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## Installation
There are two versions of MMCV:
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- **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.
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```{warning}
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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` .
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```
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### Install mmcv-full
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```{note}
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- 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 )
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```
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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
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```bash
python -c 'import torch;print(torch.__version__)'
```
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If version information is output, then PyTorch is installed.
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#### Install with mim (recommended)
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[mim ](https://github.com/open-mmlab/mim ) is the package management tool for the OpenMMLab projects, which makes it easy to install mmcv-full
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```bash
pip install -U openmim
mim install mmcv-full
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```
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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 >
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< / details >
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To install a specific version of mmcv-full, for example, mmcv-full version 1.6.0, you can use the following command
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```bash
mim install mmcv-full==1.6.0
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```
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:::{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` .
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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
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```
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:::
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 => {
select.size = 1;
});
}
function handleSelectBlur(id) {
const dom = document.getElementById(id);
if (!dom) {
// 如果没有指定特定的id，
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${torchVal.substring(0, torchVal.length - 2)}` ;
cmdString = cmdString.replace("{cu_version}", cudaVersion).replace("{mmcv_version}", mmcvVal).replace("{torch_version}", torchVersion);
cmd.textContent = cmdString;
}
// string数组去重
function unique(arr) {
if (!arr || !Array.isArray(arr)) return [];
return [...new Set(arr)];
}
// 根据string数组生成option的DocumentFragment
function genOptionFragment(data, id) {
const name = id.includes("-")? id.split("-")[1] : id;
const fragment = new DocumentFragment();
data.forEach(option => {
const ele = document.createElement("option");
let text = `${name} ${option}` ;
if (name === "os" || option.toUpperCase() === "CPU") {
text = `${option}` ;
}
ele.textContent = text;
// 添加value属性，
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（ ） ，
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) {
const order = ["select-mmcv", "select-torch", "select-cuda", "select-os"];
const idx = order.indexOf(id);
if (idx === -1) return;
const versionDetail = version[osVal];
if (idx >= 3) {
// 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");
}
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];
findAndAppend(mmcv, "select-mmcv");
}
changeCmd();
}
// 初始化， ，
function init() {
// 增加一个全局的click事件监听，
document.addEventListener("click", handleSelectBlur);
const version = window.version;
// OS
const os = Object.keys(version);
osVal = os[0];
findAndAppend(os, "select-os");
change("select-os");
changeCmd();
}
// 利用xhr获取本地version数据， ，
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，
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}
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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.
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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` .
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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
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```
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:::
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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 .
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```
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Or build with remote repository
```bash
docker build -t mmcv https://github.com/open-mmlab/mmcv.git#master:docker/release
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```
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The [Dockerfile ](release/Dockerfile ) installs latest released version of mmcv-full by default, but you can specify mmcv versions to install expected versions.
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```bash
docker image build -t mmcv -f docker/release/Dockerfile --build-arg MMCV=1.5.0 .
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```
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If you also want to use other versions of PyTorch and CUDA, you can also pass them when building docker images.
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An example to build an image with PyTorch 1.11 and CUDA 11.3.
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```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 .
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```
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More available versions of PyTorch and CUDA can be found at [dockerhub/pytorch ](https://hub.docker.com/r/pytorch/pytorch/tags ).
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### Install mmcv
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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
```
