yolov3-tiny.yaml 1.2 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 # save_models depth multiple
  5. width_multiple: 1.0 # layer channel multiple
  6. anchors:
  7. - [10,14, 23,27, 37,58] # P4/16
  8. - [81,82, 135,169, 344,319] # P5/32
  9. # YOLOv3-tiny backbone
  10. backbone:
  11. # [from, number, module, args]
  12. [[-1, 1, Conv, [16, 3, 1]], # 0
  13. [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 1-P1/2
  14. [-1, 1, Conv, [32, 3, 1]],
  15. [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 3-P2/4
  16. [-1, 1, Conv, [64, 3, 1]],
  17. [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 5-P3/8
  18. [-1, 1, Conv, [128, 3, 1]],
  19. [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 7-P4/16
  20. [-1, 1, Conv, [256, 3, 1]],
  21. [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 9-P5/32
  22. [-1, 1, Conv, [512, 3, 1]],
  23. [-1, 1, nn.ZeroPad2d, [[0, 1, 0, 1]]], # 11
  24. [-1, 1, nn.MaxPool2d, [2, 1, 0]], # 12
  25. ]
  26. # YOLOv3-tiny head
  27. head:
  28. [[-1, 1, Conv, [1024, 3, 1]],
  29. [-1, 1, Conv, [256, 1, 1]],
  30. [-1, 1, Conv, [512, 3, 1]], # 15 (P5/32-large)
  31. [-2, 1, Conv, [128, 1, 1]],
  32. [-1, 1, nn.Upsample, [None, 2, 'nearest']],
  33. [[-1, 8], 1, Concat, [1]], # cat backbone P4
  34. [-1, 1, Conv, [256, 3, 1]], # 19 (P4/16-medium)
  35. [[19, 15], 1, Detect, [nc, anchors]], # Detect(P4, P5)
  36. ]