mirror of
https://github.com/open-mmlab/mmdeploy.git
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48 lines
1.8 KiB
Markdown
48 lines
1.8 KiB
Markdown
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# Precompiled package
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This document is going to describe the way to build MMDeploy package.
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## Prerequisites
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- Download and install Miniconda from the [official website](https://docs.conda.io/en/latest/miniconda.html).
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- Create conda environments for python 3.6, 3.7, 3.8 and 3.9, respectively.
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```shell
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for PYTHON_VERSION in 3.6 3.7 3.8 3.9
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do
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conda create --name mmdeploy-$PYTHON_VERSION python=$PYTHON_VERSION -y
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done
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```
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- Prepare MMDeploy dependencies
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Please follow the [build-on-Linux guide](../../docs/en/01-how-to-build/linux-x86_64.md) or [build-on-Windows guide](../../docs/en/01-how-to-build/linux-x86_64.md) to install dependencies of MMDeploy,
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including PyTorch, MMCV, OpenCV, ppl.cv, ONNX Runtime and TensorRT.
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Make sure the environment variables `pplcv_DIR`, `ONNXRUNTIME_DIR`, `TENSORRT_DIR`, `CUDNN_DIR` and `CUDA_TOOLKIT_ROOT_DIR` are exported.
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## Run precompiled command
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- On Linux platform,
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```shell
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conda activate mmdeploy-3.6
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pip install pyyaml
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cd the/root/path/of/mmdeploy
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python tools/package_tools/mmdeploy_builder.py tools/package_tools/configs/linux_x64.yaml .
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```
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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.
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- On Windows platform, open `Anaconda Powershell Prompt` from the start menu and execute:
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```shell
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conda activate mmdeploy-3.6
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pip install pyyaml
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cd the/root/path/of/MMDeploy
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python tools/package_tools/mmdeploy_builder.py tools/package_tools/configs/windows_x64.yaml .
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```
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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.
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