PP-YOLOE_plus-S_face.yaml 3.3 KB

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  1. # Runtime
  2. epoch: 10
  3. log_iter: 10
  4. find_unused_parameters: false
  5. use_gpu: true
  6. use_xpu: false
  7. use_mlu: false
  8. use_npu: false
  9. use_ema: True
  10. save_dir: output
  11. snapshot_epoch: 1
  12. print_flops: false
  13. print_params: false
  14. # Dataset
  15. metric: WiderFace
  16. num_classes: 1
  17. worker_num: 4
  18. eval_height: &eval_height 1088
  19. eval_width: &eval_width 1088
  20. eval_size: &eval_size [*eval_height, *eval_width]
  21. TrainDataset:
  22. name: COCODataSet
  23. image_dir: WIDER_train/images
  24. anno_path: train.json
  25. dataset_dir: data_face
  26. data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd']
  27. EvalDataset:
  28. name: COCODataSet
  29. image_dir: WIDER_val/images
  30. anno_path: val.json
  31. dataset_dir: data_face
  32. allow_empty: true
  33. TestDataset:
  34. name: COCODataSet
  35. image_dir: WIDER_val/images
  36. anno_path: val.json
  37. dataset_dir: data_face
  38. TrainReader:
  39. sample_transforms:
  40. - Decode: {}
  41. - RandomDistort: {}
  42. - RandomExpand: {fill_value: [123.675, 116.28, 103.53]}
  43. - RandomCrop: {}
  44. - RandomFlip: {}
  45. batch_transforms:
  46. - BatchRandomResize: {target_size: [320, 352, 384, 416, 448, 480, 512, 544, 576, 608, 640, 672, 704, 736, 768], random_size: True, random_interp: True, keep_ratio: False}
  47. - NormalizeImage: {mean: [0., 0., 0.], std: [1., 1., 1.], norm_type: none}
  48. - Permute: {}
  49. - PadGT: {}
  50. batch_size: 8
  51. shuffle: true
  52. drop_last: true
  53. use_shared_memory: true
  54. collate_batch: true
  55. EvalReader:
  56. sample_transforms:
  57. - Decode: {}
  58. - Resize: {target_size: *eval_size, keep_ratio: False, interp: 2}
  59. - NormalizeImage: {mean: [0., 0., 0.], std: [1., 1., 1.], norm_type: none}
  60. - Permute: {}
  61. batch_size: 2
  62. TestReader:
  63. inputs_def:
  64. image_shape: [3, *eval_height, *eval_width]
  65. sample_transforms:
  66. - Decode: {}
  67. - Resize: {target_size: *eval_size, keep_ratio: False, interp: 2}
  68. - NormalizeImage: {mean: [0., 0., 0.], std: [1., 1., 1.], norm_type: none}
  69. - Permute: {}
  70. batch_size: 1
  71. # Model
  72. architecture: YOLOv3
  73. pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_s_obj365_pretrained.pdparams
  74. norm_type: sync_bn
  75. ema_decay: 0.9998
  76. ema_black_list: ['proj_conv.weight']
  77. custom_black_list: ['reduce_mean']
  78. depth_mult: 0.33
  79. width_mult: 0.50
  80. YOLOv3:
  81. backbone: CSPResNet
  82. neck: CustomCSPPAN
  83. yolo_head: PPYOLOEHead
  84. post_process: ~
  85. CSPResNet:
  86. layers: [3, 6, 6, 3]
  87. channels: [64, 128, 256, 512, 1024]
  88. return_idx: [1, 2, 3]
  89. use_large_stem: true
  90. use_alpha: True
  91. CustomCSPPAN:
  92. out_channels: [768, 384, 192]
  93. stage_num: 1
  94. block_num: 3
  95. act: 'swish'
  96. spp: true
  97. PPYOLOEHead:
  98. fpn_strides: [32, 16, 8]
  99. grid_cell_scale: 5.0
  100. grid_cell_offset: 0.5
  101. static_assigner_epoch: 30
  102. use_varifocal_loss: true
  103. loss_weight: {class: 1.0, iou: 2.5, dfl: 0.5}
  104. static_assigner:
  105. name: ATSSAssigner
  106. topk: 9
  107. assigner:
  108. name: TaskAlignedAssigner
  109. topk: 13
  110. alpha: 1.0
  111. beta: 6.0
  112. nms:
  113. name: MultiClassNMS
  114. nms_top_k: 1000
  115. keep_top_k: 300
  116. score_threshold: 0.01
  117. nms_threshold: 0.7
  118. # Optimizer
  119. LearningRate:
  120. base_lr: 0.0001
  121. schedulers:
  122. - name: CosineDecay
  123. max_epochs: 300
  124. - name: LinearWarmup
  125. start_factor: 0.
  126. steps: 100
  127. OptimizerBuilder:
  128. optimizer:
  129. momentum: 0.9
  130. type: Momentum
  131. regularizer:
  132. factor: 0.0005
  133. type: L2
  134. # Export
  135. export:
  136. post_process: true
  137. nms: true
  138. benchmark: false
  139. fuse_conv_bn: false