Prepare the Environment¶
Use conda and activate the environment:
conda create -n open-mmlab python=3.7 -y conda activate open-mmlab
MMEngine, please make sure that PyTorch has been successfully installed in the environment. You can refer to PyTorch official installation documentation. Verify the installation with the following command:
python -c 'import torch;print(torch.__version__)'
If you only want to use the fileio, registry, and config modules in MMEngine, you can install
mmengine-lite, which will only install the few third-party library dependencies that are necessary (e.g., it will not install opencv, matplotlib):
pip install mmengine-lite
Install with mim¶
mim is a package management tool for OpenMMLab projects, which can be used to install the OpenMMLab project easily.
pip install -U openmim mim install mmengine
Install with pip¶
pip install mmengine
Use docker images¶
Build the image
docker build -t mmengine https://github.com/open-mmlab/mmengine.git#main:docker/release
More information can be referred from mmengine/docker.
Run the image
docker run --gpus all --shm-size=8g -it mmengine
Build from source¶
# if cloning speed is too slow, you can switch the source to https://gitee.com/open-mmlab/mmengine.git git clone https://github.com/open-mmlab/mmengine.git cd mmengine pip install -e . -v
# if cloning speed is too slow, you can switch the source to https://gitee.com/open-mmlab/mmengine.git git clone https://github.com/open-mmlab/mmengine.git cd mmengine MMENGINE_LITE=1 pip install -e . -v
Verify the Installation¶
To verify if
MMEngine and the necessary environment are successfully installed, we can run this command:
python -c 'import mmengine;print(mmengine.__version__)'