11 KiB
Installation
There are two versions of MMCV:
- mmcv: comprehensive, with full features and various CUDA ops out of box. It takes longer time to build.
- mmcv-lite: 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, 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 after running the installation commands.
i. Install the latest version.
The rule for installing the latest mmcv
is as follows:
pip install 'mmcv>=2.0.0rc1' -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
with CUDA 11.1
and PyTorch 1.9.0
, use the following command:
pip install 'mmcv>=2.0.0rc1' -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9.0/index.html
For more details, please refer the the following tables and delete =={mmcv_version}
.
ii. Install a specified version.
The rule for installing a specified mmcv
is as follows:
pip install mmcv=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html
First of all, please refer to the Releases and replace {mmcv_version}
a specified one. e.g. 2.0.0rc1
.
Then replace {cu_version}
and {torch_version}
in the url to your desired versions. For example,
to install mmcv==2.0.0rc1
with CUDA 11.1
and PyTorch 1.9.0
, use the following command:
pip install mmcv==2.0.0rc1 -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9.0/index.html
mmcv 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 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.
`pip install mmcv==2.0.0rc1 -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.8.0/index.html`
For more details, please refer the the following tables.
CUDA | torch 1.12 | torch 1.11 | torch 1.10 | torch 1.9 | torch 1.8 | torch 1.7 | torch 1.6 |
---|---|---|---|---|---|---|---|
11.6 | install |
||||||
11.5 | install |
||||||
11.3 | install |
install |
install |
||||
11.1 | install |
install |
install |
||||
11.0 | install |
||||||
10.2 | install |
install |
install |
install |
install |
install |
install |
10.1 | install |
install |
install |
||||
9.2 | install |
install |
|||||
cpu | install |
install |
install |
install |
install |
install |
install |
mmcv 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>=2.0.0rc1'
Note that the local compiling may take up to 10 mins.
b. Install the lite version.
pip install mmcv-lite
If you would like to build MMCV from source, please refer to the guide.