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‎.gitignore

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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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*.ipynb
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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.hypothesis/
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.pytest_cache/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# pyenv
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.python-version
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# celery beat schedule file
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celerybeat-schedule
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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# cython generated cpp
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mmdet3d/ops/nms/src/soft_nms_cpu.cpp
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mmdet3d/version.py
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data
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.vscode
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.idea
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# custom
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*.pkl
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*.pkl.json
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*.log.json
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work_dirs/
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exps/
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*~
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# Pytorch
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*.pth
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# demo
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*.jpg
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*.png

‎.gitlab-ci.yml

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variables:
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PYTORCH_IMAGE: registry.sensetime.com/eig-research/pytorch:pytorch1.3.1-cuda10.1-devel
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stages:
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- linting
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- test
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before_script:
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- echo $PATH
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- gcc --version
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- nvcc --version
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- python --version
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- pip --version
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- python -c "import torch; print(torch.__version__)"
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.linting_template: &linting_template_def
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stage: linting
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script:
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- pip install flake8 yapf isort
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- flake8 .
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- isort -rc --check-only --diff mmdet3d/ tools/ tests/
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- yapf -r -d mmdet3d/ tools/ tests/ configs/
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.test_template: &test_template_def
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stage: test
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script:
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- echo "Start building..."
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- conda install av -c conda-forge -y
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- pip install git+https://github.com/open-mmlab/mmdetection.git@v2.0
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- python -c "import mmdet; print(mmdet.__version__)"
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- pip install -v -e .[all]
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- python -c "import mmdet3d; print(mmdet3d.__version__)"
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- echo "Start testing..."
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- coverage run --branch --source mmdet3d -m pytest tests/
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- coverage report -m
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linting:pytorch1.3-cuda10:
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image: $PYTORCH_IMAGE
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<<: *linting_template_def
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test:pytorch1.3-cuda10:
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image: $PYTORCH_IMAGE
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<<: *test_template_def

‎.isort.cfg

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[isort]
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line_length = 79
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multi_line_output = 0
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known_standard_library = setuptools
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known_first_party = mmdet,mmdet3d
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known_third_party = Cython,cv2,mmcv,numba,numpy,nuscenes,pycocotools,pyquaternion,scipy,shapely,six,skimage,terminaltables,torch,torchvision
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no_lines_before = STDLIB,LOCALFOLDER
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default_section = THIRDPARTY

‎.pre-commit-config.yaml

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repos:
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- repo: https://gitlab.com/pycqa/flake8.git
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rev: 3.7.9
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hooks:
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- id: flake8
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- repo: https://github.com/asottile/seed-isort-config
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rev: v2.1.0
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hooks:
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- id: seed-isort-config
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- repo: https://github.com/timothycrosley/isort
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rev: 4.3.21
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hooks:
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- id: isort
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- repo: https://github.com/pre-commit/mirrors-yapf
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rev: v0.29.0
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hooks:
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- id: yapf
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- repo: https://github.com/pre-commit/pre-commit-hooks
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rev: v2.5.0
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hooks:
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- id: trailing-whitespace
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- id: check-yaml
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- id: end-of-file-fixer
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- id: requirements-txt-fixer
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- id: double-quote-string-fixer
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- id: fix-encoding-pragma
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args: ["--remove"]

‎.style.yapf

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[style]
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BASED_ON_STYLE = pep8
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BLANK_LINE_BEFORE_NESTED_CLASS_OR_DEF = true
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SPLIT_BEFORE_EXPRESSION_AFTER_OPENING_PAREN = true

‎.travis.yml

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dist: bionic # ubuntu 18.04
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language: python
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python:
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- "3.5"
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- "3.6"
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- "3.7"
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env: CUDA=10.1.105-1 CUDA_SHORT=10.1 UBUNTU_VERSION=ubuntu1804 FORCE_CUDA=1
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cache: pip
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# Ref to CUDA installation in Travis: https://github.com/jeremad/cuda-travis
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before_install:
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- INSTALLER=cuda-repo-${UBUNTU_VERSION}_${CUDA}_amd64.deb
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- wget http://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/${INSTALLER}
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- sudo dpkg -i ${INSTALLER}
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- wget https://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/7fa2af80.pub
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- sudo apt-key add 7fa2af80.pub
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- sudo apt update -qq
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- sudo apt install -y cuda-${CUDA_SHORT/./-} cuda-cufft-dev-${CUDA_SHORT/./-}
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- sudo apt clean
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- CUDA_HOME=/usr/local/cuda-${CUDA_SHORT}
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- LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${CUDA_HOME}/include:${LD_LIBRARY_PATH}
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- PATH=${CUDA_HOME}/bin:${PATH}
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install:
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- pip install Pillow==6.2.2 # remove this line when torchvision>=0.5
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- pip install torch==1.2 torchvision==0.4.0 # TODO: fix CI for pytorch>1.2
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- pip install "git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI"
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- pip install -r requirements.txt
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before_script:
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- flake8 .
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- isort -rc --check-only --diff mmdet3d/ tools/ tests/
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- yapf -r -d --style .style.yapf mmdet3d/ tools/ tests/ configs/
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script:
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- python setup.py check -m -s
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- python setup.py build_ext --inplace
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- coverage run --source mmdet3d -m py.test -v --xdoctest-modules tests mmdet3d
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after_success:
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- coverage report

‎README.md

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# MMDetection3D
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## Introduction
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The master branch works with **PyTorch 1.1** or higher.
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mmdetection3d is an open source 3D object detection toolbox based on PyTorch. It is
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a part of the open-mmlab project developed by [Multimedia Laboratory, CUHK](http://mmlab.ie.cuhk.edu.hk/).
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### Major features
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## License
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This project is released under the [Apache 2.0 license](LICENSE).
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## Updates
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v0.0.1 (07/08/2019)
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- the project is initiated
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## Benchmark and model zoo
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Supported methods and backbones are shown in the below table.
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Results and models are available in the [Model zoo](MODEL_ZOO.md).
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## Installation
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Please refer to [INSTALL.md](INSTALL.md) for installation and dataset preparation.
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## Get Started
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Please see [GETTING_STARTED.md](GETTING_STARTED.md) for the basic usage of MMDetection.
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## Contributing
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We appreciate all contributions to improve MMDetection3D. Please refer to [CONTRIBUTING.md](CONTRIBUTING.md) for the contributing guideline.
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## Acknowledgement
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MMDetection3D is an open source project that is contributed by researchers and engineers from various colleges and companies. We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks.
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We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new detectors.
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## Citation
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## Contact
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This repo is currently maintained by Wenwei Zhang ([@ZwwWayne](http://github.com/ZwwWayne)).

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