changelog.md

## Changelog

### v0.6.0 (20/9/2020)

#### Highlights

- Support new methods [H3DNet](https://arxiv.org/abs/2006.05682), [3DSSD](https://arxiv.org/abs/2002.10187), [CenterPoint](https://arxiv.org/abs/2006.11275).
- Support new dataset [Waymo](https://waymo.com/open/) (with PointPillars baselines) and [nuImages](https://www.nuscenes.org/nuimages) (with Mask R-CNN and Cascade Mask R-CNN baselines).
- Support Batch Inference
- Support Pytorch 1.6
- Start to publish `mmdet3d` package to PyPI since v0.5.0. You can use mmdet3d through `pip install mmdet3d`.

#### Backwards Incompatible Changes

- Support Batch Inference (#95, #103, #116): MMDetection3D v0.6.0 migrates to support batch inference based on MMDetection >= v2.4.0. This change influences all the test APIs in MMDetection3D and downstream codebases.
- Start to use collect environment function from MMCV (#113): MMDetection3D v0.6.0 migrates to use `collect_env` function in MMCV.
`get_compiler_version` and `get_compiling_cuda_version` compiled in `mmdet3d.ops.utils` are removed. Please import these two functions from `mmcv.ops`.

#### Bug Fixes

- Rename CosineAnealing to CosineAnnealing (#57)
- Fix device inconsistant bug in 3D IoU computation (#69)
- Fix a minor bug in json2csv of lyft dataset (#78)
- Add missed test data for pointnet modules (#85)
- Fix `use_valid_flag` bug in `CustomDataset` (#106)

#### New Features

- Support [nuImages](https://www.nuscenes.org/nuimages) dataset by converting them into coco format and release Mask R-CNN and Cascade Mask R-CNN baseline models (#91, #94)
- Support to publish to PyPI in github-action (#17, #19, #25, #39, #40)
- Support CBGSDataset and make it generally applicable to all the supported datasets (#75, #94)
- Support [H3DNet](https://arxiv.org/abs/2006.05682) and release models on ScanNet dataset (#53, #58, #105)
- Support Fusion Point Sampling used in [3DSSD](https://arxiv.org/abs/2002.10187) (#66)
- Add `BackgroundPointsFilter` to filter background points in data pipeline (#84)
- Support pointnet2 with multi-scale grouping in backbone and refactor pointnets (#82)
- Support dilated ball query used in [3DSSD](https://arxiv.org/abs/2002.10187) (#96)
- Support [3DSSD](https://arxiv.org/abs/2002.10187) and release models on KITTI dataset (#83, #100, #104)
- Support [CenterPoint](https://arxiv.org/abs/2006.11275) and release models on nuScenes dataset (#49, #92)
- Support [Waymo](https://waymo.com/open/) dataset and release PointPillars baseline models (#118)
- Allow `LoadPointsFromMultiSweeps` to pad empty sweeps and select multiple sweeps randomly (#67)

#### Improvements

- Fix all warnings and bugs in Pytorch 1.6.0 (#70, #72)
- Update issue templates (#43)
- Update unit tests (#20, #24, #30)
- Update documentation for using `ply` format point cloud data (#41)
- Use points loader to load point cloud data in ground truth (GT) samplers (#87)
- Unify version file of OpenMMLab projects by using `version.py` (#112)
- Remove unnecessary data preprocessing commands of SUN RGB-D dataset (#110)

### v0.5.0 (9/7/2020)

MMDetection3D is released.