MMDetection3D对三维数据进行检测

<div align="center"> <img src="resources/mmdet3d-logo.png" width="600"/> <div>&nbsp;</div> <div align="center"> <b><font size="5">OpenMMLab website</font></b> ^{<a href="https://openmmlab.com"> <i><font size="4">HOT</font></i> </a>} &nbsp;&nbsp;&nbsp;&nbsp; <b><font size="5">OpenMMLab platform</font></b> ^{<a href="https://platform.openmmlab.com"> <i><font size="4">TRY IT OUT</font></i> </a>} </div> <div>&nbsp;</div> [](https://pypi.org/project/mmdet3d) [](https://mmdetection3d.readthedocs.io/en/latest/) [](https://github.com/open-mmlab/mmdetection3d/actions) [](https://codecov.io/gh/open-mmlab/mmdetection3d) [](https://github.com/open-mmlab/mmdetection3d/blob/main/LICENSE) [](https://github.com/open-mmlab/mmdetection3d/issues) [](https://github.com/open-mmlab/mmdetection3d/issues) [📘Documentation](https://mmdetection3d.readthedocs.io/en/latest/) | [🛠️Installation](https://mmdetection3d.readthedocs.io/en/latest/get_started.html) | [👀Model Zoo](https://mmdetection3d.readthedocs.io/en/latest/model_zoo.html) | [🆕Update News](https://mmdetection3d.readthedocs.io/en/latest/notes/changelog.html) | [🚀Ongoing Projects](https://github.com/open-mmlab/mmdetection3d/projects) | [🤔Reporting Issues](https://github.com/open-mmlab/mmdetection3d/issues/new/choose) </div> <div align="center"> English | [简体中文](README_zh-CN.md) </div> <div align="center"> <a href="https://openmmlab.medium.com/" style="text-decoration:none;"> <img src="https://user-images.githubusercontent.com/25839884/219255827-67c1a27f-f8c5-46a9-811d-5e57448c61d1.png" width="3%" alt="" /></a> <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> <a href="https://discord.com/channels/1037617289144569886/1046608014234370059" style="text-decoration:none;"> <img src="https://user-images.githubusercontent.com/25839884/218347213-c080267f-cbb6-443e-8532-8e1ed9a58ea9.png" width="3%" alt="" /></a> <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> <a href="https://twitter.com/OpenMMLab" style="text-decoration:none;"> <img src="https://user-images.githubusercontent.com/25839884/218346637-d30c8a0f-3eba-4699-8131-512fb06d46db.png" width="3%" alt="" /></a> <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> <a href="https://www.youtube.com/openmmlab" style="text-decoration:none;"> <img src="https://user-images.githubusercontent.com/25839884/218346691-ceb2116a-465a-40af-8424-9f30d2348ca9.png" width="3%" alt="" /></a> <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> <a href="https://space.bilibili.com/1293512903" style="text-decoration:none;"> <img src="https://user-images.githubusercontent.com/25839884/219026751-d7d14cce-a7c9-4e82-9942-8375fca65b99.png" width="3%" alt="" /></a> <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> <a href="https://www.zhihu.com/people/openmmlab" style="text-decoration:none;"> <img src="https://user-images.githubusercontent.com/25839884/219026120-ba71e48b-6e94-4bd4-b4e9-b7d175b5e362.png" width="3%" alt="" /></a> </div> ## Introduction MMDetection3D is an open source object detection toolbox based on PyTorch, towards the next-generation platform for general 3D detection. It is a part of the [OpenMMLab](https://openmmlab.com/) project. The main branch works with **PyTorch 1.8+**.  <details open> <summary>Major features</summary> - **Support multi-modality/single-modality detectors out of box** It directly supports multi-modality/single-modality detectors including MVXNet, VoteNet, PointPillars, etc. - **Support indoor/outdoor 3D detection out of box** It directly supports popular indoor and outdoor 3D detection datasets, including ScanNet, SUNRGB-D, Waymo, nuScenes, Lyft, and KITTI. For nuScenes dataset, we also support [nuImages dataset](https://github.com/open-mmlab/mmdetection3d/tree/main/configs/nuimages). - **Natural integration with 2D detection** All the about **300+ models, methods of 40+ papers**, and modules supported in [MMDetection](https://github.com/open-mmlab/mmdetection/blob/3.x/docs/en/model_zoo.md) can be trained or used in this codebase. - **High efficiency** It trains faster than other codebases. The main results are as below. Details can be found in [benchmark.md](./docs/en/notes/benchmarks.md). We compare the number of samples trained per second (the higher, the better). The models that are not supported by other codebases are marked by `✗`. | Methods | MMDetection3D | [OpenPCDet](https://github.com/open-mmlab/OpenPCDet) | [votenet](https://github.com/facebookresearch/votenet) | [Det3D](https://github.com/poodarchu/Det3D) | | :-----------------: | :-----------: | :--------------------------------------------------: | :----------------------------------------------------: | :-----------------------------------------: | | VoteNet | 358 | ✗ | 77 | ✗ | | PointPillars-car | 141 | ✗ | ✗ | 140 | | PointPillars-3class | 107 | 44 | ✗ | ✗ | | SECOND | 40 | 30 | ✗ | ✗ | | Part-A2 | 17 | 14 | ✗ | ✗ | </details> Like [MMDetection](https://github.com/open-mmlab/mmdetection) and [MMCV](https://github.com/open-mmlab/mmcv), MMDetection3D can also be used as a library to support different projects on top of it. ## What's New ### Highlight In version 1.4, MMDetecion3D refactors the Waymo dataset and accelerates the preprocessing, training/testing setup, and evaluation of Waymo dataset. We also extends the support for camera-based, such as Monocular and BEV, 3D object detection models on Waymo. A detailed description of the Waymo data information is provided [here](https://mmdetection3d.readthedocs.io/en/latest/advanced_guides/datasets/waymo.html). Besides, in version 1.4, MMDetection3D provides [Waymo-mini](https://download.openmmlab.com/mmdetection3d/data/waymo_mmdet3d_after_1x4/waymo_mini.tar.gz) to help community users get started with Waymo and use it for quick iterative development. **v1.4.0** was released in 8/1/2024： - Support the training of [DSVT](<(https://arxiv.org/abs/2301.06051)>) in `projects` - Support [Nerf-Det](https://arxiv.org/abs/2307.14620) in `proj