OpenCvSharp

Cross platform wrapper of OpenCV for .NET Framework.

Old versions of OpenCvSharp is maintained in opencvsharp_2410.

Installation

NuGet

Package	NuGet
OpenCvSharp core libraries
All-in-one package for Windows - same as OpenCvSharp3-AnyCPU
Native bindings for Windows x64/x86
Native bindings for Ubuntu 18.04 x64
Development Build Package	https://ci.appveyor.com/nuget/opencvsharp

Native binding (OpenCvSharpExtern.dll / libOpenCvSharpExtern.so) is required to work OpenCvSharp. To use OpenCvSharp, you should add both OpenCvSharp4 and OpenCvSharp4.runtime.* packages to your project. Currently, native bindings for Windows and Ubuntu 18.04 are released.

Windows

Add OpenCvSharp4 and OpenCvSharp4.runtime.win NuGet packages to your project. You can use OpenCvSharp4.Windows instead.

Ubuntu 18.04

Add OpenCvSharp4 and OpenCvSharp4.runtime.ubuntu.18.04.x64 NuGet packages to your project

dotnet new console -n ConsoleApp01
cd ConsoleApp01
dotnet add package OpenCvSharp4
dotnet add package OpenCvSharp4.runtime.ubuntu.18.04-x64
# -- edit Program.cs --- # 
dotnet run

Downloads

If you do not use NuGet, get DLL files from the release page.

Requirements

• OpenCV 4.0.0 with opencv_contrib
• (Windows)Visual C++ 2017 Redistributable Package
• .NET Framework 2.0 or later / .NET Core 2.0 / Mono

OpenCvSharp may not work on UWP and Unity platform. Please consider using OpenCV for Unity

Documents

https://shimat.github.io/opencvsharp_docs/index.html

Usage

For more details, see the Wiki page.

// Edge detection by Canny algorithm
using OpenCvSharp;

class Program 
{
    static void Main() 
    {
        Mat src = new Mat("lenna.png", ImreadModes.Grayscale);
        // Mat src = Cv2.ImRead("lenna.png", ImreadModes.Grayscale);
        Mat dst = new Mat();
        
        Cv2.Canny(src, dst, 50, 200);
        using (new Window("src image", src)) 
        using (new Window("dst image", dst)) 
        {
            Cv2.WaitKey();
        }
    }
}

Features

• OpenCvSharp is modeled on the native OpenCV C/C++ API style as much as possible.
• Many classes of OpenCvSharp implement IDisposable. There is no need to manage unsafe resources.
• OpenCvSharp does not force object-oriented programming style on you. You can also call native-style OpenCV functions.
• OpenCvSharp provides functions for converting from Mat/IplImage into Bitmap(GDI+) or WriteableBitmap(WPF).
• OpenCvSharp can work on Mono. It can run on any platform which Mono supports (e.g. Linux).

OpenCvSharp Build Instructions

Windows

• Install Visual Studio 2017 or later
  • VC++ features are required.
• Get all submodules

git submodule update --init --recursive

• Build tesseract and leptonica using vcpkg

.\vcpkg install tesseract:x64-windows-static
.\vcpkg install tesseract:x86-windows-static
.\vcpkg integrate install

• Build OpenCvSharp
  • Open OpenCvSharp.sln and build

Ubuntu 18.04

• Build OpenCV with opencv_contrib.
  • https://www.learnopencv.com/install-opencv-4-on-ubuntu-18-04/
• Install .NET Core SDK. https://dotnet.microsoft.com/download/linux-package-manager/ubuntu18-04/sdk-2.1.202
• Get OpenCvSharp source files

git clone https://github.com/shimat/opencvsharp.git
cd opencvsharp
git fetch --all --tags --prune && git checkout ${OPENCVSHARP_VERSION}

• Build native wrapper OpenCvSharpExtern

cd opencvsharp/src
mkdir build
cd build
cmake -D CMAKE_INSTALL_PREFIX=${YOUR_OPENCV_INSTALL_PATH} ..
make -j 
make install

You should add reference to opencvsharp/src/build/OpenCvSharpExtern/libOpenCvSharpExtern.so

export LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/home/shimat/opencvsharp/src/build/OpenCvSharpExtern"

• Add OpenCvSharp4 NuGet package to your project

dotnet new console -n ConsoleApp01
cd ConsoleApp01
dotnet add package OpenCvSharp4
# -- edit Program.cs --- # 
dotnet run

Older Ubuntu

Refer to the Dockerfile and Wiki pages.

License

Licensed under the BSD 3-Clause License.