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  1. # YOLOv5 🚀 by Ultralytics, GPL-3.0 license
  2. # Parameters
  3. nc: 80 # number of classes
  4. depth_multiple: 0.33 # model depth multiple
  5. width_multiple: 0.50 # layer channel multiple
  6. anchors: 3 # AutoAnchor evolves 3 anchors per P output layer
  7. # YOLOv5 v6.0 backbone
  8. backbone:
  9. # [from, number, module, args]
  10. [ [ -1, 1, Conv, [ 64, 6, 2, 2 ] ], # 0-P1/2
  11. [ -1, 1, Conv, [ 128, 3, 2 ] ], # 1-P2/4
  12. [ -1, 3, C3, [ 128 ] ],
  13. [ -1, 1, Conv, [ 256, 3, 2 ] ], # 3-P3/8
  14. [ -1, 6, C3, [ 256 ] ],
  15. [ -1, 1, Conv, [ 512, 3, 2 ] ], # 5-P4/16
  16. [ -1, 9, C3, [ 512 ] ],
  17. [ -1, 1, Conv, [ 1024, 3, 2 ] ], # 7-P5/32
  18. [ -1, 3, C3, [ 1024 ] ],
  19. [ -1, 1, SPPF, [ 1024, 5 ] ], # 9
  20. ]
  21. # YOLOv5 v6.0 head with (P3, P4) outputs
  22. head:
  23. [ [ -1, 1, Conv, [ 512, 1, 1 ] ],
  24. [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ],
  25. [ [ -1, 6 ], 1, Concat, [ 1 ] ], # cat backbone P4
  26. [ -1, 3, C3, [ 512, False ] ], # 13
  27. [ -1, 1, Conv, [ 256, 1, 1 ] ],
  28. [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ],
  29. [ [ -1, 4 ], 1, Concat, [ 1 ] ], # cat backbone P3
  30. [ -1, 3, C3, [ 256, False ] ], # 17 (P3/8-small)
  31. [ -1, 1, Conv, [ 256, 3, 2 ] ],
  32. [ [ -1, 14 ], 1, Concat, [ 1 ] ], # cat head P4
  33. [ -1, 3, C3, [ 512, False ] ], # 20 (P4/16-medium)
  34. [ [ 17, 20 ], 1, Detect, [ nc, anchors ] ], # Detect(P3, P4)
  35. ]