|
||
---|---|---|
.. | ||
configs | ||
packaging | ||
scripts | ||
test | ||
README.md | ||
generate_build_config.py | ||
mmdeploy_builder.py |
README.md
Precompiled package
This document is going to describe the way to build MMDeploy package.
Prerequisites
-
Download and install Miniconda from the official website.
-
Create conda environments for python 3.6, 3.7, 3.8 and 3.9, respectively.
for PYTHON_VERSION in 3.6 3.7 3.8 3.9 do conda create --name mmdeploy-$PYTHON_VERSION python=$PYTHON_VERSION -y done
-
Prepare MMDeploy dependencies
Please follow the build-on-Linux guide or build-on-Windows guide to install dependencies of MMDeploy, including PyTorch, MMCV, OpenCV, ppl.cv, ONNX Runtime and TensorRT.
Make sure the environment variables
pplcv_DIR
,ONNXRUNTIME_DIR
,TENSORRT_DIR
,CUDNN_DIR
andCUDA_TOOLKIT_ROOT_DIR
are exported.
Run precompiled command
-
On Linux platform,
conda activate mmdeploy-3.6 pip install pyyaml cd the/root/path/of/mmdeploy python tools/package_tools/mmdeploy_builder.py tools/package_tools/configs/linux_x64.yaml .
You will get the precompiled packages
mmdeploy-{version}-linux-x86_64-cuda11.1-tensorrt8.2.3.0
andmmdeploy-{version}-linux-x86_64-onnxruntime1.8.1
in the current directory if everything's going well. -
On Windows platform, open
Anaconda Powershell Prompt
from the start menu and execute:conda activate mmdeploy-3.6 pip install pyyaml cd the/root/path/of/MMDeploy python tools/package_tools/mmdeploy_builder.py tools/package_tools/configs/windows_x64.yaml .
When the build procedure finishes successfully, you will find
mmdeploy-{version}-windows-amd64-cuda11.1-tensorrt8.2.3.0
andmmdeploy-{version}-windows-amd64-onnxruntime1.8.1
precompiled packages in the current directory.