sabl-faster-rcnn_r101_fpn_1x_coco.py 1.3 KB

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  1. _base_ = [
  2. '../_base_/models/faster-rcnn_r50_fpn.py',
  3. '../_base_/datasets/coco_detection.py',
  4. '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
  5. ]
  6. model = dict(
  7. backbone=dict(
  8. depth=101,
  9. init_cfg=dict(type='Pretrained',
  10. checkpoint='torchvision://resnet101')),
  11. roi_head=dict(
  12. bbox_head=dict(
  13. _delete_=True,
  14. type='SABLHead',
  15. num_classes=80,
  16. cls_in_channels=256,
  17. reg_in_channels=256,
  18. roi_feat_size=7,
  19. reg_feat_up_ratio=2,
  20. reg_pre_kernel=3,
  21. reg_post_kernel=3,
  22. reg_pre_num=2,
  23. reg_post_num=1,
  24. cls_out_channels=1024,
  25. reg_offset_out_channels=256,
  26. reg_cls_out_channels=256,
  27. num_cls_fcs=1,
  28. num_reg_fcs=0,
  29. reg_class_agnostic=True,
  30. norm_cfg=None,
  31. bbox_coder=dict(
  32. type='BucketingBBoxCoder', num_buckets=14, scale_factor=1.7),
  33. loss_cls=dict(
  34. type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),
  35. loss_bbox_cls=dict(
  36. type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),
  37. loss_bbox_reg=dict(type='SmoothL1Loss', beta=0.1,
  38. loss_weight=1.0))))