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README.md 1.5 kB

2 years ago
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  1. # Strong Baselines
  2. We train Mask R-CNN with large-scale jittor and longer schedule as strong baselines.
  3. The modifications follow those in [Detectron2](https://github.com/facebookresearch/detectron2/tree/master/configs/new_baselines).
  4. ## Results and models
  5. | Backbone | Style | Lr schd | Mem (GB) | Inf time (fps) | box AP | mask AP | Config | Download |
  6. | :-------------: | :-----: | :-----: | :------: | :------------: | :----: | :-----: | :------: | :--------: |
  7. | R-50-FPN | pytorch | 50e | | | | | [config](./mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_lsj_50e_coco.py) | [model]() | [log]() |
  8. | R-50-FPN | pytorch | 100e | | | | | [config](./mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_lsj_100e_coco.py) | [model]() | [log]() |
  9. | R-50-FPN | caffe | 100e | | | 44.7 | 40.4 | [config](./mask_rcnn_r50_caffe_fpn_syncbn-all_rpn-2conv_lsj_100e_coco.py) | [model]() | [log]() |
  10. | R-50-FPN | caffe | 400e | | | | | [config](./mask_rcnn_r50_caffe_fpn_syncbn-all_rpn-2conv_lsj_400e_coco.py) | [model]() | [log]() |
  11. ## Notice
  12. When using large-scale jittering, there are sometimes empty proposals in the box and mask heads during training.
  13. This requires MMSyncBN that allows empty tensors. Therefore, please use mmcv-full>=1.3.14 to train models supported in this directory.

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