TensorRT转化代码
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  1. # Parameters
  2. nc: 80 # number of classes
  3. depth_multiple: 1.0 # model depth multiple
  4. width_multiple: 1.0 # layer channel multiple
  5. anchors: 3
  6. # YOLOv5 backbone
  7. backbone:
  8. # [from, number, module, args]
  9. [[-1, 1, Focus, [64, 3]], # 0-P1/2
  10. [-1, 1, Conv, [128, 3, 2]], # 1-P2/4
  11. [-1, 3, C3, [128]],
  12. [-1, 1, Conv, [256, 3, 2]], # 3-P3/8
  13. [-1, 9, C3, [256]],
  14. [-1, 1, Conv, [512, 3, 2]], # 5-P4/16
  15. [-1, 9, C3, [512]],
  16. [-1, 1, Conv, [1024, 3, 2]], # 7-P5/32
  17. [-1, 1, SPP, [1024, [5, 9, 13]]],
  18. [-1, 3, C3, [1024, False]], # 9
  19. ]
  20. # YOLOv5 head
  21. head:
  22. [[-1, 1, Conv, [512, 1, 1]],
  23. [-1, 1, nn.Upsample, [None, 2, 'nearest']],
  24. [[-1, 6], 1, Concat, [1]], # cat backbone P4
  25. [-1, 3, C3, [512, False]], # 13
  26. [-1, 1, Conv, [256, 1, 1]],
  27. [-1, 1, nn.Upsample, [None, 2, 'nearest']],
  28. [[-1, 4], 1, Concat, [1]], # cat backbone P3
  29. [-1, 3, C3, [256, False]], # 17 (P3/8-small)
  30. [-1, 1, Conv, [128, 1, 1]],
  31. [-1, 1, nn.Upsample, [None, 2, 'nearest']],
  32. [[-1, 2], 1, Concat, [1]], # cat backbone P2
  33. [-1, 1, C3, [128, False]], # 21 (P2/4-xsmall)
  34. [-1, 1, Conv, [128, 3, 2]],
  35. [[-1, 18], 1, Concat, [1]], # cat head P3
  36. [-1, 3, C3, [256, False]], # 24 (P3/8-small)
  37. [-1, 1, Conv, [256, 3, 2]],
  38. [[-1, 14], 1, Concat, [1]], # cat head P4
  39. [-1, 3, C3, [512, False]], # 27 (P4/16-medium)
  40. [-1, 1, Conv, [512, 3, 2]],
  41. [[-1, 10], 1, Concat, [1]], # cat head P5
  42. [-1, 3, C3, [1024, False]], # 30 (P5/32-large)
  43. [[24, 27, 30], 1, Detect, [nc, anchors]], # Detect(P3, P4, P5)
  44. ]