47 lines
1.5 KiB
YAML
47 lines
1.5 KiB
YAML
# Parameters
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nc: 80 # number of classes
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depth_multiple: 0.33 # model depth multiple
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width_multiple: 0.50 # layer channel multiple
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anchors:
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- [ 10,13, 16,30, 33,23 ] # P3/8
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- [ 30,61, 62,45, 59,119 ] # P4/16
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- [ 116,90, 156,198, 373,326 ] # P5/32
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# YOLOv5 backbone
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backbone:
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# [from, number, module, args]
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[ [ -1, 1, Focus, [ 64, 3 ] ], # 0-P1/2
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[ -1, 1, Conv, [ 128, 3, 2 ] ], # 1-P2/4
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[ -1, 3, C3, [ 128 ] ],
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[ -1, 1, Conv, [ 256, 3, 2 ] ], # 3-P3/8
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[ -1, 9, C3, [ 256 ] ],
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[ -1, 1, Conv, [ 512, 3, 2 ] ], # 5-P4/16
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[ -1, 9, C3, [ 512 ] ],
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[ -1, 1, Conv, [ 1024, 3, 2 ] ], # 7-P5/32
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[ -1, 1, SPP, [ 1024, [ 5, 9, 13 ] ] ],
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[ -1, 3, C3TR, [ 1024, False ] ], # 9 <-------- C3TR() Transformer module
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]
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# YOLOv5 head
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head:
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[ [ -1, 1, Conv, [ 512, 1, 1 ] ],
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[ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ],
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[ [ -1, 6 ], 1, Concat, [ 1 ] ], # cat backbone P4
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[ -1, 3, C3, [ 512, False ] ], # 13
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[ -1, 1, Conv, [ 256, 1, 1 ] ],
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[ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ],
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[ [ -1, 4 ], 1, Concat, [ 1 ] ], # cat backbone P3
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[ -1, 3, C3, [ 256, False ] ], # 17 (P3/8-small)
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[ -1, 1, Conv, [ 256, 3, 2 ] ],
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[ [ -1, 14 ], 1, Concat, [ 1 ] ], # cat head P4
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[ -1, 3, C3, [ 512, False ] ], # 20 (P4/16-medium)
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[ -1, 1, Conv, [ 512, 3, 2 ] ],
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[ [ -1, 10 ], 1, Concat, [ 1 ] ], # cat head P5
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[ -1, 3, C3, [ 1024, False ] ], # 23 (P5/32-large)
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[ [ 17, 20, 23 ], 1, Detect, [ nc, anchors ] ], # Detect(P3, P4, P5)
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]
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