The ID prefix of this package has been reserved for one of the owners of this package by Prefix Reserved
dotnet add package Sdcb.PaddleInference --version
NuGet\Install-Package Sdcb.PaddleInference -Version
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="Sdcb.PaddleInference" Version="" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Sdcb.PaddleInference --version
#r "nuget: Sdcb.PaddleInference,"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install Sdcb.PaddleInference as a Cake Addin
#addin nuget:?package=Sdcb.PaddleInference&version=

// Install Sdcb.PaddleInference as a Cake Tool
#tool nuget:?package=Sdcb.PaddleInference&version=

PaddleSharp 🌟 main QQ

💗 .NET Wrapper for PaddleInference C API, support Windows(x64) 💻, NVIDIA Cuda 10.2+ based GPU 🎮 and Linux(Ubuntu-22.04 x64) 🐧, currently contained following main components:

  • PaddleOCR 📖 support 14 OCR languages model download on-demand, allow rotated text angle detection, 180 degree text detection, also support table recognition 📊.
  • PaddleDetection 🎯 support PPYolo detection model and PicoDet model 🏹.
  • RotationDetection 🔄 use Baidu's official text_image_orientation_infer model to detect text picture's rotation angle(0, 90, 180, 270).
  • Paddle2Onnx 🔄 Allow user export ONNX model using C#.

NuGet Packages/Docker Images 📦

Release notes 📝

Please checkout this page 📄.

Infrastructure packages 🏗️

NuGet Package 💼 Version 📌 Description 📚
Sdcb.PaddleInference NuGet Paddle Inference C API .NET binding ⚙️

Native packages 🏗️

Package Source Version 📌 Description
Sdcb.PaddleInference.runtime.win64.mkl Baidu NuGet win64+mkldnn
Sdcb.PaddleInference.runtime.win64.openblas Sdcb NuGet win64+openblas
Sdcb.PaddleInference.runtime.win64.openblas-noavx Sdcb NuGet win64+openblas(no AVX, for old CPUs)
Sdcb.PaddleInference.runtime.win64.cuda102_cudnn76_tr72_sm61_75 Sdcb NuGet win64/CUDA 10.2/cuDNN 7.6/TensorRT 7.2/sm61+sm75
Sdcb.PaddleInference.runtime.win64.cuda118_cudnn86_tr85_sm86_89 Sdcb NuGet win64/CUDA 11.8/cuDNN 8.6/TensorRT 8.5/sm86+sm89
Sdcb.PaddleInference.runtime.win64.cuda117_cudnn84_tr84_sm86 Sdcb NuGet win64/CUDA 11.7/cuDNN 8.4/TensorRT 8.4/sm86
Sdcb.PaddleInference.runtime.win64.cuda102_cudnn76_sm61_75 Sdcb NuGet win64/CUDA 10.2/cuDNN 7.6/sm61+sm75
Sdcb.PaddleInference.runtime.win64.cuda116_cudnn84_sm86_onnx Sdcb NuGet win64/CUDA 11.6/cuDNN 8.4/sm86/onnx

Any other packages that starts with Sdcb.PaddleInference.runtime might deprecated.

Baidu packages were downloaded from here:

My Sdcb packages were self compiled.

Baidu official GPU packages are too large(>1.5GB) to publish to, there is a limitation of 250MB when upload to Github, there is some related issues to this:

But You're good to build your own GPU nuget package using 01-build-native.linq 🛠️.

Note: Linux does not need a native binding NuGet package like windows(Sdcb.PaddleInference.runtime.win64.mkl), instead, you can/should based from a Dockerfile🐳 to development:

Docker Images 🐳 Version 📌 Description 📚
sdflysha/dotnet6-paddle Docker PaddleInference 2.5.0, OpenCV 4.7.0, based on official Ubuntu 22.04 .NET 6 Runtime 🌐
sdflysha/dotnet6sdk-paddle Docker PaddleInference 2.5.0, OpenCV 4.7.0, based on official Ubuntu 22.04 .NET 6 SDK 🌐

Paddle Devices

  • Mkldnn - PaddleDevice.Mkldnn()

    Based on Mkldnn, generally fast

  • Openblas - PaddleDevice.Openblas()

    Based on openblas, slower, but dependencies file smaller and consume lesser memory

  • Onnx - PaddleDevice.Onnx()

    Based on onnxruntime, is also pretty fast and consume less memory

  • Gpu - PaddleDevice.Gpu()

    Much faster but relies on NVIDIA GPU and CUDA

    If you wants to use GPU, you should refer to FAQ How to enable GPU? section, CUDA/cuDNN/TensorRT need to be installed manually.

  • TensorRT - PaddleDevice.Gpu().And(PaddleDevice.TensorRt("shape-info.txt"))

    Even faster than raw Gpu but need install TensorRT environment.

    Please refer to tensorrt section for more details


Why my code runs good in my windows machine, but DllNotFoundException in other machine: 💻

  1. Please ensure the latest Visual C++ Redistributable was installed in Windows (typically it should automatically installed if you have Visual Studio installed) 🛠️ Otherwise, it will fail with the following error (Windows only):

    DllNotFoundException: Unable to load DLL 'paddle_inference_c' or one of its dependencies (0x8007007E)

    If it's Unable to load DLL OpenCvSharpExtern.dll or one of its dependencies, then most likely the Media Foundation is not installed in the Windows Server 2012 R2 machine: <img width="830" alt="image" src="">

  2. Many old CPUs do not support AVX instructions, please ensure your CPU supports AVX, or download the x64-noavx-openblas DLLs and disable Mkldnn: PaddleDevice.Openblas() 🚀

  3. If you're using Win7-x64, and your CPU does support AVX2, then you might also need to extract the following 3 DLLs into C:\Windows\System32 folder to make it run: 💾

    • api-ms-win-core-libraryloader-l1-2-0.dll
    • api-ms-win-core-processtopology-obsolete-l1-1-0.dll
    • API-MS-Win-Eventing-Provider-L1-1-0.dll

    You can download these 3 DLLs here: ⬇️

How to enable GPU? 🎮

Enable GPU support can significantly improve the throughput and lower the CPU usage. 🚀

Steps to use GPU in Windows:

  1. (for Windows) Install the package: Sdcb.PaddleInference.runtime.win64.cuda* instead of Sdcb.PaddleInference.runtime.win64.mkl, do not install both. 📦
  2. Install CUDA from NVIDIA, and configure environment variables to PATH or LD_LIBRARY_PATH (Linux) 🔧
  3. Install cuDNN from NVIDIA, and configure environment variables to PATH or LD_LIBRARY_PATH (Linux) 🛠️
  4. Install TensorRT from NVIDIA, and configure environment variables to PATH or LD_LIBRARY_PATH (Linux) ⚙️

You can refer to this blog page for GPU in Windows: 关于PaddleSharp GPU使用 常见问题记录 📝

If you're using Linux, you need to compile your own OpenCvSharp4 environment following the docker build scripts and the CUDA/cuDNN/TensorRT configuration tasks. 🐧

After these steps are completed, you can try specifying PaddleDevice.Gpu() in the paddle device configuration parameter, then enjoy the performance boost! 🎉

TensorRT 🚄

To use TensorRT, just specify PaddleDevice.Gpu().And(PaddleDevice.TensorRt("shape-info.txt")) instead of PaddleDevice.Gpu() to make it work. 💡

Please be aware, this shape info text file **.txt is bound to your model. Different models have different shape info, so if you're using a complex model like Sdcb.PaddleOCR, you should use different shapes for different models like this:

using PaddleOcrAll all = new(model,
   Enable180Classification = true,
   AllowRotateDetection = true,

In this case:

  • DetectionModel will use det.txt 🔍
  • 180DegreeClassificationModel will use cls.txt 🔃
  • RecognitionModel will use rec.txt 🔡


The first round of TensorRT running will generate a shape info **.txt file in this folder: %AppData%\Sdcb.PaddleInference\TensorRtCache. It will take around 100 seconds to finish TensorRT cache generation. After that, it should be faster than the general GPU. 🚀

In this case, if something strange happens (for example, you mistakenly create the same shape-info.txt file for different models), you can delete this folder to generate TensorRT cache again: %AppData%\Sdcb.PaddleInference\TensorRtCache. 🗑️

Thanks & Sponsors 🙏

  • 崔亮
  • 梁现伟
  • 深圳-钱文松
  • iNeuOS工业互联网操作系统:

Contact 📞

QQ group of C#/.NET computer vision technical communication (C#/.NET计算机视觉技术交流群): 579060605 alternate text is missing from this package README image

Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  net5.0-windows was computed.  net6.0 is compatible.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 was computed.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed. 
.NET Core netcoreapp2.0 was computed.  netcoreapp2.1 was computed.  netcoreapp2.2 was computed.  netcoreapp3.0 was computed.  netcoreapp3.1 was computed. 
.NET Standard netstandard2.0 is compatible.  netstandard2.1 was computed. 
.NET Framework net45 is compatible.  net451 was computed.  net452 was computed.  net46 was computed.  net461 was computed.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
MonoAndroid monoandroid was computed. 
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NuGet packages (7)

Showing the top 5 NuGet packages that depend on Sdcb.PaddleInference:

Package Downloads
Sdcb.PaddleOCR The ID prefix of this package has been reserved for one of the owners of this package by

Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition)


基于PaddleSharp.PaddleOCR设计的线程安全模板,示例: SafePaddleOCR safePaddleOCR = new SafePaddleOCR(); string imgPath = @"DimTechStudio-Logo.png"; var res = safePaddleOCR.Run(imgPath); Console.WriteLine($"res: {}");

Sdcb.PaddleDetection The ID prefix of this package has been reserved for one of the owners of this package by

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.


Library packed for OCR


Package Description

GitHub repositories (3)

Showing the top 3 popular GitHub repositories that depend on Sdcb.PaddleInference:

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🍨BetterGI · 更好的原神 - 自动拾取 | 自动剧情 | 全自动钓鱼(AI) | 全自动七圣召唤 | 自动伐木 | 快速传送 | 自动刷本 - UI Automation Testing Tools For Genshin Impact
The AI Agent Framework in .NET
.NET/C# binding for Baidu paddle inference library and PaddleOCR
Version Downloads Last updated 4,841 8/5/2023
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