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# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
# Parameters
nc: 80 # number of classes
depth_multiple: 1.00 # model depth multiple
width_multiple: 1.25 # layer channel multiple
# YOLOv8.0x backbone
backbone:
# [from, number, module, args]
[[-1, 1, Conv, [64, 3, 2]], # 0-P1/2
[-1, 1, Conv, [128, 3, 2]], # 1-P2/4
[-1, 3, C2f, [128, True]],
[-1, 1, Conv, [256, 3, 2]], # 3-P3/8
[-1, 6, C2f, [256, True]],
[-1, 1, Conv, [512, 3, 2]], # 5-P4/16
[-1, 6, C2f, [512, True]],
[-1, 1, Conv, [512, 3, 2]], # 7-P5/32
[-1, 3, C2f, [512, True]],
[-1, 1, SPPF, [512, 5]], # 9
]
# YOLOv8.0x head
head:
[[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 6], 1, Concat, [1]], # cat backbone P4
[-1, 3, C2f, [512]], # 13
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 4], 1, Concat, [1]], # cat backbone P3
[-1, 3, C2f, [256]], # 17 (P3/8-small)
[-1, 1, Conv, [256, 3, 2]],
[[-1, 12], 1, Concat, [1]], # cat head P4
[-1, 3, C2f, [512]], # 20 (P4/16-medium)
[-1, 1, Conv, [512, 3, 2]],
[[-1, 9], 1, Concat, [1]], # cat head P5
[-1, 3, C2f, [512]], # 23 (P5/32-large)
[[15, 18, 21], 1, Segment, [nc, 32, 256]], # Detect(P3, P4, P5)
]