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yolov5_ZWgra/models/yolov5s.yaml
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# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Parameters
nc: 80 # number of classes
depth_multiple: 0.33 # model depth multiple
width_multiple: 0.50 # layer channel multiple
anchors:
- [10, 13, 16, 30, 33, 23] # P3/8
- [30, 61, 62, 45, 59, 119] # P4/16
- [116, 90, 156, 198, 373, 326] # P5/32
# YOLOv5 v6.0 backbone
# backbone:
# # [from, number, module, args]
# [
# [-1, 1, Conv, [64, 6, 2, 2]], # 0-P1/2
# [-1, 1, Conv, [128, 3, 2]], # 1-P2/4
# [-1, 3, C3, [128]],
# [-1, 1, Conv, [256, 3, 2]], # 3-P3/8
# [-1, 6, C3, [256]],
# [-1, 1, Conv, [512, 3, 2]], # 5-P4/16
# [-1, 9, C3, [512]],
# [-1, 1, Conv, [1024, 3, 2]], # 7-P5/32
# [-1, 3, C3, [1024]],
# [-1, 1, SPPF, [1024, 5]], # 9
# ]
backbone:
[
[-1, 1, Conv, [64, 6, 2, 2]], # 0-P1/2
[-1, 1, Conv, [128, 3, 2]], # 1-P2/4
[-1, 3, C3, [128]], # 2 (保持不变)
[-1, 1, Conv, [256, 3, 2]], # 3-P3/8
[-1, 6, C3, [256]], # 4 (保持不变)
[-1, 1, Conv, [512, 3, 2]], # 5-P4/16
[-1, 9, C3CBAM, [512]], # 6 ★ 加 CBAM
[-1, 1, Conv, [1024, 3, 2]], # 7-P5/32
[-1, 3, C3CBAM, [1024]], # 8 ★ 加 CBAM
[-1, 1, SPPF, [1024, 5]], # 9
]
# YOLOv5 v6.0 head
head: [
[-1, 1, Conv, [512, 1, 1]],
[-1, 1, nn.Upsample, [None, 2, "nearest"]],
[[-1, 6], 1, Concat, [1]], # cat backbone P4
[-1, 3, C3, [512, False]], # 13
[-1, 1, Conv, [256, 1, 1]],
[-1, 1, nn.Upsample, [None, 2, "nearest"]],
[[-1, 4], 1, Concat, [1]], # cat backbone P3
[-1, 3, C3, [256, False]], # 17 (P3/8-small)
[-1, 1, Conv, [256, 3, 2]],
[[-1, 14], 1, Concat, [1]], # cat head P4
[-1, 3, C3, [512, False]], # 20 (P4/16-medium)
[-1, 1, Conv, [512, 3, 2]],
[[-1, 10], 1, Concat, [1]], # cat head P5
[-1, 3, C3, [1024, False]], # 23 (P5/32-large)
[[17, 20, 23], 1, Detect, [nc, anchors]], # Detect(P3, P4, P5)
]