yolov5-p2.yaml
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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, [ 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)
]