mmdeploy/tools/package_tools
irexyc 3aaf592a7e rename mmdeploy_python -> mmdeploy_runtime 2023-03-23 17:59:11 +08:00
..
configs [Feature]: Add github prebuild workflow after new release. (#1852) 2023-03-23 17:00:19 +08:00
packaging rename mmdeploy_python -> mmdeploy_runtime 2023-03-23 17:59:11 +08:00
scripts [Feature]: Add github prebuild workflow after new release. (#1852) 2023-03-23 17:00:19 +08:00
test rename mmdeploy_python -> mmdeploy_runtime 2023-03-23 17:59:11 +08:00
README.md [Enhancement] build sdk python api in standard-alone manner (#810) 2022-08-02 10:23:48 +08:00
generate_build_config.py rename mmdeploy_python -> mmdeploy_runtime 2023-03-23 17:59:11 +08:00
mmdeploy_builder.py rename mmdeploy_python -> mmdeploy_runtime 2023-03-23 17:59:11 +08:00

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 and CUDA_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 and mmdeploy-{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 and mmdeploy-{version}-windows-amd64-onnxruntime1.8.1 precompiled packages in the current directory.