There are two versions of MMCV:
- mmcv-full: comprehensive, with full features and various CUDA ops out of box. It takes longer time to build.
- mmcv: lite, without CUDA ops but all other features, similar to mmcv<1.0.0. It is useful when you do not need those CUDA ops.
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`.
a. Install the full version.
Before installing mmcv-full, make sure that PyTorch has been successfully installed following the official guide.
We provide pre-built mmcv packages (recommended) with different PyTorch and CUDA versions to simplify the building for Linux and Windows systems. In addition, you can run check_installation.py to check the installation of mmcv-full after running the installation commands.
i. Install the latest version.
The rule for installing the latest mmcv-full is as follows:
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.htmlPlease replace {cu_version} and {torch_version} in the url to your desired one. For example,
to install the latest mmcv-full with CUDA 11.1 and PyTorch 1.9.0, use the following command:
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9.0/index.htmlFor more details, please refer the the following tables and delete =={mmcv_version}.
ii. Install a specified version.
The rule for installing a specified mmcv-full is as follows:
pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.htmlFirst of all, please refer to the Releases and replace {mmcv_version} a specified one. e.g. 1.3.9.
Then replace {cu_version} and {torch_version} in the url to your desired versions. For example,
to install mmcv-full==1.3.9 with CUDA 11.1 and PyTorch 1.9.0, use the following command:
pip install mmcv-full==1.3.9 -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9.0/index.htmlmmcv-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 and CUDA version is 11.1, you
can use the following command to install mmcv-full.
`pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.8.0/index.html`
For more details, please refer the the following tables.
| CUDA | torch 1.11 | torch 1.10 | torch 1.9 | torch 1.8 | torch 1.7 | torch 1.6 | torch 1.5 |
|---|---|---|---|---|---|---|---|
| 11.5 | install |
||||||
| 11.3 | install |
install |
|||||
| 11.1 | install |
install |
install |
||||
| 11.0 | install |
||||||
| 10.2 | install |
install |
install |
install |
install |
install |
install |
| 10.1 | install |
install |
install |
install |
|||
| 9.2 | install |
install |
install |
||||
| cpu | install |
install |
install |
install |
install |
install |
install |
The pre-built packages provided above do not include all versions of mmcv-full, you can click on the corresponding links to see the supported versions. For example, if you click [cu102-torch1.8.0](https://download.openmmlab.com/mmcv/dist/cu102/torch1.8.0/index.html), you can see that `cu102-torch1.8.0` only provides 1.3.0 and above versions of mmcv-full. In addition, We no longer provide `mmcv-full` pre-built packages compiled with `PyTorch 1.3 & 1.4` since v1.3.17. You can find previous versions that compiled with PyTorch 1.3 & 1.4 [here](./previous_versions.md). The compatibility is still ensured in our CI, but we will discard the support of PyTorch 1.3 & 1.4 next year.
mmcv-full does not provide pre-built packages for `cu102-torch1.11` and `cu92-torch*` on Windows.
Another way is to compile locally by running
pip install mmcv-fullNote that the local compiling may take up to 10 mins.
b. Install the lite version.
pip install mmcvc. Install full version with custom operators for onnxruntime
- Check here for detailed instruction.
If you would like to build MMCV from source, please refer to the guide.