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MMDetection3D V0.6.0 Release
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@ZwwWayne ZwwWayne released this 20 Sep 13:17
v0.6.0
1cd5048
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Highlights

  • Support new methods H3DNet, 3DSSD, CenterPoint.
  • Support new dataset Waymo (with PointPillars baselines) and 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 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 and release models on ScanNet dataset (#53, #58, #105)
  • Support Fusion Point Sampling used in 3DSSD (#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 (#96)
  • Support 3DSSD and release models on KITTI dataset (#83, #100, #104)
  • Support CenterPoint and release models on nuScenes dataset (#49, #92)
  • Support Waymo 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)
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