OCRNet_HRNet-W18.yaml 1.1 KB

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  1. batch_size: 2
  2. iters: 160000
  3. train_dataset:
  4. type: Dataset
  5. dataset_root: datasets/Cityscapes
  6. train_path: datasets/Cityscapes/train.txt
  7. num_classes: 19
  8. transforms:
  9. - type: ResizeStepScaling
  10. min_scale_factor: 0.5
  11. max_scale_factor: 2.0
  12. scale_step_size: 0.25
  13. - type: RandomPaddingCrop
  14. crop_size: [1024, 512]
  15. - type: RandomHorizontalFlip
  16. - type: RandomDistort
  17. brightness_range: 0.4
  18. contrast_range: 0.4
  19. saturation_range: 0.4
  20. - type: Normalize
  21. mode: train
  22. val_dataset:
  23. type: Dataset
  24. dataset_root: datasets/Cityscapes
  25. val_path: datasets/Cityscapes/val.txt
  26. num_classes: 19
  27. transforms:
  28. - type: Normalize
  29. mode: val
  30. model:
  31. type: OCRNet
  32. backbone:
  33. type: HRNet_W18
  34. pretrained: https://bj.bcebos.com/paddleseg/dygraph/hrnet_w18_ssld.tar.gz
  35. backbone_indices: [0]
  36. optimizer:
  37. type: SGD
  38. momentum: 0.9
  39. weight_decay: 4.0e-5
  40. lr_scheduler:
  41. type: PolynomialDecay
  42. learning_rate: 0.01
  43. end_lr: 0
  44. power: 0.9
  45. loss:
  46. types:
  47. - type: CrossEntropyLoss
  48. - type: CrossEntropyLoss
  49. coef: [1, 0.4]