Highlights

• Support CrowdDet and EIoU Loss
• Support training detection models in Detectron2
• Refactor Fast R-CNN
• Note: In this version, we upgrade the minimum version requirement of MMEngine to 0.3.0 to use ignore_key of ConcatDataset for training VOC datasets (#9058)

New Features

• Support CrowdDet (#8744)
• Support training detection models in Detectron2 with examples of Mask R-CNN, Faster R-CNN, and RetinaNet (#8672)
• Support EIoU Loss (#9086)

Bug Fixes

• Fix XMLDataset image size error (#9216)
• Fix bugs of empty_instances when predicting without nms in roi_head (#9015)
• Fix the config file of DETR (#9158)
• Fix SOLOv2 cannot dealing with empty gt image (#9192)
• Fix inference demo (#9153)
• Add ignore_key in VOC ConcatDataset (#9058)
• Fix dumping results issue in test scripts. (#9241)
• Fix configs of training coco subsets on MMDet 3.x (#9225)
• Fix corner2hbox of HorizontalBoxes for supporting empty bboxes (#9140)

Improvements

• Refactor Fast R-CNN (#9132)
• Clean requirements of mmcv-full due to SyncBN (#9207)
• Support training detection models in detectron2 (#8672)
• Add box_type support for DynamicSoftLabelAssigner (#9179)
• Make scipy as a default dependency in runtime (#9187)
• Update eval_metric (#9062)
• Add seg_map_suffix in BaseDetDataset (#9088)

New Contributors

• @Wwupup made their first contribution in https://github.com/open-mmlab/mmdetection/pull/9086
• @sanbuphy made their first contribution in https://github.com/open-mmlab/mmdetection/pull/9153
• @cxiang26 made their first contribution in https://github.com/open-mmlab/mmdetection/pull/9158
• @JosonChan1998 made their first contribution in https://github.com/open-mmlab/mmdetection/pull/9225

Contributors

A total of 13 developers contributed to this release.

Thanks @wanghonglie, @Wwupup, @sanbuphy, @BIGWangYuDong, @liuyanyi, @cxiang26, @jbwang1997, @ZwwWayne, @yuyoujiang, @RangiLyu, @hhaAndroid, @JosonChan1998, @Czm369

Full Changelog: https://github.com/open-mmlab/mmdetection/compare/v3.0.0rc2...v3.0.0rc3