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# 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, [ 768, 3, 2 ] ], # 7-P5/32
[ -1, 3, C3, [ 768 ] ],
[ -1, 1, Conv, [ 1024, 3, 2 ] ], # 9-P6/64
[ -1, 3, C3, [ 1024 ] ],
[ -1, 1, Conv, [ 1280, 3, 2 ] ], # 11-P7/128
[ -1, 1, SPP, [ 1280, [ 3, 5 ] ] ],
[ -1, 3, C3, [ 1280, False ] ], # 13
]
# YOLOv5 head
head:
[ [ -1, 1, Conv, [ 1024, 1, 1 ] ],
[ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ],
[ [ -1, 10 ], 1, Concat, [ 1 ] ], # cat backbone P6
[ -1, 3, C3, [ 1024, False ] ], # 17
[ -1, 1, Conv, [ 768, 1, 1 ] ],
[ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ],
[ [ -1, 8 ], 1, Concat, [ 1 ] ], # cat backbone P5
[ -1, 3, C3, [ 768, False ] ], # 21
[ -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 ] ], # 25
[ -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 ] ], # 29 (P3/8-small)
[ -1, 1, Conv, [ 256, 3, 2 ] ],
[ [ -1, 26 ], 1, Concat, [ 1 ] ], # cat head P4
[ -1, 3, C3, [ 512, False ] ], # 32 (P4/16-medium)
[ -1, 1, Conv, [ 512, 3, 2 ] ],
[ [ -1, 22 ], 1, Concat, [ 1 ] ], # cat head P5
[ -1, 3, C3, [ 768, False ] ], # 35 (P5/32-large)
[ -1, 1, Conv, [ 768, 3, 2 ] ],
[ [ -1, 18 ], 1, Concat, [ 1 ] ], # cat head P6
[ -1, 3, C3, [ 1024, False ] ], # 38 (P6/64-xlarge)
[ -1, 1, Conv, [ 1024, 3, 2 ] ],
[ [ -1, 14 ], 1, Concat, [ 1 ] ], # cat head P7
[ -1, 3, C3, [ 1280, False ] ], # 41 (P7/128-xxlarge)
[ [ 29, 32, 35, 38, 41 ], 1, Detect, [ nc, anchors ] ], # Detect(P3, P4, P5, P6, P7)
]
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