# parameters nc: 80 # number of classes depth_multiple: 1.0 # model depth multiple width_multiple: 1.0 # layer channel multiple # anchors anchors: 3 # YOLOv5 backbone backbone: # [from, number, module, args] [ [ -1, 1, Focus, [ 64, 3 ] ], # 0-P1/2 [ -1, 1, Conv, [ 128, 3, 2 ] ], # 1-P2/4 [ -1, 3, C3, [ 128 ] ], [ -1, 1, Conv, [ 256, 3, 2 ] ], # 3-P3/8 [ -1, 9, C3, [ 256 ] ], [ -1, 1, Conv, [ 512, 3, 2 ] ], # 5-P4/16 [ -1, 9, C3, [ 512 ] ], [ -1, 1, Conv, [ 1024, 3, 2 ] ], # 7-P5/32 [ -1, 1, SPP, [ 1024, [ 5, 9, 13 ] ] ], [ -1, 3, C3, [ 1024, False ] ], # 9 ] # YOLOv5 head head: [ [ -1, 1, Conv, [ 512, 1, 1 ] ], [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], [ [ -1, 6 ], 1, Concat, [ 1 ] ], # cat backbone P4 [ -1, 3, C3, [ 512, False ] ], # 13 [ -1, 1, Conv, [ 256, 1, 1 ] ], [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], [ [ -1, 4 ], 1, Concat, [ 1 ] ], # cat backbone P3 [ -1, 3, C3, [ 256, False ] ], # 17 (P3/8-small) [ -1, 1, Conv, [ 128, 1, 1 ] ], [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], [ [ -1, 2 ], 1, Concat, [ 1 ] ], # cat backbone P2 [ -1, 1, C3, [ 128, False ] ], # 21 (P2/4-xsmall) [ -1, 1, Conv, [ 128, 3, 2 ] ], [ [ -1, 18 ], 1, Concat, [ 1 ] ], # cat head P3 [ -1, 3, C3, [ 256, False ] ], # 24 (P3/8-small) [ -1, 1, Conv, [ 256, 3, 2 ] ], [ [ -1, 14 ], 1, Concat, [ 1 ] ], # cat head P4 [ -1, 3, C3, [ 512, False ] ], # 27 (P4/16-medium) [ -1, 1, Conv, [ 512, 3, 2 ] ], [ [ -1, 10 ], 1, Concat, [ 1 ] ], # cat head P5 [ -1, 3, C3, [ 1024, False ] ], # 30 (P5/32-large) [ [ 24, 27, 30 ], 1, Detect, [ nc, anchors ] ], # Detect(P3, P4, P5) ]