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FastDeploy supports CPU inference with ONNX Runtime and GPU inference with Nvidia TensorRT/Paddle Inference on Nvidia Jetson platform
- If there's error occurs, shows
Could not find a package configuration file provided by "Python" with any of the following names: PythonConfig.cmake python-config.cmake
, please try to upgrade cmake to 3.25 or newer version to solve the problem.
Prerequisite for Compiling on NVIDIA Jetson:
- gcc/g++ >= 5.4 (8.2 is recommended)
- cmake >= 3.10.0
- jetpack >= 4.6.1
If you need to integrate Paddle Inference backend(Support CPU/GPU),please download and decompress the prebuilt library in Paddle Inference prebuild libraries according to your develop envriment.
git clone https://github.com/PaddlePaddle/FastDeploy.git
cd FastDeploy
mkdir build && cd build
cmake .. -DBUILD_ON_JETSON=ON \
-DENABLE_VISION=ON \
-DENABLE_PADDLE_BACKEND=ON \ # This is optional, can be OFF if you don't need
-DPADDLEINFERENCE_DIRECTORY=/Download/paddle_inference_jetson \
-DCMAKE_INSTALL_PREFIX=${PWD}/installed_fastdeploy
make -j8
make install
Once compiled, the C++ inference library is generated in the directory specified by CMAKE_INSTALL_PREFIX
Prerequisite for Compiling on NVIDIA Jetson:
- gcc/g++ >= 5.4 (8.2 is recommended)
- cmake >= 3.10.0
- jetpack >= 4.6.1
- python >= 3.6
Notice the wheel
is required if you need to pack a wheel, execute pip install wheel
first.
If you need to integrate Paddle Inference backend(Support CPU/GPU),please download and decompress the prebuilt library in Paddle Inference prebuild libraries according to your develop envriment.
All compilation options are imported via environment variables
git clone https://github.com/PaddlePaddle/FastDeploy.git
cd FastDeploy/python
export BUILD_ON_JETSON=ON
export ENABLE_VISION=ON
# ENABLE_PADDLE_BACKEND & PADDLEINFERENCE_DIRECTORY are optional
export ENABLE_PADDLE_BACKEND=ON
export PADDLEINFERENCE_DIRECTORY=/Download/paddle_inference_jetson
python setup.py build
python setup.py bdist_wheel
The compiled wheel
package will be generated in the FastDeploy/python/dist
directory once finished. Users can pip-install it directly.
During the compilation, if developers want to change the compilation parameters, it is advisable to delete the build
and .setuptools-cmake-build
subdirectories in the FastDeploy/python
to avoid the possible impact from cache, and then recompile.