yolov5l.yaml 1.4 KB

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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:
  7. - [10,13, 16,30, 33,23] # P3/8
  8. - [30,61, 62,45, 59,119] # P4/16
  9. - [116,90, 156,198, 373,326] # P5/32
  10. # YOLOv5 v6.0 backbone
  11. backbone:
  12. # [from, number, module, args]
  13. [[-1, 1, Conv, [64, 6, 2, 2]], # 0-P1/2
  14. [-1, 1, Conv, [128, 3, 2]], # 1-P2/4
  15. [-1, 3, C3, [128]],
  16. [-1, 1, Conv, [256, 3, 2]], # 3-P3/8
  17. [-1, 6, C3, [256]],
  18. [-1, 1, Conv, [512, 3, 2]], # 5-P4/16
  19. [-1, 9, C3, [512]],
  20. [-1, 1, Conv, [1024, 3, 2]], # 7-P5/32
  21. [-1, 3, C3, [1024]],
  22. [-1, 1, SPPF, [1024, 5]], # 9
  23. ]
  24. # YOLOv5 v6.0 head
  25. head:
  26. [[-1, 1, Conv, [512, 1, 1]],
  27. [-1, 1, nn.Upsample, [None, 2, 'nearest']],
  28. [[-1, 6], 1, Concat, [1]], # cat backbone P4
  29. [-1, 3, C3, [512, False]], # 13
  30. [-1, 1, Conv, [256, 1, 1]],
  31. [-1, 1, nn.Upsample, [None, 2, 'nearest']],
  32. [[-1, 4], 1, Concat, [1]], # cat backbone P3
  33. [-1, 3, C3, [256, False]], # 17 (P3/8-small)
  34. [-1, 1, Conv, [256, 3, 2]],
  35. [[-1, 14], 1, Concat, [1]], # cat head P4
  36. [-1, 3, C3, [512, False]], # 20 (P4/16-medium)
  37. [-1, 1, Conv, [512, 3, 2]],
  38. [[-1, 10], 1, Concat, [1]], # cat head P5
  39. [-1, 3, C3, [1024, False]], # 23 (P5/32-large)
  40. [[17, 20, 23], 1, Detect, [nc, anchors]], # Detect(P3, P4, P5)
  41. ]