mask_rcnn_r50.yml 1.6 KB

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  1. architecture: MaskRCNN
  2. pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
  3. MaskRCNN:
  4. backbone: ResNet
  5. rpn_head: RPNHead
  6. bbox_head: BBoxHead
  7. mask_head: MaskHead
  8. # post process
  9. bbox_post_process: BBoxPostProcess
  10. mask_post_process: MaskPostProcess
  11. ResNet:
  12. # index 0 stands for res2
  13. depth: 50
  14. norm_type: bn
  15. freeze_at: 0
  16. return_idx: [2]
  17. num_stages: 3
  18. RPNHead:
  19. anchor_generator:
  20. aspect_ratios: [0.5, 1.0, 2.0]
  21. anchor_sizes: [32, 64, 128, 256, 512]
  22. strides: [16]
  23. rpn_target_assign:
  24. batch_size_per_im: 256
  25. fg_fraction: 0.5
  26. negative_overlap: 0.3
  27. positive_overlap: 0.7
  28. use_random: True
  29. train_proposal:
  30. min_size: 0.0
  31. nms_thresh: 0.7
  32. pre_nms_top_n: 12000
  33. post_nms_top_n: 2000
  34. topk_after_collect: False
  35. test_proposal:
  36. min_size: 0.0
  37. nms_thresh: 0.7
  38. pre_nms_top_n: 6000
  39. post_nms_top_n: 1000
  40. BBoxHead:
  41. head: Res5Head
  42. roi_extractor:
  43. resolution: 14
  44. sampling_ratio: 0
  45. aligned: True
  46. bbox_assigner: BBoxAssigner
  47. with_pool: true
  48. BBoxAssigner:
  49. batch_size_per_im: 512
  50. bg_thresh: 0.5
  51. fg_thresh: 0.5
  52. fg_fraction: 0.25
  53. use_random: True
  54. BBoxPostProcess:
  55. decode: RCNNBox
  56. nms:
  57. name: MultiClassNMS
  58. keep_top_k: 100
  59. score_threshold: 0.05
  60. nms_threshold: 0.5
  61. MaskHead:
  62. head: MaskFeat
  63. roi_extractor:
  64. resolution: 14
  65. sampling_ratio: 0
  66. aligned: True
  67. mask_assigner: MaskAssigner
  68. share_bbox_feat: true
  69. MaskFeat:
  70. num_convs: 0
  71. out_channel: 256
  72. MaskAssigner:
  73. mask_resolution: 14
  74. MaskPostProcess:
  75. binary_thresh: 0.5