[net] # Testing #batch=1 #subdivisions=1 # Training batch=8 subdivisions=1 width=640 height=640 channels=3 momentum=0.9 decay=0.0005 angle=0 saturation = 1.5 exposure = 1.5 hue=.1 learning_rate=0.00261 burn_in=1000 max_batches = 2000200 policy=steps steps=1600000,1800000 scales=.1,.1 # 0 [convolutional] batch_normalize=1 filters=32 size=3 stride=1 pad=1 activation=swish # 1 [convolutional] batch_normalize=1 filters=64 size=3 stride=2 pad=1 activation=swish [convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=swish # 3 [convolutional] batch_normalize=1 filters=128 size=3 stride=2 pad=1 activation=swish [convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=swish [route] layers=-2 [convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=swish [route] layers = -1,-3,-5,-7 # 12 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [maxpool] size=2 stride=2 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=swish [route] layers=-3 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=2 pad=1 activation=swish # 18 [route] layers = -1,-4 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=swish [route] layers=-2 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=swish [route] layers = -1,-3,-5,-7 # 27 [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=swish [maxpool] size=2 stride=2 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [route] layers=-3 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=2 pad=1 activation=swish # 33 [route] layers = -1,-4 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [route] layers=-2 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=swish [route] layers = -1,-3,-5,-7 # 42 [convolutional] batch_normalize=1 filters=1024 size=1 stride=1 pad=1 activation=swish [maxpool] size=2 stride=2 [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=swish [route] layers=-3 [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=512 size=3 stride=2 pad=1 activation=swish # 48 [route] layers = -1,-4 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [route] layers=-2 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=swish [route] layers = -1,-3,-5,-7 # 57 [convolutional] batch_normalize=1 filters=1024 size=1 stride=1 pad=1 activation=swish ################################## ### SPPCSP ### [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=swish [route] layers = -2 [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=512 activation=swish [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=swish ### SPP ### [maxpool] stride=1 size=5 [route] layers=-2 [maxpool] stride=1 size=9 [route] layers=-4 [maxpool] stride=1 size=13 [route] layers=-6,-5,-3,-1 ### End SPP ### [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=512 activation=swish [route] layers = -1, -13 # 72 [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=swish ### End SPPCSP ### [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [upsample] stride=2 [route] layers = 42 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [route] layers = -1,-3 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [route] layers=-2 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=swish [route] layers = -1,-2,-3,-4,-5,-7 # 86 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=swish [upsample] stride=2 [route] layers = 27 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=swish [route] layers = -1,-3 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=swish [route] layers=-2 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=swish [route] layers = -1,-2,-3,-4,-5,-7 # 100 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=swish [maxpool] size=2 stride=2 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=swish [route] layers=-3 [convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=2 pad=1 activation=swish [route] layers = -1,-4,86 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [route] layers=-2 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=swish [route] layers = -1,-2,-3,-4,-5,-7 # 115 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [maxpool] size=2 stride=2 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [route] layers=-3 [convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=2 pad=1 activation=swish [route] layers = -1,-4,72 [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=swish [route] layers=-2 [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=swish [convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=swish [route] layers = -1,-2,-3,-4,-5,-7 # 130 [convolutional] batch_normalize=1 filters=512 size=1 stride=1 pad=1 activation=swish ############################# # ============ End of Neck ============ # # ============ Head ============ # # P3 [route] layers = 100 [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=256 activation=swish [convolutional] size=1 stride=1 pad=1 filters=255 #activation=linear activation=logistic [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=80 num=9 jitter=.1 scale_x_y = 2.0 objectness_smooth=1 ignore_thresh = .7 truth_thresh = 1 #random=1 resize=1.5 iou_thresh=0.2 iou_normalizer=0.05 cls_normalizer=0.5 obj_normalizer=1.0 iou_loss=ciou nms_kind=diounms beta_nms=0.6 new_coords=1 max_delta=2 # P4 [route] layers = 115 [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=512 activation=swish [convolutional] size=1 stride=1 pad=1 filters=255 #activation=linear activation=logistic [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=80 num=9 jitter=.1 scale_x_y = 2.0 objectness_smooth=1 ignore_thresh = .7 truth_thresh = 1 #random=1 resize=1.5 iou_thresh=0.2 iou_normalizer=0.05 cls_normalizer=0.5 obj_normalizer=1.0 iou_loss=ciou nms_kind=diounms beta_nms=0.6 new_coords=1 max_delta=2 # P5 [route] layers = 130 [convolutional] batch_normalize=1 size=3 stride=1 pad=1 filters=1024 activation=swish [convolutional] size=1 stride=1 pad=1 filters=255 #activation=linear activation=logistic [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=80 num=9 jitter=.1 scale_x_y = 2.0 objectness_smooth=1 ignore_thresh = .7 truth_thresh = 1 #random=1 resize=1.5 iou_thresh=0.2 iou_normalizer=0.05 cls_normalizer=0.5 obj_normalizer=1.0 iou_loss=ciou nms_kind=diounms beta_nms=0.6 new_coords=1 max_delta=2