\n", "mAP=0.3932928092386687\n", "[Epoch 3] Current best map: 0.393293 vs previous 0.384463, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 4][Batch 99], Speed: 0.131402 samples/sec, CrossEntropy=2.604468, SmoothL1=1.383709\n", "[Epoch 4][Batch 199], Speed: 0.228963 samples/sec, CrossEntropy=2.572918, SmoothL1=1.327220\n", "[Epoch 4][Batch 299], Speed: 0.207217 samples/sec, CrossEntropy=2.588549, SmoothL1=1.365786\n", "[Epoch 4] Training cost: 154.471757, CrossEntropy=2.596326, SmoothL1=1.368044\n", "[Epoch 4] Validation: \n", "heightworker=0.8153007898740745\n", "nobelt=0.397530452991\n", "standardbelt=0.0346774291976413\n", "belt=0.4439719288496102\n", "mAP=0.4228701502280815\n", "[Epoch 4] Current best map: 0.422870 vs previous 0.393293, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 5][Batch 99], Speed: 0.133645 samples/sec, CrossEntropy=2.560080, SmoothL1=1.431230\n", "[Epoch 5][Batch 199], Speed: 0.167899 samples/sec, CrossEntropy=2.596402, SmoothL1=1.416087\n", "[Epoch 5][Batch 299], Speed: 0.208077 samples/sec, CrossEntropy=2.582214, SmoothL1=1.388991\n", "[Epoch 5] Training cost: 161.687534, CrossEntropy=2.573850, SmoothL1=1.396787\n", "[Epoch 5] Validation: \n", "heightworker=0.8168251246740159\n", "nobelt=0.4120214887708123\n", "standardbelt=0.05543514505209436\n", "belt=0.43520504289892464\n", "mAP=0.4298717003489618\n", "[Epoch 5] Current best map: 0.429872 vs previous 0.422870, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 6][Batch 99], Speed: 0.140785 samples/sec, CrossEntropy=2.504000, SmoothL1=1.346981\n", "[Epoch 6][Batch 199], Speed: 0.183403 samples/sec, CrossEntropy=2.513273, SmoothL1=1.355665\n", "[Epoch 6][Batch 299], Speed: 0.213346 samples/sec, CrossEntropy=2.519178, SmoothL1=1.378116\n", "[Epoch 6] Training cost: 156.194977, CrossEntropy=2.524865, SmoothL1=1.397374\n", "[Epoch 6] Validation: \n", "heightworker=0.8111144898676091\n", "nobelt=0.4177761189237522\n", "standardbelt=0.0816558540044515\n", "belt=0.468562596075895\n", "mAP=0.44477726471792695\n", "[Epoch 6] Current best map: 0.444777 vs previous 0.429872, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 7][Batch 99], Speed: 0.127608 samples/sec, CrossEntropy=2.530280, SmoothL1=1.368845\n", "[Epoch 7][Batch 199], Speed: 0.193268 samples/sec, CrossEntropy=2.505559, SmoothL1=1.373644\n", "[Epoch 7][Batch 299], Speed: 0.197758 samples/sec, CrossEntropy=2.494811, SmoothL1=1.360052\n", "[Epoch 7] Training cost: 160.744063, CrossEntropy=2.485639, SmoothL1=1.347823\n", "[Epoch 7] Validation: \n", "heightworker=0.8192195794638235\n", "nobelt=0.4421149689730257\n", "standardbelt=0.11529156291297059\n", "belt=0.5020142630082145\n", "mAP=0.46966009358950855\n", "[Epoch 7] Current best map: 0.469660 vs previous 0.444777, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 8][Batch 99], Speed: 0.134657 samples/sec, CrossEntropy=2.399760, SmoothL1=1.250288\n", "[Epoch 8][Batch 199], Speed: 0.195988 samples/sec, CrossEntropy=2.427742, SmoothL1=1.284697\n", "[Epoch 8][Batch 299], Speed: 0.232348 samples/sec, CrossEntropy=2.432376, SmoothL1=1.284862\n", "[Epoch 8] Training cost: 148.538998, CrossEntropy=2.441287, SmoothL1=1.285945\n", "[Epoch 8] Validation: \n", "heightworker=0.8195271074889713\n", "nobelt=0.46613481311890015\n", "standardbelt=0.0470993287564478\n", "belt=0.5453643047608764\n", "mAP=0.46953138853129894\n", "[Epoch 9][Batch 99], Speed: 0.130144 samples/sec, CrossEntropy=2.452225, SmoothL1=1.347717\n", "[Epoch 9][Batch 199], Speed: 0.198317 samples/sec, CrossEntropy=2.461100, SmoothL1=1.342007\n", "[Epoch 9][Batch 299], Speed: 0.191133 samples/sec, CrossEntropy=2.452526, SmoothL1=1.330001\n", "[Epoch 9] Training cost: 160.038805, CrossEntropy=2.437692, SmoothL1=1.311254\n", "[Epoch 9] Validation: \n", "heightworker=0.8307026212034507\n", "nobelt=0.47973281593421496\n", "standardbelt=0.07530689030874589\n", "belt=0.5315327876101942\n", "mAP=0.4793187787641514\n", "[Epoch 9] Current best map: 0.479319 vs previous 0.469660, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 10][Batch 99], Speed: 0.138113 samples/sec, CrossEntropy=2.392715, SmoothL1=1.323883\n", "[Epoch 10][Batch 199], Speed: 0.170171 samples/sec, CrossEntropy=2.413586, SmoothL1=1.356117\n", "[Epoch 10][Batch 299], Speed: 0.196867 samples/sec, CrossEntropy=2.383029, SmoothL1=1.307319\n", "[Epoch 10] Training cost: 163.177327, CrossEntropy=2.383317, SmoothL1=1.342184\n", "[Epoch 10] Validation: \n", "heightworker=0.8205852574870038\n", "nobelt=0.48376293230668077\n", "standardbelt=0.13965532674793757\n", "belt=0.5567083961154408\n", "mAP=0.5001779781642658\n", "[Epoch 10] Current best map: 0.500178 vs previous 0.479319, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 11][Batch 99], Speed: 0.111191 samples/sec, CrossEntropy=2.314387, SmoothL1=1.243747\n", "[Epoch 11][Batch 199], Speed: 0.188408 samples/sec, CrossEntropy=2.367837, SmoothL1=1.297442\n", "[Epoch 11][Batch 299], Speed: 0.234535 samples/sec, CrossEntropy=2.355158, SmoothL1=1.269368\n", "[Epoch 11] Training cost: 164.702720, CrossEntropy=2.360374, SmoothL1=1.298052\n", "[Epoch 11] Validation: \n", "heightworker=0.8324083357343061\n", "nobelt=0.467442761583165\n", "standardbelt=0.07618113920037706\n", "belt=0.5521388292165448\n", "mAP=0.4820427664335982\n", "[Epoch 12][Batch 99], Speed: 0.122951 samples/sec, CrossEntropy=2.412235, SmoothL1=1.373362\n", "[Epoch 12][Batch 199], Speed: 0.192758 samples/sec, CrossEntropy=2.388035, SmoothL1=1.350959\n", "[Epoch 12][Batch 299], Speed: 0.185221 samples/sec, CrossEntropy=2.383162, SmoothL1=1.343747\n", "[Epoch 12] Training cost: 161.433658, CrossEntropy=2.374624, SmoothL1=1.335613\n", "[Epoch 12] Validation: \n", "heightworker=0.8302562534860753\n", "nobelt=0.5160616985184809\n", "standardbelt=0.07674098227967256\n", "belt=0.5413070740820932\n", "mAP=0.4910915020915805\n", "[Epoch 13][Batch 99], Speed: 0.117270 samples/sec, CrossEntropy=2.395394, SmoothL1=1.307634\n", "[Epoch 13][Batch 199], Speed: 0.200861 samples/sec, CrossEntropy=2.353836, SmoothL1=1.294273\n", "[Epoch 13][Batch 299], Speed: 0.208207 samples/sec, CrossEntropy=2.343448, SmoothL1=1.312311\n", "[Epoch 13] Training cost: 160.950309, CrossEntropy=2.336454, SmoothL1=1.291991\n", "[Epoch 13] Validation: \n", "heightworker=0.8328424846773973\n", "nobelt=0.5189994616191055\n", "standardbelt=0.1571808281104069\n", "belt=0.58090058743736\n", "mAP=0.5224808404610674\n", "[Epoch 13] Current best map: 0.522481 vs previous 0.500178, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 14][Batch 99], Speed: 0.136590 samples/sec, CrossEntropy=2.290477, SmoothL1=1.229753\n", "[Epoch 14][Batch 199], Speed: 0.173700 samples/sec, CrossEntropy=2.273651, SmoothL1=1.248862\n", "[Epoch 14][Batch 299], Speed: 0.214375 samples/sec, CrossEntropy=2.294085, SmoothL1=1.241578\n", "[Epoch 14] Training cost: 158.105945, CrossEntropy=2.300914, SmoothL1=1.228468\n", "[Epoch 14] Validation: \n", "heightworker=0.8299180224377076\n", "nobelt=0.5345475844997125\n", "standardbelt=0.1588567389808666\n", "belt=0.5781098464996786\n", "mAP=0.5253580481044913\n", "[Epoch 14] Current best map: 0.525358 vs previous 0.522481, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 15][Batch 99], Speed: 0.120220 samples/sec, CrossEntropy=2.308886, SmoothL1=1.229523\n", "[Epoch 15][Batch 199], Speed: 0.195937 samples/sec, CrossEntropy=2.306682, SmoothL1=1.223654\n", "[Epoch 15][Batch 299], Speed: 0.190865 samples/sec, CrossEntropy=2.304577, SmoothL1=1.227018\n", "[Epoch 15] Training cost: 162.032057, CrossEntropy=2.307472, SmoothL1=1.240194\n", "[Epoch 15] Validation: \n", "heightworker=0.8386861827613267\n", "nobelt=0.5047960538239731\n", "standardbelt=0.1928168651052764\n", "belt=0.5898789199296631\n", "mAP=0.5315445054050598\n", "[Epoch 15] Current best map: 0.531545 vs previous 0.525358, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 16][Batch 99], Speed: 0.118009 samples/sec, CrossEntropy=2.269395, SmoothL1=1.332751\n", "[Epoch 16][Batch 199], Speed: 0.190849 samples/sec, CrossEntropy=2.260391, SmoothL1=1.261263\n", "[Epoch 16][Batch 299], Speed: 0.188711 samples/sec, CrossEntropy=2.273936, SmoothL1=1.257886\n", "[Epoch 16] Training cost: 163.626478, CrossEntropy=2.272700, SmoothL1=1.252668\n", "[Epoch 16] Validation: \n", "heightworker=0.8426707121027661\n", "nobelt=0.5247380387366636\n", "standardbelt=0.20249188829250162\n", "belt=0.5980375741175799\n", "mAP=0.5419845533123777\n", "[Epoch 16] Current best map: 0.541985 vs previous 0.531545, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 17][Batch 99], Speed: 0.132020 samples/sec, CrossEntropy=2.253416, SmoothL1=1.277448\n", "[Epoch 17][Batch 199], Speed: 0.187049 samples/sec, CrossEntropy=2.225926, SmoothL1=1.192324\n", "[Epoch 17][Batch 299], Speed: 0.244024 samples/sec, CrossEntropy=2.235220, SmoothL1=1.175977\n", "[Epoch 17] Training cost: 150.437266, CrossEntropy=2.236964, SmoothL1=1.165325\n", "[Epoch 17] Validation: \n", "heightworker=0.8332469041444822\n", "nobelt=0.5223038943045338\n", "standardbelt=0.15864191809345346\n", "belt=0.5783663426588596\n", "mAP=0.5231397648003323\n", "[Epoch 18][Batch 99], Speed: 0.130371 samples/sec, CrossEntropy=2.267700, SmoothL1=1.169474\n", "[Epoch 18][Batch 199], Speed: 0.183697 samples/sec, CrossEntropy=2.242484, SmoothL1=1.147458\n", "[Epoch 18][Batch 299], Speed: 0.210538 samples/sec, CrossEntropy=2.239529, SmoothL1=1.167423\n", "[Epoch 18] Training cost: 158.759453, CrossEntropy=2.233903, SmoothL1=1.169870\n", "[Epoch 18] Validation: \n", "heightworker=0.8299016598218265\n", "nobelt=0.5236527514288329\n", "standardbelt=0.14481775148225476\n", "belt=0.5955027666774394\n", "mAP=0.5234687323525884\n", "[Epoch 19][Batch 99], Speed: 0.134330 samples/sec, CrossEntropy=2.205569, SmoothL1=1.200661\n", "[Epoch 19][Batch 199], Speed: 0.179288 samples/sec, CrossEntropy=2.241840, SmoothL1=1.197243\n", "[Epoch 19][Batch 299], Speed: 0.226818 samples/sec, CrossEntropy=2.246659, SmoothL1=1.219642\n", "[Epoch 19] Training cost: 150.017984, CrossEntropy=2.232562, SmoothL1=1.197472\n", "[Epoch 19] Validation: \n", "heightworker=0.8257076607488559\n", "nobelt=0.5326734317034764\n", "standardbelt=0.2060632978602272\n", "belt=0.5844529972738532\n", "mAP=0.5372243468966031\n", "[Epoch 20][Batch 99], Speed: 0.149686 samples/sec, CrossEntropy=2.208409, SmoothL1=1.106796\n", "[Epoch 20][Batch 199], Speed: 0.193756 samples/sec, CrossEntropy=2.227868, SmoothL1=1.151793\n", "[Epoch 20][Batch 299], Speed: 0.207842 samples/sec, CrossEntropy=2.210743, SmoothL1=1.139681\n", "[Epoch 20] Training cost: 148.765540, CrossEntropy=2.221418, SmoothL1=1.155381\n", "[Epoch 20] Validation: \n", "heightworker=0.8478520151890593\n", "nobelt=0.5292945588180082\n", "standardbelt=0.17825901933957472\n", "belt=0.6112443311431587\n", "mAP=0.5416624811224502\n", "[Epoch 21][Batch 99], Speed: 0.122134 samples/sec, CrossEntropy=2.217795, SmoothL1=1.176061\n", "[Epoch 21][Batch 199], Speed: 0.195547 samples/sec, CrossEntropy=2.200070, SmoothL1=1.182949\n", "[Epoch 21][Batch 299], Speed: 0.219407 samples/sec, CrossEntropy=2.190032, SmoothL1=1.157252\n", "[Epoch 21] Training cost: 158.059703, CrossEntropy=2.198478, SmoothL1=1.164325\n", "[Epoch 21] Validation: \n", "heightworker=0.8470359177219842\n", "nobelt=0.5298597565016704\n", "standardbelt=0.18415902852069255\n", "belt=0.626902424099994\n", "mAP=0.5469892817110853\n", "[Epoch 21] Current best map: 0.546989 vs previous 0.541985, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 22][Batch 99], Speed: 0.130623 samples/sec, CrossEntropy=2.138289, SmoothL1=1.130281\n", "[Epoch 22][Batch 199], Speed: 0.161787 samples/sec, CrossEntropy=2.183021, SmoothL1=1.180491\n", "[Epoch 22][Batch 299], Speed: 0.164881 samples/sec, CrossEntropy=2.192276, SmoothL1=1.209359\n", "[Epoch 22] Training cost: 170.830048, CrossEntropy=2.185847, SmoothL1=1.183705\n", "[Epoch 22] Validation: \n", "heightworker=0.841519755825001\n", "nobelt=0.5251123865051537\n", "standardbelt=0.22596159886882652\n", "belt=0.6179456152813744\n", "mAP=0.5526348391200889\n", "[Epoch 22] Current best map: 0.552635 vs previous 0.546989, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 23][Batch 99], Speed: 0.102644 samples/sec, CrossEntropy=2.230603, SmoothL1=1.222950\n", "[Epoch 23][Batch 199], Speed: 0.185764 samples/sec, CrossEntropy=2.220845, SmoothL1=1.274662\n", "[Epoch 23][Batch 299], Speed: 0.188303 samples/sec, CrossEntropy=2.193851, SmoothL1=1.211441\n", "[Epoch 23] Training cost: 175.472680, CrossEntropy=2.195441, SmoothL1=1.223051\n", "[Epoch 23] Validation: \n", "heightworker=0.8339065333525041\n", "nobelt=0.4992794975429385\n", "standardbelt=0.2313434431302071\n", "belt=0.5671488733833019\n", "mAP=0.5329195868522378\n", "[Epoch 24][Batch 99], Speed: 0.119638 samples/sec, CrossEntropy=2.194728, SmoothL1=1.210847\n", "[Epoch 24][Batch 199], Speed: 0.176132 samples/sec, CrossEntropy=2.210927, SmoothL1=1.216788\n", "[Epoch 24][Batch 299], Speed: 0.181535 samples/sec, CrossEntropy=2.177979, SmoothL1=1.169643\n", "[Epoch 24] Training cost: 172.706517, CrossEntropy=2.170936, SmoothL1=1.163919\n", "[Epoch 24] Validation: \n", "heightworker=0.8326718818201262\n", "nobelt=0.5588154243916758\n", "standardbelt=0.23037307264073828\n", "belt=0.5928999182505316\n", "mAP=0.5536900742757679\n", "[Epoch 24] Current best map: 0.553690 vs previous 0.552635, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 25][Batch 99], Speed: 0.108486 samples/sec, CrossEntropy=2.196277, SmoothL1=1.274813\n", "[Epoch 25][Batch 199], Speed: 0.180358 samples/sec, CrossEntropy=2.175340, SmoothL1=1.241473\n", "[Epoch 25][Batch 299], Speed: 0.214842 samples/sec, CrossEntropy=2.182210, SmoothL1=1.222219\n", "[Epoch 25] Training cost: 168.531043, CrossEntropy=2.180254, SmoothL1=1.203968\n", "[Epoch 25] Validation: \n", "heightworker=0.8350033087162921\n", "nobelt=0.5143033390897945\n", "standardbelt=0.2688450815574306\n", "belt=0.607390220471075\n", "mAP=0.556385487458648\n", "[Epoch 25] Current best map: 0.556385 vs previous 0.553690, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 26][Batch 99], Speed: 0.128068 samples/sec, CrossEntropy=2.177830, SmoothL1=1.154046\n", "[Epoch 26][Batch 199], Speed: 0.190253 samples/sec, CrossEntropy=2.159799, SmoothL1=1.129294\n", "[Epoch 26][Batch 299], Speed: 0.171054 samples/sec, CrossEntropy=2.168456, SmoothL1=1.139574\n", "[Epoch 26] Training cost: 168.438067, CrossEntropy=2.174098, SmoothL1=1.156559\n", "[Epoch 26] Validation: \n", "heightworker=0.8292477229350562\n", "nobelt=0.5469848934076519\n", "standardbelt=0.19140571459645908\n", "belt=0.5996889016789593\n", "mAP=0.5418318081545317\n", "[Epoch 27][Batch 99], Speed: 0.129730 samples/sec, CrossEntropy=2.110300, SmoothL1=1.060703\n", "[Epoch 27][Batch 199], Speed: 0.200323 samples/sec, CrossEntropy=2.159471, SmoothL1=1.115933\n", "[Epoch 27][Batch 299], Speed: 0.172993 samples/sec, CrossEntropy=2.138171, SmoothL1=1.125784\n", "[Epoch 27] Training cost: 159.562064, CrossEntropy=2.144340, SmoothL1=1.142494\n", "[Epoch 27] Validation: \n", "heightworker=0.8425143879166308\n", "nobelt=0.5298139066347352\n", "standardbelt=0.18680899386668004\n", "belt=0.5990052052662941\n", "mAP=0.5395356234210851\n", "[Epoch 28][Batch 99], Speed: 0.123988 samples/sec, CrossEntropy=2.121229, SmoothL1=1.167856\n", "[Epoch 28][Batch 199], Speed: 0.190924 samples/sec, CrossEntropy=2.094521, SmoothL1=1.096108\n", "[Epoch 28][Batch 299], Speed: 0.209199 samples/sec, CrossEntropy=2.118604, SmoothL1=1.122503\n", "[Epoch 28] Training cost: 172.712696, CrossEntropy=2.129358, SmoothL1=1.119792\n", "[Epoch 28] Validation: \n", "heightworker=0.8436063699611236\n", "nobelt=0.5766860092361211\n", "standardbelt=0.2626299497904274\n", "belt=0.661018404768606\n", "mAP=0.5859851834390695\n", "[Epoch 28] Current best map: 0.585985 vs previous 0.556385, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 29][Batch 99], Speed: 0.114177 samples/sec, CrossEntropy=2.139752, SmoothL1=1.136636\n", "[Epoch 29][Batch 199], Speed: 0.181515 samples/sec, CrossEntropy=2.116380, SmoothL1=1.102540\n", "[Epoch 29][Batch 299], Speed: 0.195880 samples/sec, CrossEntropy=2.115896, SmoothL1=1.111862\n", "[Epoch 29] Training cost: 174.685872, CrossEntropy=2.119284, SmoothL1=1.122195\n", "[Epoch 29] Validation: \n", "heightworker=0.836571559057371\n", "nobelt=0.5507019245120308\n", "standardbelt=0.2143896787064658\n", "belt=0.6388854212272486\n", "mAP=0.5601371458757791\n", "[Epoch 30][Batch 99], Speed: 0.125268 samples/sec, CrossEntropy=2.112626, SmoothL1=1.145603\n", "[Epoch 30][Batch 199], Speed: 0.150279 samples/sec, CrossEntropy=2.117757, SmoothL1=1.144765\n", "[Epoch 30][Batch 299], Speed: 0.168934 samples/sec, CrossEntropy=2.104447, SmoothL1=1.115576\n", "[Epoch 30] Training cost: 178.486867, CrossEntropy=2.095483, SmoothL1=1.109897\n", "[Epoch 30] Validation: \n", "heightworker=0.8451710616115378\n", "nobelt=0.5563404925943641\n", "standardbelt=0.2525627321792033\n", "belt=0.6260348673559842\n", "mAP=0.5700272884352723\n", "[Epoch 31][Batch 99], Speed: 0.123333 samples/sec, CrossEntropy=2.083433, SmoothL1=1.077566\n", "[Epoch 31][Batch 199], Speed: 0.176567 samples/sec, CrossEntropy=2.105111, SmoothL1=1.091563\n", "[Epoch 31][Batch 299], Speed: 0.206513 samples/sec, CrossEntropy=2.123615, SmoothL1=1.119905\n", "[Epoch 31] Training cost: 165.294859, CrossEntropy=2.121371, SmoothL1=1.105606\n", "[Epoch 31] Validation: \n", "heightworker=0.8454498470718984\n", "nobelt=0.5430623899965673\n", "standardbelt=0.24706625438247717\n", "belt=0.6196797215391365\n", "mAP=0.5638145532475198\n", "[Epoch 32][Batch 99], Speed: 0.114596 samples/sec, CrossEntropy=2.128087, SmoothL1=1.084204\n", "[Epoch 32][Batch 199], Speed: 0.194815 samples/sec, CrossEntropy=2.126884, SmoothL1=1.136026\n", "[Epoch 32][Batch 299], Speed: 0.198864 samples/sec, CrossEntropy=2.111101, SmoothL1=1.126218\n", "[Epoch 32] Training cost: 165.464765, CrossEntropy=2.107689, SmoothL1=1.117144\n", "[Epoch 32] Validation: \n", "heightworker=0.8425383210560027\n", "nobelt=0.555164757130567\n", "standardbelt=0.2723534864600695\n", "belt=0.601204657701663\n", "mAP=0.5678153055870755\n", "[Epoch 33][Batch 99], Speed: 0.129185 samples/sec, CrossEntropy=2.056934, SmoothL1=1.022372\n", "[Epoch 33][Batch 199], Speed: 0.176127 samples/sec, CrossEntropy=2.053895, SmoothL1=1.033461\n", "[Epoch 33][Batch 299], Speed: 0.216028 samples/sec, CrossEntropy=2.061051, SmoothL1=1.059077\n", "[Epoch 33] Training cost: 159.030589, CrossEntropy=2.067143, SmoothL1=1.063118\n", "[Epoch 33] Validation: \n", "heightworker=0.8304356382558891\n", "nobelt=0.5223173134007598\n", "standardbelt=0.2512974127346652\n", "belt=0.6035803411053048\n", "mAP=0.5519076763741547\n", "[Epoch 34][Batch 99], Speed: 0.112204 samples/sec, CrossEntropy=2.029974, SmoothL1=1.033859\n", "[Epoch 34][Batch 199], Speed: 0.169891 samples/sec, CrossEntropy=2.078218, SmoothL1=1.074919\n", "[Epoch 34][Batch 299], Speed: 0.203701 samples/sec, CrossEntropy=2.082458, SmoothL1=1.123983\n", "[Epoch 34] Training cost: 171.656600, CrossEntropy=2.076770, SmoothL1=1.107024\n", "[Epoch 34] Validation: \n", "heightworker=0.8249268543083346\n", "nobelt=0.5650753459878004\n", "standardbelt=0.25397660009856127\n", "belt=0.6325011698675413\n", "mAP=0.5691199925655595\n", "[Epoch 35][Batch 99], Speed: 0.115694 samples/sec, CrossEntropy=2.084293, SmoothL1=1.164426\n", "[Epoch 35][Batch 199], Speed: 0.186077 samples/sec, CrossEntropy=2.085703, SmoothL1=1.117537\n", "[Epoch 35][Batch 299], Speed: 0.209047 samples/sec, CrossEntropy=2.082955, SmoothL1=1.127046\n", "[Epoch 35] Training cost: 168.081582, CrossEntropy=2.069576, SmoothL1=1.100504\n", "[Epoch 35] Validation: \n", "heightworker=0.8266157666139474\n", "nobelt=0.5233265633970978\n", "standardbelt=0.23582898627617052\n", "belt=0.6320290884765238\n", "mAP=0.5544501011909349\n", "[Epoch 36][Batch 99], Speed: 0.130448 samples/sec, CrossEntropy=1.971211, SmoothL1=0.995878\n", "[Epoch 36][Batch 199], Speed: 0.205601 samples/sec, CrossEntropy=2.039139, SmoothL1=1.064553\n", "[Epoch 36][Batch 299], Speed: 0.186071 samples/sec, CrossEntropy=2.027545, SmoothL1=1.055791\n", "[Epoch 36] Training cost: 157.152851, CrossEntropy=2.023051, SmoothL1=1.047413\n", "[Epoch 36] Validation: \n", "heightworker=0.8306595319641845\n", "nobelt=0.5306331553869549\n", "standardbelt=0.2027979568847782\n", "belt=0.6515338546637299\n", "mAP=0.5539061247249119\n", "[Epoch 37][Batch 99], Speed: 0.124447 samples/sec, CrossEntropy=2.007164, SmoothL1=1.001850\n", "[Epoch 37][Batch 199], Speed: 0.178682 samples/sec, CrossEntropy=2.022967, SmoothL1=1.047651\n", "[Epoch 37][Batch 299], Speed: 0.192772 samples/sec, CrossEntropy=2.028888, SmoothL1=1.052221\n", "[Epoch 37] Training cost: 169.782362, CrossEntropy=2.041812, SmoothL1=1.065085\n", "[Epoch 37] Validation: \n", "heightworker=0.8347044518145792\n", "nobelt=0.5596088479641403\n", "standardbelt=0.24879218585020932\n", "belt=0.6555069387675938\n", "mAP=0.5746531060991307\n", "[Epoch 38][Batch 99], Speed: 0.123775 samples/sec, CrossEntropy=1.989004, SmoothL1=1.000430\n", "[Epoch 38][Batch 199], Speed: 0.181663 samples/sec, CrossEntropy=2.021585, SmoothL1=1.000357\n", "[Epoch 38][Batch 299], Speed: 0.194566 samples/sec, CrossEntropy=2.040062, SmoothL1=1.035534\n", "[Epoch 38] Training cost: 166.586843, CrossEntropy=2.034828, SmoothL1=1.041980\n", "[Epoch 38] Validation: \n", "heightworker=0.8367205153225289\n", "nobelt=0.5422950486775294\n", "standardbelt=0.26677706110242216\n", "belt=0.6373378150038304\n", "mAP=0.5707826100265777\n", "[Epoch 39][Batch 99], Speed: 0.131784 samples/sec, CrossEntropy=2.063358, SmoothL1=1.020546\n", "[Epoch 39][Batch 199], Speed: 0.172072 samples/sec, CrossEntropy=2.032843, SmoothL1=1.033687\n", "[Epoch 39][Batch 299], Speed: 0.191196 samples/sec, CrossEntropy=2.028218, SmoothL1=1.023613\n", "[Epoch 39] Training cost: 169.738786, CrossEntropy=2.020836, SmoothL1=1.024840\n", "[Epoch 39] Validation: \n", "heightworker=0.8465403976533026\n", "nobelt=0.5533686096981176\n", "standardbelt=0.2174141338230042\n", "belt=0.65881339780444\n", "mAP=0.5690341347447161\n", "[Epoch 40][Batch 99], Speed: 0.121696 samples/sec, CrossEntropy=1.982058, SmoothL1=1.044105\n", "[Epoch 40][Batch 199], Speed: 0.197264 samples/sec, CrossEntropy=1.990847, SmoothL1=1.023124\n", "[Epoch 40][Batch 299], Speed: 0.176589 samples/sec, CrossEntropy=2.004517, SmoothL1=1.038447\n", "[Epoch 40] Training cost: 167.678280, CrossEntropy=2.013765, SmoothL1=1.042237\n", "[Epoch 40] Validation: \n", "heightworker=0.8188207815982701\n", "nobelt=0.5792342764365814\n", "standardbelt=0.2259469196778312\n", "belt=0.6379044323502115\n", "mAP=0.5654766025157235\n", "[Epoch 41][Batch 99], Speed: 0.134451 samples/sec, CrossEntropy=2.017664, SmoothL1=1.073149\n", "[Epoch 41][Batch 199], Speed: 0.176754 samples/sec, CrossEntropy=2.028189, SmoothL1=1.126002\n", "[Epoch 41][Batch 299], Speed: 0.210433 samples/sec, CrossEntropy=2.021274, SmoothL1=1.089973\n", "[Epoch 41] Training cost: 154.355847, CrossEntropy=2.016715, SmoothL1=1.077170\n", "[Epoch 41] Validation: \n", "heightworker=0.841789560740314\n", "nobelt=0.5930611389113571\n", "standardbelt=0.20707890010515345\n", "belt=0.6672034838774383\n", "mAP=0.5772832709085658\n", "[Epoch 42][Batch 99], Speed: 0.129321 samples/sec, CrossEntropy=2.001544, SmoothL1=1.060866\n", "[Epoch 42][Batch 199], Speed: 0.196420 samples/sec, CrossEntropy=2.009353, SmoothL1=1.056488\n", "[Epoch 42][Batch 299], Speed: 0.179910 samples/sec, CrossEntropy=2.006856, SmoothL1=1.046012\n", "[Epoch 42] Training cost: 159.673826, CrossEntropy=2.008407, SmoothL1=1.048347\n", "[Epoch 42] Validation: \n", "heightworker=0.8510464530846769\n", "nobelt=0.5725043386341137\n", "standardbelt=0.2814955308508302\n", "belt=0.6506681188720401\n", "mAP=0.5889286103604152\n", "[Epoch 42] Current best map: 0.588929 vs previous 0.585985, saved to /home/Enderfga/emotion/837f94e2/.trial_0/best_checkpoint.pkl\n", "[Epoch 43][Batch 99], Speed: 0.112349 samples/sec, CrossEntropy=2.021055, SmoothL1=1.050659\n", "[Epoch 43][Batch 199], Speed: 0.202119 samples/sec, CrossEntropy=1.968687, SmoothL1=1.004695\n", "[Epoch 43][Batch 299], Speed: 0.191252 samples/sec, CrossEntropy=1.977109, SmoothL1=1.014494\n", "[Epoch 43] Training cost: 164.168938, CrossEntropy=1.966631, SmoothL1=1.006323\n", "[Epoch 43] Validation: \n", "heightworker=0.8432437569012604\n", "nobelt=0.5795248335547055\n", "standardbelt=0.2385414120401484\n", "belt=0.6160674802006546\n", "mAP=0.5693443706741922\n", "[Epoch 44][Batch 99], Speed: 0.131469 samples/sec, CrossEntropy=1.898763, SmoothL1=0.931305\n", "[Epoch 44][Batch 199], Speed: 0.215613 samples/sec, CrossEntropy=1.893369, SmoothL1=0.953186\n", "[Epoch 44][Batch 299], Speed: 0.229503 samples/sec, CrossEntropy=1.917714, SmoothL1=0.978616\n", "[Epoch 44] Training cost: 144.536649, CrossEntropy=1.928804, SmoothL1=0.988270\n", "[Epoch 44] Validation: \n", "heightworker=0.8526037353707543\n", "nobelt=0.5696558833824661\n", "standardbelt=0.21237880309777263\n", "belt=0.6472803756287198\n", "mAP=0.5704796993699282\n", "[Epoch 45][Batch 99], Speed: 0.131603 samples/sec, CrossEntropy=1.919390, SmoothL1=1.001440\n", "[Epoch 45][Batch 199], Speed: 0.209018 samples/sec, CrossEntropy=1.914812, SmoothL1=0.987075\n", "[Epoch 45][Batch 299], Speed: 0.213170 samples/sec, CrossEntropy=1.922292, SmoothL1=0.961816\n", "[Epoch 45] Training cost: 154.180059, CrossEntropy=1.934709, SmoothL1=0.971509\n", "[Epoch 45] Validation: \n", "heightworker=0.843780573450042\n", "nobelt=0.5737630280521158\n", "standardbelt=0.25663415615332735\n", "belt=0.6524851512685217\n", "mAP=0.5816657272310017\n", "[Epoch 46][Batch 99], Speed: 0.126491 samples/sec, CrossEntropy=1.968253, SmoothL1=1.001633\n", "[Epoch 46][Batch 199], Speed: 0.198232 samples/sec, CrossEntropy=1.959303, SmoothL1=0.977345\n", "[Epoch 46][Batch 299], Speed: 0.221459 samples/sec, CrossEntropy=1.955996, SmoothL1=0.977143\n", "[Epoch 46] Training cost: 154.386925, CrossEntropy=1.955834, SmoothL1=0.975623\n", "[Epoch 46] Validation: \n", "heightworker=0.8586684416458265\n", "nobelt=0.5778613834481572\n", "standardbelt=0.23673396813591938\n", "belt=0.6774493611521375\n", "mAP=0.5876782885955101\n", "[Epoch 47][Batch 99], Speed: 0.131877 samples/sec, CrossEntropy=1.924224, SmoothL1=1.017108\n", "[Epoch 47][Batch 199], Speed: 0.208372 samples/sec, CrossEntropy=1.901115, SmoothL1=0.975608\n", "[Epoch 47][Batch 299], Speed: 0.193503 samples/sec, CrossEntropy=1.920918, SmoothL1=0.984684\n", "[Epoch 47] Training cost: 152.632604, CrossEntropy=1.934879, SmoothL1=0.983263\n", "[Epoch 47] Validation: \n", "heightworker=0.8526240439996454\n", "nobelt=0.571398052532826\n", "standardbelt=0.2763700946428856\n", "belt=0.6457010776482792\n", "mAP=0.586523317205909\n", "[Epoch 48][Batch 99], Speed: 0.136915 samples/sec, CrossEntropy=1.945685, SmoothL1=1.008107\n", "[Epoch 48][Batch 199], Speed: 0.176507 samples/sec, CrossEntropy=1.960009, SmoothL1=0.983261\n", "[Epoch 48][Batch 299], Speed: 0.214841 samples/sec, CrossEntropy=1.951627, SmoothL1=0.989833\n", "[Epoch 48] Training cost: 152.848697, CrossEntropy=1.967023, SmoothL1=1.000666\n", "[Epoch 48] Validation: \n", "heightworker=0.8417318396769218\n", "nobelt=0.5306525754294658\n", "standardbelt=0.2895005919674694\n", "belt=0.6432529603947285\n", "mAP=0.5762844918671464\n", "[Epoch 49][Batch 99], Speed: 0.108227 samples/sec, CrossEntropy=1.909769, SmoothL1=0.983960\n", "[Epoch 49][Batch 199], Speed: 0.172738 samples/sec, CrossEntropy=1.970051, SmoothL1=1.037901\n", "[Epoch 49][Batch 299], Speed: 0.171082 samples/sec, CrossEntropy=1.955805, SmoothL1=1.027667\n", "[Epoch 49] Training cost: 178.957119, CrossEntropy=1.954463, SmoothL1=1.023570\n", "[Epoch 49] Validation: \n", "heightworker=0.8329835869549723\n", "nobelt=0.5654899403902274\n", "standardbelt=0.27781422275853934\n", "belt=0.6568063694580729\n", "mAP=0.583273529890453\n", "Applying the state from the best checkpoint...\n", "\tStopping HPO to satisfy time limit...\n", "Saving Training Curve in checkpoint/plot_training_curves.png\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "Finished, total runtime is 8376.84 s\n", "{ 'best_config': { 'dataset': 'auto',\n", " 'dataset_root': 'auto',\n", " 'estimator': ,\n", " 'gpus': [0, 1, 2, 3],\n", " 'horovod': False,\n", " 'num_workers': 40,\n", " 'resume': '',\n", " 'save_interval': 1,\n", " 'ssd': { 'amp': False,\n", " 'base_network': 'resnet50_v1',\n", " 'data_shape': 512,\n", " 'filters': None,\n", " 'nms_thresh': 0.45,\n", " 'nms_topk': 400,\n", " 'ratios': ( [1, 2, 0.5],\n", " [1, 2, 0.5, 3, 0.3333333333333333],\n", " [1, 2, 0.5, 3, 0.3333333333333333],\n", " [1, 2, 0.5, 3, 0.3333333333333333],\n", " [1, 2, 0.5],\n", " [1, 2, 0.5]),\n", " 'sizes': (30, 60, 111, 162, 213, 264, 315),\n", " 'steps': (8, 16, 32, 64, 100, 300),\n", " 'syncbn': False,\n", " 'transfer': 'ssd_512_resnet50_v1_coco'},\n", " 'train': { 'batch_size': 8,\n", " 'dali': False,\n", " 'early_stop_baseline': -inf,\n", " 'early_stop_max_value': inf,\n", " 'early_stop_min_delta': 0.001,\n", " 'early_stop_patience': 20,\n", " 'epochs': 50,\n", " 'log_interval': 100,\n", " 'lr': 0.0001,\n", " 'lr_decay': 0.1,\n", " 'lr_decay_epoch': (160, 200),\n", " 'momentum': 0.9,\n", " 'seed': 721,\n", " 'start_epoch': 0,\n", " 'wd': 0.0005},\n", " 'valid': { 'batch_size': 8,\n", " 'iou_thresh': 0.5,\n", " 'metric': 'voc07',\n", " 'val_interval': 1}},\n", " 'total_time': 8376.586211204529,\n", " 'train_map': 0.6989020544515637,\n", " 'valid_map': 0.5889286103604152}\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 训练模型\n", "time_limit = 60*60*4 # at most 4 hour\n", "detector = ObjectDetector()\n", "detector.fit(dataset_train, time_limit=time_limit, presets='good_quality_fast_inference')" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# 保存模型\n", "savefile = 'detector2.ag'\n", "detector.save(savefile)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/Enderfga/data1/anaconda3/envs/nlp/lib/python3.7/site-packages/mxnet/gluon/block.py:1512: UserWarning: Cannot decide type for the following arguments. Consider providing them as input:\n", "\tdata: None\n", " input_sym_arg_type = in_param.infer_type()[0]\n" ] } ], "source": [ "# 加载模型\n", "new_detector = ObjectDetector.load('/home/Enderfga/emotion/detector2.ag',verbosity=0)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[21:11:01] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)\n", "[21:11:27] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)\n", "[21:11:58] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)\n", "[21:12:16] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)\n", "[21:12:33] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)\n", "[21:12:49] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)\n", "[21:13:30] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)\n", "[21:13:48] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " predict_class predict_score \\\n", "0 heightworker 0.700292 \n", "1 heightworker 0.672959 \n", "2 heightworker 0.643593 \n", "3 heightworker 0.350276 \n", "4 heightworker 0.312996 \n", "... ... ... \n", "306337 nobelt 0.038863 \n", "306338 nobelt 0.038397 \n", "306339 standardbelt 0.038192 \n", "306340 heightworker 0.037805 \n", "306341 heightworker 0.037645 \n", "\n", " predict_rois \\\n", "0 {'xmin': 0.4158405363559723, 'ymin': 0.2798240... \n", "1 {'xmin': 0.4895811975002289, 'ymin': 0.2275337... \n", "2 {'xmin': 0.5889867544174194, 'ymin': 0.3096078... \n", "3 {'xmin': 0.7787730693817139, 'ymin': 0.9041902... \n", "4 {'xmin': 0.6774665713310242, 'ymin': 0.4684889... \n", "... ... \n", "306337 {'xmin': 0.6894903779029846, 'ymin': 0.2435063... \n", "306338 {'xmin': 0.0, 'ymin': 0.6906387805938721, 'xma... \n", "306339 {'xmin': 0.6630510687828064, 'ymin': 0.7101314... \n", "306340 {'xmin': 0.3144895136356354, 'ymin': 0.9502524... \n", "306341 {'xmin': 0.7065272331237793, 'ymin': 0.1936995... \n", "\n", " image \n", "0 train/JPEGImages/001.jpg \n", "1 train/JPEGImages/001.jpg \n", "2 train/JPEGImages/001.jpg \n", "3 train/JPEGImages/001.jpg \n", "4 train/JPEGImages/001.jpg \n", "... ... \n", "306337 train/JPEGImages/fff82288-75e5-4178-be46-59ee4... \n", "306338 train/JPEGImages/fff82288-75e5-4178-be46-59ee4... \n", "306339 train/JPEGImages/fff82288-75e5-4178-be46-59ee4... \n", "306340 train/JPEGImages/fff82288-75e5-4178-be46-59ee4... \n", "306341 train/JPEGImages/fff82288-75e5-4178-be46-59ee4... \n", "\n", "[306342 rows x 4 columns]\n" ] } ], "source": [ "# 预测结果\n", "bulk_result = new_detector.predict(dataset_train)\n", "print(bulk_result)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# 保存为csv文件方便后续处理\n", "bulk_result.to_csv('/home/Enderfga/emotion/bulk_result.csv')" ] } ], "metadata": { "interpreter": { "hash": "4c83ae40a13bf2733dfd8dae71f7e96f7a46c0b1d2cda0ba4696c5d384a48522" }, "kernelspec": { "display_name": "Python 3.7.12 ('nlp')", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.12" } }, "nbformat": 4, "nbformat_minor": 4 }