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f43ff32752
* add c sharp api for fastdeploy * update accroding to c apis * add cmakelist for c sharp api * add cmakelists for c sharp * fix cmakelists * fix cmakelists * add c sharp api for fastdeploy * add ppyoloe demo * add ppyoloe demo * modify demo namespace code * add readme * fix format * format code * fix doc --------- Co-authored-by: heliqi <1101791222@qq.com>
98 lines
4.0 KiB
Markdown
98 lines
4.0 KiB
Markdown
English | [简体中文](README_CN.md)
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# PaddleDetection C# Deployment Example
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This directory provides examples that `infer_xxx.cs` to fastly finish the deployment of PaddleDetection models, including PPYOLOE on CPU/GPU.
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Before deployment, two steps require confirmation
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- 1. Software and hardware should meet the requirements. Please refer to [FastDeploy Environment Requirements](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md)
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- 2. Download the precompiled deployment library and samples code according to your development environment. Refer to [FastDeploy Precompiled Library](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md)
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Please follow below instructions to compile and test in Windows. FastDeploy version 1.0.4 or above (x.x.x>=1.0.4) is required to support this model.
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## 1. Download C# package management tool nuget client
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> https://dist.nuget.org/win-x86-commandline/v6.4.0/nuget.exe
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Add nuget program into system variable **PATH**
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## 2. Download model and image for test
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> https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz # (unzip it after download)
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> https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
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## 3. Compile example code
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Open `x64 Native Tools Command Prompt for VS 2019` command tool on Windows, cd to the demo path of ppyoloe and execute commands
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```shell
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cd D:\Download\fastdeploy-win-x64-gpu-x.x.x\examples\vision\detection\paddledetection\csharp
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mkdir build && cd build
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cmake .. -G "Visual Studio 16 2019" -A x64 -DFASTDEPLOY_INSTALL_DIR=D:\Download\fastdeploy-win-x64-gpu-x.x.x -DCUDA_DIRECTORY="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.2"
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nuget restore
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msbuild infer_demo.sln /m:4 /p:Configuration=Release /p:Platform=x64
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```
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For more information about how to use FastDeploy SDK to compile a project with Visual Studio 2019. Please refer to
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- [Using the FastDeploy C++ SDK on Windows Platform](../../../../../docs/en/faq/use_sdk_on_windows.md)
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## 4. Execute compiled program
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fastdeploy.dll and related dynamic libraries are required by the program. FastDeploy provide a script to copy all required dll to your program path.
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```shell
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cd D:\Download\fastdeploy-win-x64-gpu-x.x.x
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fastdeploy_init.bat install %cd% D:\Download\fastdeploy-win-x64-gpu-x.x.x\examples\vision\detection\paddledetection\csharp\build\Release
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```
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Then you can run your program and test the model with image
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```shell
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cd Release
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infer_ppyoloe_demo.exe ppyoloe_crn_l_300e_coco 000000014439.jpg 0 # CPU
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infer_ppyoloe_demo.exe ppyoloe_crn_l_300e_coco 000000014439.jpg 1 # GPU
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```
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## PaddleDetection C# Interface
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### Model Class
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```c#
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fastdeploy.vision.detection.PPYOLOE(
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string model_file,
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string params_file,
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string config_file
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fastdeploy.RuntimeOption runtime_option = null,
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fastdeploy.ModelFormat model_format = ModelFormat.PADDLE)
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```
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> PaddleDetection PPYOLOE initialization.
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> **Params**
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>> * **model_file**(str): Model file path
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>> * **params_file**(str): Parameter file path
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>> * **config_file**(str): Configuration file path, which is the deployment yaml file exported by PaddleDetection
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>> * **runtime_option**(RuntimeOption): Backend inference configuration. null by default, which is the default configuration
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>> * **model_format**(ModelFormat): Model format. Paddle format by default
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#### Predict Function
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```c#
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fastdeploy.DetectionResult Predict(OpenCvSharp.Mat im)
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```
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> Model prediction interface. Input images and output results directly.
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>
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> **Params**
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>
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>> * **im**(Mat): Input images in HWC or BGR format
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>
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> **Return**
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>
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>> * **result**(DetectionResult): Detection result, including detection box and confidence of each box. Refer to [Vision Model Prediction Result](../../../../../docs/api/vision_results/) for DetectionResult
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- [Model Description](../../)
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- [Python Deployment](../python)
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- [Vision Model prediction results](../../../../../docs/api/vision_results/)
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- [How to switch the model inference backend engine](../../../../../docs/en/faq/how_to_change_backend.md)
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