detectors_cascade-rcnn_r50_1x_coco.py 1.0 KB

1234567891011121314151617181920212223242526272829303132
  1. _base_ = [
  2. '../_base_/models/cascade-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. type='DetectoRS_ResNet',
  9. conv_cfg=dict(type='ConvAWS'),
  10. sac=dict(type='SAC', use_deform=True),
  11. stage_with_sac=(False, True, True, True),
  12. output_img=True),
  13. neck=dict(
  14. type='RFP',
  15. rfp_steps=2,
  16. aspp_out_channels=64,
  17. aspp_dilations=(1, 3, 6, 1),
  18. rfp_backbone=dict(
  19. rfp_inplanes=256,
  20. type='DetectoRS_ResNet',
  21. depth=50,
  22. num_stages=4,
  23. out_indices=(0, 1, 2, 3),
  24. frozen_stages=1,
  25. norm_cfg=dict(type='BN', requires_grad=True),
  26. norm_eval=True,
  27. conv_cfg=dict(type='ConvAWS'),
  28. sac=dict(type='SAC', use_deform=True),
  29. stage_with_sac=(False, True, True, True),
  30. pretrained='torchvision://resnet50',
  31. style='pytorch')))