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Release v1.0.0rc4
Release v1.0.0rc4
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.github/workflows/build.yml

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apt-get update && apt-get install -y ffmpeg libsm6 git ninja-build libglib2.0-0 libsm6 libxrender-dev python${{matrix.python-version}}-dev
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apt-get clean
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rm -rf /var/lib/apt/lists/*
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- name: Install Pillow
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run: python -m pip install Pillow==6.2.2
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if: ${{matrix.torchvision < 0.5}}
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- name: Install PyTorch
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run: python -m pip install numpy==1.19.5 torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
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- name: Install mmdet3d dependencies
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run: |
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python -m pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu101/${{matrix.torch_version}}/index.html
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python -m pip install mmcv-full==1.6.0 -f https://download.openmmlab.com/mmcv/dist/cu101/${{matrix.torch_version}}/index.html
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python -m pip install mmdet
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python -m pip install mmsegmentation
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python -m pip install -r requirements.txt

.github/workflows/lint.yml

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- name: Install linting dependencies
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run: |
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python -m pip install --upgrade pip
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pip install flake8 isort yapf interrogate
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pip install flake8==3.8.3 isort==5.10.1 yapf==v0.30.0 interrogate
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- name: Lint with flake8
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run: flake8 .
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- name: Lint with isort

.github/workflows/test_mim.yml

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name: test-mim
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on:
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push:
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paths:
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- 'model-index.yml'
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- 'configs/**'
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pull_request:
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paths:
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- 'model-index.yml'
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- 'configs/**'
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concurrency:
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group: ${{ github.workflow }}-${{ github.ref }}
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cancel-in-progress: true
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jobs:
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build_cpu:
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runs-on: ubuntu-18.04
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strategy:
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matrix:
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python-version: [3.7]
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torch: [1.8.0]
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include:
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- torch: 1.8.0
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torch_version: torch1.8
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torchvision: 0.9.0
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.python-version }}
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- name: Upgrade pip
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run: pip install pip --upgrade
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- name: Install Pillow
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run: pip install Pillow==6.2.2
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if: ${{matrix.torchvision == '0.4.2'}}
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- name: Install PyTorch
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run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
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- name: Install openmim
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run: pip install openmim
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- name: Build and install
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run: rm -rf .eggs && mim install -e .
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- name: test commands of mim
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run: mim search mmdet3d

.pre-commit-config.yaml

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hooks:
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- id: codespell
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- repo: https://github.com/executablebooks/mdformat
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rev: 0.7.14
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rev: 0.7.9
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hooks:
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- id: mdformat
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args: [ "--number" ]
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additional_dependencies:
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- mdformat-gfm
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- mdformat-openmmlab
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- mdformat_frontmatter
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- linkify-it-py
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- repo: https://github.com/myint/docformatter

README.md

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[![codecov](https://codecov.io/gh/open-mmlab/mmdetection3d/branch/master/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmdetection3d)
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[![license](https://img.shields.io/github/license/open-mmlab/mmdetection3d.svg)](https://github.com/open-mmlab/mmdetection3d/blob/master/LICENSE)
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**News**: We released the codebase v1.0.0rc3.
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**News**: We released the codebase v1.0.0rc4.
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Note: We are going through large refactoring to provide simpler and more unified usage of many modules.
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| Methods | MMDetection3D | [OpenPCDet](https://github.com/open-mmlab/OpenPCDet) | [votenet](https://github.com/facebookresearch/votenet) | [Det3D](https://github.com/poodarchu/Det3D) |
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| :-----------------: | :-----------: | :--------------------------------------------------: | :----------------------------------------------------: | :-----------------------------------------: |
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| VoteNet | 358 | × | 77 | × |
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| PointPillars-car | 141 | × | × | 140 |
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| PointPillars-3class | 107 | 44 | × | × |
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| SECOND | 40 | 30 | × | × |
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| Part-A2 | 17 | 14 | × | × |
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| VoteNet | 358 | | 77 | |
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| PointPillars-car | 141 | | | 140 |
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| PointPillars-3class | 107 | 44 | | |
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| SECOND | 40 | 30 | | |
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| Part-A2 | 17 | 14 | | |
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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.
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## Changelog
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v1.0.0rc3 was released in 8/6/2022.
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v1.0.0rc4 was released in 8/8/2022.
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- Support [SA-SSD](https://openaccess.thecvf.com/content_CVPR_2020/papers/He_Structure_Aware_Single-Stage_3D_Object_Detection_From_Point_Cloud_CVPR_2020_paper.pdf)
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- Support [FCAF3D](https://arxiv.org/pdf/2112.00322.pdf)
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Please refer to [changelog.md](docs/en/changelog.md) for details and release history.
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<li><a href="configs/regnet">RegNet (CVPR'2020)</a></li>
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<li><a href="configs/dgcnn">DGCNN (TOG'2019)</a></li>
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<li>DLA (CVPR'2018)</li>
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<li>MinkResNet (CVPR'2019)</li>
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</ul>
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</td>
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<td>
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</ul>
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</td>
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</tr>
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</td>
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</tr>
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</tbody>
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</table>
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<li><a href="configs/votenet">VoteNet (ICCV'2019)</a></li>
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<li><a href="configs/h3dnet">H3DNet (ECCV'2020)</a></li>
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<li><a href="configs/groupfree3d">Group-Free-3D (ICCV'2021)</a></li>
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<li><a href="configs/fcaf3d">FCAF3D (ECCV'2022)</a></li>
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</ul>
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</td>
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<td>
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</tbody>
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</table>
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| | ResNet | ResNeXt | SENet | PointNet++ | DGCNN | HRNet | RegNetX | Res2Net | DLA |
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| ------------- | :----: | :-----: | :---: | :--------: | :---: | :---: | :-----: | :-----: | :-: |
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| SECOND ||||||||||
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| PointPillars ||||||||||
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| FreeAnchor ||||||||||
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| VoteNet ||||||||||
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| H3DNet ||||||||||
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| 3DSSD ||||||||||
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| Part-A2 ||||||||||
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| MVXNet ||||||||||
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| CenterPoint ||||||||||
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| SSN ||||||||||
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| ImVoteNet ||||||||||
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| FCOS3D ||||||||||
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| PointNet++ ||||||||||
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| Group-Free-3D ||||||||||
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| ImVoxelNet ||||||||||
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| PAConv ||||||||||
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| DGCNN ||||||||||
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| SMOKE ||||||||||
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| PGD ||||||||||
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| MonoFlex ||||||||||
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| SA-SSD ||||||||||
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| | ResNet | PointNet++ | SECOND | DGCNN | RegNetX | DLA | MinkResNet |
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| :-----------: | :----: | :--------: | :----: | :---: | :-----: | :-: | :--------: |
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| SECOND ||||||||
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| PointPillars ||||||||
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| FreeAnchor ||||||||
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| VoteNet ||||||||
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| H3DNet ||||||||
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| 3DSSD ||||||||
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| Part-A2 ||||||||
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| MVXNet ||||||||
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| CenterPoint ||||||||
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| SSN ||||||||
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| ImVoteNet ||||||||
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| FCOS3D ||||||||
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| PointNet++ ||||||||
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| Group-Free-3D ||||||||
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| ImVoxelNet ||||||||
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| PAConv ||||||||
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| DGCNN ||||||||
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| SMOKE ||||||||
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| PGD ||||||||
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| MonoFlex ||||||||
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| SA-SSD ||||||||
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| FCAF3D ||||||||
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**Note:** All the about **300+ models, methods of 40+ papers** in 2D detection supported by [MMDetection](https://github.com/open-mmlab/mmdetection/blob/master/docs/en/model_zoo.md) can be trained or used in this codebase.
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