48 lines
1.3 KiB
YAML
48 lines
1.3 KiB
YAML
# parameters
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nc: 1 # number of classes
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depth_multiple: 1.0 # model depth multiple
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width_multiple: 1.0 # layer channel multiple
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# anchors
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anchors:
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- [4,5, 8,10, 13,16] # P3/8
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- [23,29, 43,55, 73,105] # P4/16
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- [146,217, 231,300, 335,433] # 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, StemBlock, [64, 3, 2]], # 0-P1/2
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[-1, 3, C3, [128]],
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[-1, 1, Conv, [256, 3, 2]], # 2-P3/8
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[-1, 9, C3, [256]],
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[-1, 1, Conv, [512, 3, 2]], # 4-P4/16
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[-1, 9, C3, [512]],
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[-1, 1, Conv, [1024, 3, 2]], # 6-P5/32
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[-1, 1, SPP, [1024, [3,5,7]]],
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[-1, 3, C3, [1024, False]], # 8
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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, 5], 1, Concat, [1]], # cat backbone P4
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[-1, 3, C3, [512, False]], # 12
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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, 3], 1, Concat, [1]], # cat backbone P3
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[-1, 3, C3, [256, False]], # 16 (P3/8-small)
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[-1, 1, Conv, [256, 3, 2]],
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[[-1, 13], 1, Concat, [1]], # cat head P4
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[-1, 3, C3, [512, False]], # 19 (P4/16-medium)
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[-1, 1, Conv, [512, 3, 2]],
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[[-1, 9], 1, Concat, [1]], # cat head P5
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[-1, 3, C3, [1024, False]], # 22 (P5/32-large)
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[[16, 19, 22], 1, Detect, [nc, anchors]], # Detect(P3, P4, P5)
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]
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