faster_rcnn_r50.yml 1.2 KB

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