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+# Installation
+
+We provide some tips for MMAction2 installation in this file.
+
+<!-- TOC -->
+
+- [Installation](#installation)
+  - [Requirements](#requirements)
+  - [Prepare environment](#prepare-environment)
+  - [Install MMAction2](#install-mmaction2)
+  - [Install with CPU only](#install-with-cpu-only)
+  - [Another option: Docker Image](#another-option-docker-image)
+  - [A from-scratch setup script](#a-from-scratch-setup-script)
+  - [Developing with multiple MMAction2 versions](#developing-with-multiple-mmaction2-versions)
+  - [Verification](#verification)
+
+<!-- TOC -->
+
+## Requirements
+
+- Linux (Windows is not officially supported)
+- Python 3.6+
+- PyTorch 1.3+
+- CUDA 9.2+ (If you build PyTorch from source, CUDA 9.0 is also compatible)
+- GCC 5+
+- [mmcv](https://github.com/open-mmlab/mmcv) 1.1.1+
+- Numpy
+- ffmpeg (4.2 is preferred)
+- [decord](https://github.com/dmlc/decord) (optional, 0.4.1+): Install CPU version by `pip install decord==0.4.1` and install GPU version from source
+- [PyAV](https://github.com/mikeboers/PyAV) (optional): `conda install av -c conda-forge -y`
+- [PyTurboJPEG](https://github.com/lilohuang/PyTurboJPEG) (optional): `pip install PyTurboJPEG`
+- [denseflow](https://github.com/open-mmlab/denseflow) (optional): See [here](https://github.com/innerlee/setup) for simple install scripts.
+- [moviepy](https://zulko.github.io/moviepy/) (optional): `pip install moviepy`. See [here](https://zulko.github.io/moviepy/install.html) for official installation.  **Note**(according to [this issue](https://github.com/Zulko/moviepy/issues/693)) that:
+  1. For Windows users, [ImageMagick](https://www.imagemagick.org/script/index.php) will not be automatically detected by MoviePy,
+    there is a need to modify `moviepy/config_defaults.py` file by providing the path to the ImageMagick binary called `magick`, like `IMAGEMAGICK_BINARY = "C:\\Program Files\\ImageMagick_VERSION\\magick.exe"`
+  2. For Linux users, there is a need to modify the `/etc/ImageMagick-6/policy.xml` file by commenting out
+    `<policy domain="path" rights="none" pattern="@*" />` to `<!-- <policy domain="path" rights="none" pattern="@*" /> -->`, if [ImageMagick](https://www.imagemagick.org/script/index.php) is not detected by `moviepy`.
+- [Pillow-SIMD](https://docs.fast.ai/performance.html#pillow-simd) (optional): Install it by the following scripts.
+
+```shell
+conda uninstall -y --force pillow pil jpeg libtiff libjpeg-turbo
+pip   uninstall -y         pillow pil jpeg libtiff libjpeg-turbo
+conda install -yc conda-forge libjpeg-turbo
+CFLAGS="${CFLAGS} -mavx2" pip install --upgrade --no-cache-dir --force-reinstall --no-binary :all: --compile pillow-simd
+conda install -y jpeg libtiff
+```
+
+:::{note}
+You need to run `pip uninstall mmcv` first if you have mmcv installed.
+If mmcv and mmcv-full are both installed, there will be `ModuleNotFoundError`.
+:::
+
+## Prepare environment
+
+a. Create a conda virtual environment and activate it.
+
+```shell
+conda create -n open-mmlab python=3.7 -y
+conda activate open-mmlab
+```
+
+b. Install PyTorch and torchvision following the [official instructions](https://pytorch.org/), e.g.,
+
+```shell
+conda install pytorch torchvision -c pytorch
+```
+
+:::{note}
+Make sure that your compilation CUDA version and runtime CUDA version match.
+You can check the supported CUDA version for precompiled packages on the [PyTorch website](https://pytorch.org/).
+
+`E.g.1` If you have CUDA 10.1 installed under `/usr/local/cuda` and would like to install PyTorch 1.5,
+you need to install the prebuilt PyTorch with CUDA 10.1.
+
+```shell
+conda install pytorch cudatoolkit=10.1 torchvision -c pytorch
+```
+
+`E.g.2` If you have CUDA 9.2 installed under `/usr/local/cuda` and would like to install PyTorch 1.3.1.,
+you need to install the prebuilt PyTorch with CUDA 9.2.
+
+```shell
+conda install pytorch=1.3.1 cudatoolkit=9.2 torchvision=0.4.2 -c pytorch
+```
+
+If you build PyTorch from source instead of installing the prebuilt package, you can use more CUDA versions such as 9.0.
+:::
+
+## Install MMAction2
+
+We recommend you to install MMAction2 with [MIM](https://github.com/open-mmlab/mim).
+
+```shell
+pip install git+https://github.com/open-mmlab/mim.git
+mim install mmaction2 -f https://github.com/open-mmlab/mmaction2.git
+```
+
+MIM can automatically install OpenMMLab projects and their requirements.
+
+Or, you can install MMAction2 manually:
+
+a. Install mmcv, we recommend you to install the pre-build mmcv as below.
+
+```shell
+pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html
+```
+
+Please replace ``{cu_version}`` and ``{torch_version}`` in the url to your desired one. For example, to install the latest ``mmcv-full`` with ``CUDA 11`` and ``PyTorch 1.7.0``, use the following command:
+
+```shell
+pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu110/torch1.7.0/index.html
+```
+
+See [here](https://github.com/open-mmlab/mmcv#installation) for different versions of MMCV compatible to different PyTorch and CUDA versions.
+
+Optionally you can choose to compile mmcv from source by the following command
+
+```shell
+git clone https://github.com/open-mmlab/mmcv.git
+cd mmcv
+MMCV_WITH_OPS=1 pip install -e .  # package mmcv-full, which contains cuda ops, will be installed after this step
+# OR pip install -e .  # package mmcv, which contains no cuda ops, will be installed after this step
+cd ..
+```
+
+Or directly run
+
+```shell
+pip install mmcv-full
+# alternative: pip install mmcv
+```
+
+**Important:** You need to run `pip uninstall mmcv` first if you have mmcv installed. If mmcv and mmcv-full are both installed, there will be `ModuleNotFoundError`.
+
+b. Clone the MMAction2 repository.
+
+```shell
+git clone https://github.com/open-mmlab/mmaction2.git
+cd mmaction2
+```
+
+c. Install build requirements and then install MMAction2.
+
+```shell
+pip install -r requirements/build.txt
+pip install -v -e .  # or "python setup.py develop"
+```
+
+If you build MMAction2 on macOS, replace the last command with
+
+```shell
+CC=clang CXX=clang++ CFLAGS='-stdlib=libc++' pip install -e .
+```
+
+d. Install mmdetection for spatial temporal detection tasks.
+
+This part is **optional** if you're not going to do spatial temporal detection.
+
+See [here](https://github.com/open-mmlab/mmdetection#installation) to install mmdetection.
+
+:::{note}
+
+1. The git commit id will be written to the version number with step b, e.g. 0.6.0+2e7045c. The version will also be saved in trained models.
+   It is recommended that you run step b each time you pull some updates from github. If C++/CUDA codes are modified, then this step is compulsory.
+
+2. Following the above instructions, MMAction2 is installed on `dev` mode, any local modifications made to the code will take effect without the need to reinstall it (unless you submit some commits and want to update the version number).
+
+3. If you would like to use `opencv-python-headless` instead of `opencv-python`,
+   you can install it before installing MMCV.
+
+4. If you would like to use `PyAV`, you can install it with `conda install av -c conda-forge -y`.
+
+5. Some dependencies are optional. Running `python setup.py develop` will only install the minimum runtime requirements.
+   To use optional dependencies like `decord`, either install them with `pip install -r requirements/optional.txt`
+   or specify desired extras when calling `pip` (e.g. `pip install -v -e .[optional]`,
+   valid keys for the `[optional]` field are `all`, `tests`, `build`, and `optional`) like `pip install -v -e .[tests,build]`.
+
+:::
+
+## Install with CPU only
+
+The code can be built for CPU only environment (where CUDA isn't available).
+
+In CPU mode you can run the demo/demo.py for example.
+
+## Another option: Docker Image
+
+We provide a [Dockerfile](/docker/Dockerfile) to build an image.
+
+```shell
+# build an image with PyTorch 1.6.0, CUDA 10.1, CUDNN 7.
+docker build -f ./docker/Dockerfile --rm -t mmaction2 .
+```
+
+**Important:** Make sure you've installed the [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker).
+
+Run it with command:
+
+```shell
+docker run --gpus all --shm-size=8g -it -v {DATA_DIR}:/mmaction2/data mmaction2
+```
+
+## A from-scratch setup script
+
+Here is a full script for setting up MMAction2 with conda and link the dataset path (supposing that your Kinetics-400 dataset path is $KINETICS400_ROOT).
+
+```shell
+conda create -n open-mmlab python=3.7 -y
+conda activate open-mmlab
+
+# install latest pytorch prebuilt with the default prebuilt CUDA version (usually the latest)
+conda install -c pytorch pytorch torchvision -y
+
+# install the latest mmcv or mmcv-full, here we take mmcv as example
+pip install mmcv
+
+# install mmaction2
+git clone https://github.com/open-mmlab/mmaction2.git
+cd mmaction2
+pip install -r requirements/build.txt
+python setup.py develop
+
+mkdir data
+ln -s $KINETICS400_ROOT data
+```
+
+## Developing with multiple MMAction2 versions
+
+The train and test scripts already modify the `PYTHONPATH` to ensure the script use the MMAction2 in the current directory.
+
+To use the default MMAction2 installed in the environment rather than that you are working with, you can remove the following line in those scripts.
+
+```shell
+PYTHONPATH="$(dirname $0)/..":$PYTHONPATH
+```
+
+## Verification
+
+To verify whether MMAction2 and the required environment are installed correctly,
+we can run sample python codes to initialize a recognizer and inference a demo video:
+
+```python
+import torch
+from mmaction.apis import init_recognizer, inference_recognizer
+
+config_file = 'configs/recognition/tsn/tsn_r50_video_inference_1x1x3_100e_kinetics400_rgb.py'
+device = 'cuda:0' # or 'cpu'
+device = torch.device(device)
+
+model = init_recognizer(config_file, device=device)
+# inference the demo video
+inference_recognizer(model, 'demo/demo.mp4')
+```