## Installation

There are two versions of MMCV:

- **mmcv-full**: comprehensive, with full features and various CPU and CUDA ops out of box. It takes longer time to build.
- **mmcv**: lite, without CPU and CUDA ops but all other features, similar to mmcv\<1.0.0. It is useful when you do not need those CUDA ops.

```{warning}
Do not install both versions in the same environment, otherwise you may encounter errors like `ModuleNotFound`. You need to uninstall one before installing the other. `Installing the full version is highly recommended if CUDA is avaliable`.
```

### Install mmcv-full

```{note}
- The following installation steps are for Linux and Windows platforms only. To install mmcv-full on macOS platform, please refer to [build mmcv-full from source](build.md#build-on-macos).
- To compile ONNX Runtime custom operators, please refer to [How to build custom operators for ONNX Runtime](../deployment/onnxruntime_op.md#how-to-build-custom-operators-for-onnx-runtime)
- To compile TensorRT customization, please refer to [How to build TensorRT plugins in MMCV](../deployment/tensorrt_plugin.md#how-to-build-tensorrt-plugins-in-mmcv)
```

Before installing mmcv-full, make sure that PyTorch has been successfully installed following the [PyTorch official installation guide](https://pytorch.org/get-started/locally/#start-locally). This can be verified using the following command

```bash
python -c 'import torch;print(torch.__version__)'
```

If version information is output, then PyTorch is installed.

#### Install with mim (recommended)

[mim](https://github.com/open-mmlab/mim) is the package management tool for the OpenMMLab projects, which makes it easy to install mmcv-full

```bash
pip install -U openmim
mim install mmcv-full
```

If you find that the above installation command does not use a pre-built package ending with `.whl` but a source package ending with `.tar.gz`, you may not have a pre-build package corresponding to the PyTorch or CUDA or mmcv-full version, in which case you can [build mmcv-full from source](build.md).

<details>
<summary>Installation log using pre-built packages</summary>

Looking in links: https://download.openmmlab.com/mmcv/dist/cu102/torch1.8.0/index.html<br />
Collecting mmcv-full<br />
<b>Downloading https://download.openmmlab.com/mmcv/dist/cu102/torch1.8.0/mmcv_full-1.6.1-cp38-cp38-manylinux1_x86_64.whl</b>

</details>

<details>
<summary>Installation log using source packages</summary>

Looking in links: https://download.openmmlab.com/mmcv/dist/cu102/torch1.8.0/index.html<br />
Collecting mmcv-full==1.6.0<br />
<b>Downloading mmcv-full-1.6.0.tar.gz</b>

</details>

To install a specific version of mmcv-full, for example, mmcv-full version 1.6.0, you can use the following command

```bash
mim install mmcv-full==1.6.0
```

:::{note}
If you would like to use `opencv-python-headless` instead of `opencv-python`,
e.g., in a minimum container environment or servers without GUI,
you can first install it before installing MMCV to skip the installation of `opencv-python`.

Alternatively, if it takes too long to install a dependency library, you can specify the pypi source

```bash
mim install mmcv-full -i https://pypi.tuna.tsinghua.edu.cn/simple
```

:::

You can run [check_installation.py](https://github.com/open-mmlab/mmcv/.dev_scripts/check_installation.py) to check the installation of mmcv-full after running the installation commands.

#### Install with pip

Use the following command to check the version of CUDA and PyTorch

```bash
python -c 'import torch;print(torch.__version__);print(torch.version.cuda)'
```

Select the appropriate installation command depending on the type of system, CUDA version, PyTorch version, and MMCV version

<html>
<body>
    <style>
      select {
          z-index: 1000;
          position: absolute;
          top: 10px;
          width: 6.7rem;
      }
      #select-container {
          position: relative;
          height: 30px;
      }
      #select-cmd {
          background-color: #f5f6f7;
          font-size: 14px;
          margin-top: 20px;
      }
      /* 让每一个都间隔1.3rem */
      #select-os {
          /* left: 1.375rem; */
          left: 0;
      }
      #select-cuda {
          /* left: 9.375rem;    9.375 = 1.375 + 6.7 + 1.3 */
          left: 8rem;
      }
      #select-torch {
          /* left: 17.375rem;    17.375 = 9.375 + 6.7 + 1.3 */
          left: 16rem;
      }
      #select-mmcv {
          /* left: 25.375rem;    25.375 = 17.375 + 6.7 + 1.3 */
          left: 24rem;
      }
    </style>
    <div id="select-container">
        <select
            onmousedown="handleSelectMouseDown(this.id)"
            onblur="handleSelectBlur(this.id)"
            onchange="changeOS(this.value)"
            id="select-os">
        </select>
        <select
            onmousedown="handleSelectMouseDown(this.id)"
            onblur="handleSelectBlur(this.id)"
            onchange="changeCUDA(this.value)"
            id="select-cuda">
        </select>
        <select
            onmousedown="handleSelectMouseDown(this.id)"
            onblur="handleSelectBlur(this.id)"
            onchange="changeTorch(this.value)"
            id="select-torch">
        </select>
        <select
            onmousedown="handleSelectMouseDown(this.id)"
            onblur="handleSelectBlur(this.id)"
            onchange="changeMMCV(this.value)"
            id="select-mmcv">
        </select>
    </div>
    <pre id="select-cmd"></pre>
</body>
<script>
    // 各个select当前的值
    let osVal, cudaVal, torchVal, mmcvVal;
    function changeMMCV(val) {
        mmcvVal = val;
        change("select-mmcv");
    }
    function changeTorch(val) {
        torchVal = val;
        change("select-torch");
    }
    function changeCUDA(val) {
        cudaVal = val;
        change("select-cuda");
    }
    function changeOS(val) {
        osVal = val;
        change("select-os");
    }
    // 控制size大小相关的几个方法
    function handleSelectMouseDown(id) {
        const dom = document.getElementById(id);
        if (!dom) return;
        const len = dom?.options?.length;
        if (len >= 9) {
            dom.size = 10;
            dom.style.zIndex = 100;
        }
    }
    function handleSelectClick() {
        const selects = Array.from(document.getElementsByTagName("select"));
        selects.forEach(select => {
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    }
    function handleSelectBlur(id) {
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            // 如果没有指定特定的id，那就直接把所有的select都设置成size = 1
            handleSelectClick();
            return;
        }
        dom.size = 1;
        dom.style.zIndex = 1;
    }
    function changeCmd() {
        const cmd = document.getElementById("select-cmd");
        let cmdString = "pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html";
        // e.g: pip install mmcv-full==1.6.0 -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9/index.html
        const cudaVersion = `${cudaVal === "cpu" ? cudaVal : `cu${cudaVal.split(".").join("")}`}`;
        const torchVersion = `torch${torchVal.substring(0, torchVal.length - 2)}`;
        cmdString = cmdString.replace("{cu_version}", cudaVersion).replace("{mmcv_version}", mmcvVal).replace("{torch_version}", torchVersion);
        cmd.textContent = cmdString;
    }
    // string数组去重
    function unique(arr) {
        if (!arr || !Array.isArray(arr)) return [];
        return [...new Set(arr)];
    }
    // 根据string数组生成option的DocumentFragment
    function genOptionFragment(data, id) {
        const name = id.includes("-")? id.split("-")[1] : id;
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            let text = `${name} ${option}`;
            if (name === "os" || option.toUpperCase() === "CPU") {
                text = `${option}`;
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            ele.textContent = text;
            // 添加value属性，方便下拉框选择时直接读到数据
            ele.value = option;
            // 添加点击事件监听
            ele.addEventListener('click', handleSelectClick);
            fragment.appendChild(ele);
        });
        return fragment;
    }
    // 在dom树中找到id对应的dom（select元素），并将生成的options添加到元素内
    function findAndAppend(data, id) {
        const fragment = genOptionFragment(data, id);
        const dom = document.getElementById(id);
        if (dom) dom.replaceChildren(fragment);
    }
    /**
     * change方法的重点在于
     * 1. 各个下拉框数据的联动
     *      OS ==> cuda ==> torch ==> mmcv
     * 2. 命令行的修改
    */
    function change(id) {
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        const idx = order.indexOf(id);
        if (idx === -1) return;
        const versionDetail = version[osVal];
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            // 根据os修改cuda
            let cuda = [];
            versionDetail.forEach(v => {
                cuda.push(v.cuda);
            });
            cuda = unique(cuda);
            cudaVal = cuda[0];
            findAndAppend(cuda, "select-cuda");
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        if (idx >= 2) {
            // 根据cuda修改torch
            const torch = [];
            versionDetail.forEach(v => {
                if (v.cuda === cudaVal) torch.push(v.torch);
            });
            torchVal = torch[0];
            findAndAppend(torch, "select-torch");
        }
        if (idx >= 1) {
            // 根据torch修改mmcv
            let mmcv = [];
            versionDetail.forEach(v => {
                if (v.cuda === cudaVal && v.torch === torchVal) mmcv = v.mmcv;
            });
            mmcvVal = mmcv[0];
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        const os = Object.keys(version);
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    window.onload = function () {
        const url = "../_static/version.json"
        // 申明一个XMLHttpRequest
        const request = new XMLHttpRequest();
        // 设置请求方法与路径
        request.open("get", url);
        // 不发送数据到服务器
        request.send(null);
        //XHR对象获取到返回信息后执行
        request.onload = function () {
            // 返回状态为200，即为数据获取成功
            if (request.status !== 200) return;
            const data = JSON.parse(request.responseText);
            window.version = data;
            init();
        }
    }
</script>
</html>

If you do not find a corresponding version in the dropdown box above, you probably do not have a pre-built package corresponding to the PyTorch or CUDA or mmcv-full version, at which point you can [build mmcv-full from source](build.md).

:::{note}
mmcv-full is only compiled on PyTorch 1.x.0 because the compatibility
usually holds between 1.x.0 and 1.x.1. If your PyTorch version is 1.x.1, you
can install mmcv-full compiled with PyTorch 1.x.0 and it usually works well.
For example, if your PyTorch version is 1.8.1, you can feel free to choose 1.8.x.
:::

:::{note}
If you would like to use `opencv-python-headless` instead of `opencv-python`,
e.g., in a minimum container environment or servers without GUI,
you can first install it before installing MMCV to skip the installation of `opencv-python`.

Alternatively, if it takes too long to install a dependency library, you can specify the pypi source

```bash
mim install mmcv-full -i https://pypi.tuna.tsinghua.edu.cn/simple
```

:::

You can run [check_installation.py](https://github.com/open-mmlab/mmcv/.dev_scripts/check_installation.py) to check the installation of mmcv-full after running the installation commands.

#### Using mmcv-full with Docker

Build with local repository

```bash
git clone https://github.com/open-mmlab/mmcv.git && cd mmcv
docker build -t mmcv -f docker/release/Dockerfile .
```

Or build with remote repository

```bash
docker build -t mmcv https://github.com/open-mmlab/mmcv.git#master:docker/release
```

The [Dockerfile](release/Dockerfile) installs latest released version of mmcv-full by default, but you can specify mmcv versions to install expected versions.

```bash
docker image build -t mmcv -f docker/release/Dockerfile --build-arg MMCV=1.5.0 .
```

If you also want to use other versions of PyTorch and CUDA, you can also pass them when building docker images.

An example to build an image with PyTorch 1.11 and CUDA 11.3.

```bash
docker build -t mmcv -f docker/release/Dockerfile \
    --build-arg PYTORCH=1.9.0 \
    --build-arg CUDA=11.1 \
    --build-arg CUDNN=8 \
    --build-arg MMCV=1.5.0 .
```

More available versions of PyTorch and CUDA can be found at [dockerhub/pytorch](https://hub.docker.com/r/pytorch/pytorch/tags).

### Install mmcv

If you need to use PyTorch-related modules, make sure PyTorch has been successfully installed in your environment by referring to the [PyTorch official installation guide](https://github.com/pytorch/pytorch#installation).

```python
pip install mmcv
```
