[net] # Testing #batch=1 #subdivisions=1 # Training batch=64 subdivisions=64 width=640 #For Train 640x640 input....For evaluation Train: 800x800, Val:576, Test:800 height=640 channels=3 momentum=0.949 decay=0.0005 angle=0 saturation = 1.5 exposure = 1.5 hue=.1 learning_rate=0.001 burn_in=1000 max_batches = 6000 policy=steps steps=4800,5400 scales=.1,.1 #cutmix=1 mosaic=1 #:104x104 54:52x52 85:26x26 104:13x13 for 416 [convolutional] batch_normalize=1 filters=32 size=3 stride=1 pad=1 activation=mish # Downsample [convolutional] batch_normalize=1 filters=64 size=3 stride=2 pad=1 activation=mish [convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=mish [route] layers = -2 [convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=32 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=mish [route] layers = -1,-7 [convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=mish # Downsample [convolutional] batch_normalize=1 filters=128 size=3 stride=2 pad=1 activation=mish [convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=mish [route] layers = -2 [convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=mish [route] layers = -1,-10 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=mish # Downsample [convolutional] batch_normalize=1 filters=256 size=3 stride=2 pad=1 activation=mish [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=mish [route] layers = -2 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=mish [route] layers = -1,-28 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=mish # Downsample [convolutional] batch_normalize=1 filters=512 size=3 stride=2 pad=1 activation=mish [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=mish [route] layers = -2 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=mish [route] layers = -1,-28 [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=mish # Downsample [convolutional] batch_normalize=1 filters=1024 size=3 stride=2 pad=1 activation=mish [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=mish [route] layers = -2 [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=mish [convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=mish [shortcut] from=-3 activation=linear [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=mish [route] layers = -1,-16 [convolutional] batch_normalize=1 filters=1024 size=1 stride=1 pad=1 activation=mish stopbackward=800 ########################## [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=1024 activation=leaky [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky ### SPP ### [maxpool] stride=1 size=5 [route] layers=-2 [maxpool] stride=1 size=9 [route] layers=-4 [maxpool] stride=1 size=13 [route] layers=-1,-3,-5,-6 ### End SPP ### [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=1024 activation=leaky [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [upsample] stride=2 [route] layers = 85 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [route] layers = -1, -3 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=512 activation=leaky [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=512 activation=leaky [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [upsample] stride=2 [route] layers = 54 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [route] layers = -1, -3 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=256 activation=leaky [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=256 activation=leaky [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky ########################## [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=256 activation=leaky [convolutional] size=1 stride=1 pad=1 filters=21 activation=linear [yolo] mask = 0,1,2 anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401 classes=2 num=9 jitter=.3 ignore_thresh = .7 truth_thresh = 1 scale_x_y = 1.2 iou_thresh=0.213 cls_normalizer=1.0 iou_normalizer=0.07 iou_loss=ciou nms_kind=greedynms beta_nms=0.6 max_delta=5 [route] layers = -4 [convolutional] batch_normalize=1 size=3 stride=2 pad=1 filters=256 activation=leaky [route] layers = -1, -16 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=512 activation=leaky [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=512 activation=leaky [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=512 activation=leaky [convolutional] size=1 stride=1 pad=1 filters=21 activation=linear [yolo] mask = 3,4,5 anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401 classes=2 num=9 jitter=.3 ignore_thresh = .7 truth_thresh = 1 scale_x_y = 1.1 iou_thresh=0.213 cls_normalizer=1.0 iou_normalizer=0.07 iou_loss=ciou nms_kind=greedynms beta_nms=0.6 max_delta=5 [route] layers = -4 [convolutional] batch_normalize=1 size=3 stride=2 pad=1 filters=512 activation=leaky [route] layers = -1, -37 [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=1024 activation=leaky [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=1024 activation=leaky [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=leaky [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=1024 activation=leaky [convolutional] size=1 stride=1 pad=1 filters=21 activation=linear [yolo] mask = 6,7,8 anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401 classes=2 num=9 jitter=.3 ignore_thresh = .7 truth_thresh = 1 random=1 scale_x_y = 1.05 iou_thresh=0.213 cls_normalizer=1.0 iou_normalizer=0.07 iou_loss=ciou nms_kind=greedynms beta_nms=0.6 max_delta=5