PP-TinyPose_256x192.yaml 3.1 KB

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  1. use_gpu: true
  2. log_iter: 5
  3. save_dir: output
  4. snapshot_epoch: 10
  5. weights: output/tinypose_256x192/model_final
  6. epoch: 420
  7. num_joints: &num_joints 17
  8. pixel_std: &pixel_std 200
  9. metric: KeyPointTopDownCOCOEval
  10. num_classes: 1
  11. train_height: &train_height 256
  12. train_width: &train_width 192
  13. trainsize: &trainsize [*train_width, *train_height]
  14. hmsize: &hmsize [48, 64]
  15. flip_perm: &flip_perm [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10], [11, 12], [13, 14], [15, 16]]
  16. use_ema: true
  17. #####model
  18. architecture: TopDownHRNet
  19. TopDownHRNet:
  20. backbone: LiteHRNet
  21. post_process: HRNetPostProcess
  22. flip_perm: *flip_perm
  23. num_joints: *num_joints
  24. width: &width 40
  25. loss: KeyPointMSELoss
  26. use_dark: true
  27. LiteHRNet:
  28. network_type: wider_naive
  29. freeze_at: -1
  30. freeze_norm: false
  31. return_idx: [0]
  32. KeyPointMSELoss:
  33. use_target_weight: true
  34. loss_scale: 1.0
  35. #####optimizer
  36. LearningRate:
  37. base_lr: 0.002
  38. schedulers:
  39. - !PiecewiseDecay
  40. milestones: [380, 410]
  41. gamma: 0.1
  42. - !LinearWarmup
  43. start_factor: 0.001
  44. steps: 500
  45. OptimizerBuilder:
  46. optimizer:
  47. type: Adam
  48. regularizer:
  49. factor: 0.0
  50. type: L2
  51. #####data
  52. TrainDataset:
  53. !KeypointTopDownCocoDataset
  54. image_dir: ""
  55. anno_path: aic_coco_train_cocoformat.json
  56. dataset_dir: dataset
  57. num_joints: *num_joints
  58. trainsize: *trainsize
  59. pixel_std: *pixel_std
  60. use_gt_bbox: True
  61. EvalDataset:
  62. !KeypointTopDownCocoDataset
  63. image_dir: val2017
  64. anno_path: annotations/person_keypoints_val2017.json
  65. dataset_dir: dataset/coco
  66. num_joints: *num_joints
  67. trainsize: *trainsize
  68. pixel_std: *pixel_std
  69. use_gt_bbox: True
  70. image_thre: 0.5
  71. TestDataset:
  72. !ImageFolder
  73. anno_path: dataset/coco/keypoint_imagelist.txt
  74. worker_num: 2
  75. global_mean: &global_mean [0.485, 0.456, 0.406]
  76. global_std: &global_std [0.229, 0.224, 0.225]
  77. TrainReader:
  78. sample_transforms:
  79. - RandomFlipHalfBodyTransform:
  80. scale: 0.25
  81. rot: 30
  82. num_joints_half_body: 8
  83. prob_half_body: 0.3
  84. pixel_std: *pixel_std
  85. trainsize: *trainsize
  86. upper_body_ids: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
  87. flip_pairs: *flip_perm
  88. - AugmentationbyInformantionDropping:
  89. prob_cutout: 0.5
  90. offset_factor: 0.05
  91. num_patch: 1
  92. trainsize: *trainsize
  93. - TopDownAffine:
  94. trainsize: *trainsize
  95. use_udp: true
  96. - ToHeatmapsTopDown_DARK:
  97. hmsize: *hmsize
  98. sigma: 2
  99. batch_transforms:
  100. - NormalizeImage:
  101. mean: *global_mean
  102. std: *global_std
  103. is_scale: true
  104. - Permute: {}
  105. batch_size: 128
  106. shuffle: true
  107. drop_last: false
  108. EvalReader:
  109. sample_transforms:
  110. - TopDownAffine:
  111. trainsize: *trainsize
  112. use_udp: true
  113. batch_transforms:
  114. - NormalizeImage:
  115. mean: *global_mean
  116. std: *global_std
  117. is_scale: true
  118. - Permute: {}
  119. batch_size: 16
  120. TestReader:
  121. inputs_def:
  122. image_shape: [3, *train_height, *train_width]
  123. sample_transforms:
  124. - Decode: {}
  125. - TopDownEvalAffine:
  126. trainsize: *trainsize
  127. - NormalizeImage:
  128. mean: *global_mean
  129. std: *global_std
  130. is_scale: true
  131. - Permute: {}
  132. batch_size: 1
  133. fuse_normalize: false