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# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
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# Parameters
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nc: 80 # number of classes
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depth_multiple: 0.33 # scales module repeats
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width_multiple: 0.50 # scales convolution channels
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# YOLOv8.0s backbone
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backbone:
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# [from, repeats, module, args]
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- [-1, 1, Conv, [64, 3, 2]] # 0-P1/2
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- [-1, 1, Conv, [128, 3, 2]] # 1-P2/4
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- [-1, 3, C2f, [128, True]]
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- [-1, 1, Conv, [256, 3, 2]] # 3-P3/8
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- [-1, 6, C2f, [256, True]]
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- [-1, 1, Conv, [512, 3, 2]] # 5-P4/16
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- [-1, 6, C2f, [512, True]]
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- [-1, 1, Conv, [1024, 3, 2]] # 7-P5/32
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- [-1, 3, C2f, [1024, True]]
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- [-1, 1, SPPF, [1024, 5]] # 9
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# YOLOv8.0s head
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head:
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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, C2f, [512]] # 13
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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, C2f, [256]] # 17 (P3/8-small)
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- [-1, 1, Conv, [256, 3, 2]]
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- [[-1, 12], 1, Concat, [1]] # cat head P4
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- [-1, 3, C2f, [512]] # 20 (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, C2f, [1024]] # 23 (P5/32-large)
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- [[15, 18, 21], 1, Segment, [nc, 32, 256]] # Detect(P3, P4, P5)
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