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https://github.com/PaddlePaddle/FastDeploy.git
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[docs] update quick_start and README (#181)
* [docs] update quick_start and README * [docs] remove ENABLE_PADDLE_FRONTEND flags in win docs * [docs] update supported python version for win * [docs] update windows sdk example docs Co-authored-by: Jason <jiangjiajun@baidu.com>
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@@ -69,7 +69,10 @@
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```bash
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pip install numpy opencv-python fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
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```
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##### [Anaconda配置GPU环境(推荐)](docs/quick_start/Python_prebuilt_wheels.md)
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```bash
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conda config --add channels conda-forge && conda install cudatoolkit=11.2 cudnn=8.2
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```
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##### 安装CPU版本
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```bash
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@@ -17,7 +17,7 @@ git clone https://github.com/PaddlePaddle/FastDeploy.git
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cd FastDeploy && git checkout develop
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mkdir build && cd build
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cmake .. -G "Visual Studio 16 2019" -A x64 -DCMAKE_INSTALL_PREFIX=D:\Paddle\FastDeploy\build\fastdeploy-win-x64-0.2.0 -DENABLE_ORT_BACKEND=ON -DENABLE_VISION=ON -DENABLE_VISION_VISUALIZE=ON
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cmake .. -G "Visual Studio 16 2019" -A x64 -DCMAKE_INSTALL_PREFIX=D:\Paddle\FastDeploy\build\fastdeploy-win-x64-0.2.0 -DENABLE_ORT_BACKEND=ON -DENABLE_PADDLE_BACKEND=ON -DENABLE_VISION=ON -DENABLE_VISION_VISUALIZE=ON
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msbuild fastdeploy.sln /m /p:Configuration=Release /p:Platform=x64
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msbuild INSTALL.vcxproj /m /p:Configuration=Release /p:Platform=x64
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```
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@@ -32,7 +32,7 @@ git clone https://github.com/PaddlePaddle/FastDeploy.git
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cd FastDeploy && git checkout develop
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mkdir build && cd build
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cmake .. -G "Visual Studio 16 2019" -A x64 -DCMAKE_INSTALL_PREFIX=D:\Paddle\FastDeploy\build\fastdeploy-win-x64-gpu-0.2.0 -DWITH_GPU=ON -DENABLE_ORT_BACKEND=ON -DENABLE_VISION=ON -DENABLE_VISION_VISUALIZE=ON -DENABLE_PADDLE_FRONTEND=ON -DCUDA_DIRECTORY=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2
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cmake .. -G "Visual Studio 16 2019" -A x64 -DCMAKE_INSTALL_PREFIX=D:\Paddle\FastDeploy\build\fastdeploy-win-x64-gpu-0.2.0 -DWITH_GPU=ON -DENABLE_ORT_BACKEND=ON -DENABLE_PADDLE_BACKEND=ON -DENABLE_VISION=ON -DENABLE_VISION_VISUALIZE=ON -DCUDA_DIRECTORY="C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2"
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msbuild fastdeploy.sln /m /p:Configuration=Release /p:Platform=x64
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msbuild INSTALL.vcxproj /m /p:Configuration=Release /p:Platform=x64
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@@ -52,9 +52,11 @@ git clone https://github.com/PaddlePaddle/FastDeploy.git
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cd FastDeploy && git checkout develop
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set ENABLE_ORT_BACKEND=ON
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set ENABLE_PADDLE_BACKEND=ON
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set ENABLE_VISION=ON
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set ENABLE_VISION_VISUALIZE=ON
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% 这里指定用户自己的python解释器 以ptyhon3.8为例 %
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% 这里指定用户自己的python解释器 以python3.8为例 %
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C:\Python38\python.exe setup.py build
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C:\Python38\python.exe setup.py bdist_wheel
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```
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@@ -75,14 +77,13 @@ set ENABLE_ORT_BACKEND=ON
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% 说明:如果不编译TensorRT后端 此项为OFF %
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set ENABLE_TRT_BACKEND=ON
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set ENABLE_PADDLE_BACKEND=ON
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set ENABLE_PADDLE_FRONTEND=ON
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set ENABLE_VISION=ON
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set ENABLE_VISION_VISUALIZE=ON
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git clone https://github.com/PaddlePaddle/FastDeploy.git
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cd FastDeploy && git checkout develop
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% 说明:这里指定用户自己的python解释器 以ptyhon3.8为例 %
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% 说明:这里指定用户自己的python解释器 以python3.8为例 %
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C:\Python38\python.exe setup.py build
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C:\Python38\python.exe setup.py bdist_wheel
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```
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@@ -40,6 +40,8 @@ cmake .. -G "Visual Studio 16 2019" -A x64 -DFASTDEPLOY_INSTALL_DIR=%cd%\..\..\.
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```bat
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msbuild infer_demo.sln /m:4 /p:Configuration=Release /p:Platform=x64
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```
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## 配置依赖库路径
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#### 方式一:命令行设置环境变量
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编译好的exe保存在Release目录下,在运行demo前,需要将模型和测试图片拷贝至该目录。另外,需要在终端指定DLL的搜索路径。请在build目录下执行以下命令。
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```bat
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set FASTDEPLOY_PATH=%cd%\..\..\..\..\..\..\..\fastdeploy-win-x64-gpu-0.2.0
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@@ -49,11 +51,26 @@ set PATH=%FASTDEPLOY_PATH%\lib;%FASTDEPLOY_PATH%\third_libs\install\onnxruntime\
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```bat
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copy /Y %FASTDEPLOY_PATH%\third_libs\install\onnxruntime\lib\onnxruntime* Release\
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```
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由于较新的Windows在System32系统目录下自带了onnxruntime.dll,因此就算设置了PATH,系统依然会出现onnxruntime的加载冲突。因此需要先拷贝demo用到的onnxruntime.dll到exe所在的目录。
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由于较新的Windows在System32系统目录下自带了onnxruntime.dll,因此就算设置了PATH,系统依然会出现onnxruntime的加载冲突。因此需要先拷贝demo用到的onnxruntime.dll到exe所在的目录。如下
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```bat
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where onnxruntime.dll
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C:\Windows\System32\onnxruntime.dll # windows自带的onnxruntime.dll
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```
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#### 方式二:拷贝依赖库到exe的目录下
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手动拷贝,或者在build目录下执行以下命令:
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```bat
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set FASTDEPLOY_PATH=%cd%\..\..\..\..\..\..\..\fastdeploy-win-x64-gpu-0.2.0
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copy /Y %FASTDEPLOY_PATH%\lib\*.dll Release\
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copy /Y %FASTDEPLOY_PATH%\third_libs\install\onnxruntime\lib\*.dll Release\
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copy /Y %FASTDEPLOY_PATH%\third_libs\install\opencv-win-x64-3.4.16\build\x64\vc15\bin\*.dll Release\
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copy /Y %FASTDEPLOY_PATH%\third_libs\install\paddle_inference\paddle\lib\*.dll Release\
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copy /Y %FASTDEPLOY_PATH%\third_libs\install\paddle_inference\third_party\install\mkldnn\lib\*.dll Release\
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copy /Y %FASTDEPLOY_PATH%\third_libs\install\paddle_inference\third_party\install\mklml\lib\*.dll Release\
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copy /Y %FASTDEPLOY_PATH%\third_libs\install\paddle2onnx\lib\*.dll Release\
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copy /Y %FASTDEPLOY_PATH%\third_libs\install\tensorrt\lib\*.dll Release\
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copy /Y %FASTDEPLOY_PATH%\third_libs\install\yaml-cpp\lib\*.dll Release\
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```
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## 运行 demo
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```bat
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cd Release
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@@ -5,7 +5,7 @@ FastDeploy提供了在Windows/Linux/Mac上的预先编译Python Wheel包,开
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目前各平台支持情况如下
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- Linux 支持Python3.6~3.9
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- Windows 支持Python3.8~3.9
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- Windows 支持Python3.6~3.9
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- Mac 支持Python3.6~3.9
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## 安装 CPU Python 版本
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@@ -17,6 +17,30 @@ pip install fastdeploy-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.
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pip install fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
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```
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## Anaconda 快速配置 GPU 环境
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使用Anaconda的用户可在命令运行以下命令,快速配置GPU环境。如果是Windows用户,需要先打开`Anaconda Prompt (anaconda3)`命令行终端。
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- 增加 conda-forge 源
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```bash
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conda config --add channels conda-forge
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# 国内用户可以增加国内的源,如
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conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
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conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
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conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
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```
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- 新建 python 环境
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```bash
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conda create -n py38 python=3.8
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conda activate py38
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```
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- 安装 cudatoolkit 11.x 和 cudnn 8.x
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```bash
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conda install cudatoolkit=11.2 cudnn=8.2
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```
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- 安装 FastDeploy GPU 版本 Python 包
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```bash
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pip install fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
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```
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## 注意事项
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- 不要重复安装`fastdeploy-python`和`fastdeploy-gpu-python`
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- 如已安装CPU版本的`fastdeploy-python`后,在安装GPU版本的`fastdeploy-gpu-python`,请先执行`pip uninstall fastdeploy-python`卸载已有版本
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