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yolov5-p2.yaml 1.6KB

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  1. # YOLOv5 🚀 by Ultralytics, GPL-3.0 license
  2. # Parameters
  3. nc: 80 # number of classes
  4. depth_multiple: 1.0 # model depth multiple
  5. width_multiple: 1.0 # 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 (P2, P3, P4, P5) 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, [128, 1, 1]],
  32. [-1, 1, nn.Upsample, [None, 2, 'nearest']],
  33. [[-1, 2], 1, Concat, [1]], # cat backbone P2
  34. [-1, 1, C3, [128, False]], # 21 (P2/4-xsmall)
  35. [-1, 1, Conv, [128, 3, 2]],
  36. [[-1, 18], 1, Concat, [1]], # cat head P3
  37. [-1, 3, C3, [256, False]], # 24 (P3/8-small)
  38. [-1, 1, Conv, [256, 3, 2]],
  39. [[-1, 14], 1, Concat, [1]], # cat head P4
  40. [-1, 3, C3, [512, False]], # 27 (P4/16-medium)
  41. [-1, 1, Conv, [512, 3, 2]],
  42. [[-1, 10], 1, Concat, [1]], # cat head P5
  43. [-1, 3, C3, [1024, False]], # 30 (P5/32-large)
  44. [[21, 24, 27, 30], 1, Detect, [nc, anchors]], # Detect(P2, P3, P4, P5)
  45. ]