yolov5m6.yaml 1.8 KB

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  1. # YOLOv5 🚀 by Ultralytics, GPL-3.0 license
  2. # Parameters
  3. nc: 80 # number of classes
  4. depth_multiple: 0.67 # save_models depth multiple
  5. width_multiple: 0.75 # layer channel multiple
  6. anchors:
  7. - [19,27, 44,40, 38,94] # P3/8
  8. - [96,68, 86,152, 180,137] # P4/16
  9. - [140,301, 303,264, 238,542] # P5/32
  10. - [436,615, 739,380, 925,792] # P6/64
  11. # YOLOv5 v6.0 backbone
  12. backbone:
  13. # [from, number, module, args]
  14. [[-1, 1, Conv, [64, 6, 2, 2]], # 0-P1/2
  15. [-1, 1, Conv, [128, 3, 2]], # 1-P2/4
  16. [-1, 3, C3, [128]],
  17. [-1, 1, Conv, [256, 3, 2]], # 3-P3/8
  18. [-1, 6, C3, [256]],
  19. [-1, 1, Conv, [512, 3, 2]], # 5-P4/16
  20. [-1, 9, C3, [512]],
  21. [-1, 1, Conv, [768, 3, 2]], # 7-P5/32
  22. [-1, 3, C3, [768]],
  23. [-1, 1, Conv, [1024, 3, 2]], # 9-P6/64
  24. [-1, 3, C3, [1024]],
  25. [-1, 1, SPPF, [1024, 5]], # 11
  26. ]
  27. # YOLOv5 v6.0 head
  28. head:
  29. [[-1, 1, Conv, [768, 1, 1]],
  30. [-1, 1, nn.Upsample, [None, 2, 'nearest']],
  31. [[-1, 8], 1, Concat, [1]], # cat backbone P5
  32. [-1, 3, C3, [768, False]], # 15
  33. [-1, 1, Conv, [512, 1, 1]],
  34. [-1, 1, nn.Upsample, [None, 2, 'nearest']],
  35. [[-1, 6], 1, Concat, [1]], # cat backbone P4
  36. [-1, 3, C3, [512, False]], # 19
  37. [-1, 1, Conv, [256, 1, 1]],
  38. [-1, 1, nn.Upsample, [None, 2, 'nearest']],
  39. [[-1, 4], 1, Concat, [1]], # cat backbone P3
  40. [-1, 3, C3, [256, False]], # 23 (P3/8-small)
  41. [-1, 1, Conv, [256, 3, 2]],
  42. [[-1, 20], 1, Concat, [1]], # cat head P4
  43. [-1, 3, C3, [512, False]], # 26 (P4/16-medium)
  44. [-1, 1, Conv, [512, 3, 2]],
  45. [[-1, 16], 1, Concat, [1]], # cat head P5
  46. [-1, 3, C3, [768, False]], # 29 (P5/32-large)
  47. [-1, 1, Conv, [768, 3, 2]],
  48. [[-1, 12], 1, Concat, [1]], # cat head P6
  49. [-1, 3, C3, [1024, False]], # 32 (P6/64-xlarge)
  50. [[23, 26, 29, 32], 1, Detect, [nc, anchors]], # Detect(P3, P4, P5, P6)
  51. ]