48 lines
1.5 KiB
YAML
48 lines
1.5 KiB
YAML
# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
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# Parameters
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nc: 10 # 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 v6.0 backbone
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backbone:
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# [from, number, module, args]
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[[-1, 1, Conv, [64, 6, 2, 2]], # 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, 6, 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, 3, C3, [1024]],
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[-1, 1, SPPF, [1024, 5]], # 9
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]
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# YOLOv5 v6.0 BiFPN 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, BiFPN_Add2, [256, 256]], # 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, BiFPN_Add2, [128, 128]], # cat backbone P3
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[-1, 3, C3, [256, False]], # 17 (P3/8-small)
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[-1, 1, Conv, [512, 3, 2]], # 为了BiFPN正确add，调整channel数
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[[-1, 13, 6], 1, BiFPN_Add3, [256, 256]], # cat P4 <--- BiFPN change 注意v5s通道数是默认参数的一半
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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, BiFPN_Add2, [256, 256]], # 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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] |