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53 lines
1.6 KiB
YAML
53 lines
1.6 KiB
YAML
# Ultralytics YOLOv5 🚀, AGPL-3.0 license
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# Parameters
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nc: 80 # 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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- [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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# darknet53 backbone
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backbone:
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# [from, number, module, args]
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[
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[-1, 1, Conv, [32, 3, 1]], # 0
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[-1, 1, Conv, [64, 3, 2]], # 1-P1/2
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[-1, 1, Bottleneck, [64]],
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[-1, 1, Conv, [128, 3, 2]], # 3-P2/4
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[-1, 2, Bottleneck, [128]],
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[-1, 1, Conv, [256, 3, 2]], # 5-P3/8
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[-1, 8, Bottleneck, [256]],
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[-1, 1, Conv, [512, 3, 2]], # 7-P4/16
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[-1, 8, Bottleneck, [512]],
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[-1, 1, Conv, [1024, 3, 2]], # 9-P5/32
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[-1, 4, Bottleneck, [1024]], # 10
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]
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# YOLOv3-SPP head
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head: [
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[-1, 1, Bottleneck, [1024, False]],
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[-1, 1, SPP, [512, [5, 9, 13]]],
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[-1, 1, Conv, [1024, 3, 1]],
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[-1, 1, Conv, [512, 1, 1]],
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[-1, 1, Conv, [1024, 3, 1]], # 15 (P5/32-large)
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[-2, 1, Conv, [256, 1, 1]],
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[-1, 1, nn.Upsample, [None, 2, "nearest"]],
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[[-1, 8], 1, Concat, [1]], # cat backbone P4
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[-1, 1, Bottleneck, [512, False]],
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[-1, 1, Bottleneck, [512, False]],
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[-1, 1, Conv, [256, 1, 1]],
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[-1, 1, Conv, [512, 3, 1]], # 22 (P4/16-medium)
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[-2, 1, Conv, [128, 1, 1]],
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[-1, 1, nn.Upsample, [None, 2, "nearest"]],
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[[-1, 6], 1, Concat, [1]], # cat backbone P3
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[-1, 1, Bottleneck, [256, False]],
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[-1, 2, Bottleneck, [256, False]], # 27 (P3/8-small)
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[[27, 22, 15], 1, Detect, [nc, anchors]], # Detect(P3, P4, P5)
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]
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