ppmatting-hrnet_w48-distinctions.yml 1.1 KB

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  1. batch_size: 4
  2. iters: 300000
  3. train_dataset:
  4. type: MattingDataset
  5. dataset_root: data/matting/Distinctions-646
  6. train_file: train.txt
  7. transforms:
  8. - type: LoadImages
  9. - type: Padding
  10. target_size: [512, 512]
  11. - type: RandomCrop
  12. crop_size: [[512, 512],[640, 640], [800, 800]]
  13. - type: Resize
  14. target_size: [512, 512]
  15. - type: RandomDistort
  16. - type: RandomBlur
  17. prob: 0.1
  18. - type: RandomHorizontalFlip
  19. - type: Normalize
  20. mode: train
  21. separator: '|'
  22. val_dataset:
  23. type: MattingDataset
  24. dataset_root: data/matting/Distinctions-646
  25. val_file: val.txt
  26. transforms:
  27. - type: LoadImages
  28. - type: LimitShort
  29. max_short: 1536
  30. - type: ResizeToIntMult
  31. mult_int: 32
  32. - type: Normalize
  33. mode: val
  34. get_trimap: False
  35. separator: '|'
  36. model:
  37. type: PPMatting
  38. backbone:
  39. type: HRNet_W48
  40. pretrained: https://bj.bcebos.com/paddleseg/dygraph/hrnet_w48_ssld.tar.gz
  41. pretrained: Null
  42. optimizer:
  43. type: sgd
  44. momentum: 0.9
  45. weight_decay: 4.0e-5
  46. lr_scheduler:
  47. type: PolynomialDecay
  48. learning_rate: 0.01
  49. end_lr: 0
  50. power: 0.9