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Wrapper of OpenCV for .NET
Old versions of OpenCvSharp are stored in opencvsharp_2410.
| Package | Description | Link |
|---|---|---|
| OpenCvSharp4 | OpenCvSharp core libraries |  |
| OpenCvSharp4.WpfExtensions | WPF Extensions |  |
| OpenCvSharp4.Windows | All-in-one package for Windows (except UWP) |  |
| OpenCvSharp4.runtime.win | Native bindings for Windows x64/x86 (except UWP) |  |
| OpenCvSharp4.runtime.uwp | Native bindings for UWP (Universal Windows Platform) x64/x86/ARM |  |
| OpenCvSharp4.runtime.ubuntu.18.04-x64 | Native bindings for Ubuntu 18.04 x64 |  |
| OpenCvSharp4.runtime.osx.10.15-x64 | Native bindings for macOS 10.15 x64 |  |
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, UWP, Ubuntu 18.04 and macOS are released.
Packages named OpenCvSharp3-* and OpenCvSharp-* are deprecated.
OpenCvSharp3-AnyCPU / OpenCvSharp3-WithoutDll / OpenCvSharp-AnyCPU / OpenCvSharp-WithoutDll
https://hub.docker.com/u/shimat
Add OpenCvSharp4 and OpenCvSharp4.runtime.win NuGet packages to your project. You can use OpenCvSharp4.Windows instead.
Add OpenCvSharp4 and OpenCvSharp4.runtime.uwp NuGet packages to your project. Note that OpenCvSharp4.runtime.win and OpenCvSharp4.Windows don't work for UWP.
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
Some Docker images are provided to use OpenCvSharp with AppEngine Flexible. The native binding (libOpenCvSharpExtern) is already built in the docker image and you don't need to worry about it.
FROM shimat/appengine-aspnetcore3.1-opencv4.5.0:20201030
ADD ./ /app
ENV ASPNETCORE_URLS=http://*:${PORT}
WORKDIR /app
ENTRYPOINT [ "dotnet", "YourAspNetCoreProject.dll" ]
You can use the shimat/ubuntu18-dotnetcore3.1-opencv4.5.0 docker image.
This issue may be helpful: https://github.com/shimat/opencvsharp/issues/920
If you do not use NuGet, get DLL files from the release page.
PS1> Install-WindowsFeature Server-Media-Foundation
OpenCvSharp won't work on Unity and Xamarin platform. For Unity, please consider using OpenCV for Unity or some other solutions.
OpenCvSharp does not support CUDA. If you want to use the CUDA features, you need to customize the native bindings yourself.
For more details, see samples and Wiki pages.
Always remember to release Mat instances! The using syntax is useful.
// C# 8
// Edge detection by Canny algorithm
using OpenCvSharp;
class Program
{
static void Main()
{
using var src = new Mat("lenna.png", ImreadModes.Grayscale);
using var dst = new Mat();
Cv2.Canny(src, dst, 50, 200);
using (new Window("src image", src))
using (new Window("dst image", dst))
{
Cv2.WaitKey();
}
}
}
As mentioned above, objects of classes, such as Mat and MatExpr, have unmanaged resources and need to be manually released by calling the Dispose() method. Worst of all, the +, -, *, and other operators create new objects each time, and these objects need to be disposed, or there will be memory leaks. Despite having the using syntax, the code still looks very verbose.
Therefore, a ResourcesTracker class is provided. The ResourcesTracker implements the IDisposable interface, and when the Dispose() method is called, all resources tracked by the ResourcesTracker are disposed. The T() method of ResourcesTracker can trace an object or an array of objects, and the method NewMat() is like T(new Mat(...). All the objects that need to be released can be wrapped with T().For example: t.T(255 - t.T(picMat * 0.8)) . Example code is as following:
using (var t = new ResourcesTracker())
{
Mat mat1 = t.NewMat(new Size(100, 100), MatType.CV_8UC3, new Scalar(0));
Mat mat3 = t.T(255-t.T(mat1*0.8));
Mat[] mats1 = t.T(mat3.Split());
Mat mat4 = t.NewMat();
Cv2.Merge(new Mat[] { mats1[0], mats1[1], mats1[2] }, mat4);
}
using (var t = new ResourcesTracker())
{
var src = t.T(new Mat(@"lenna.png", ImreadModes.Grayscale));
var dst = t.NewMat();
Cv2.Canny(src, dst, 50, 200);
var blurredDst = t.T(dst.Blur(new Size(3, 3)));
t.T(new Window("src image", src));
t.T(new Window("dst image", blurredDst));
Cv2.WaitKey();
}
Mat into Bitmap(GDI+) or WriteableBitmap(WPF).https://github.com/shimat/opencvsharp_samples/
http://shimat.github.io/opencvsharp/api/OpenCvSharp.html
download_opencv_windows.ps1 to download OpenCV libs and headers from https://github.com/shimat/opencv_files. Those lib files are precompiled by the owner of OpenCvSharp using AppVeyor CI..\download_opencv_windows.ps1
OpenCvSharp.sln and buildIf you want to use some OpenCV features that are not provided by default in OpenCvSharp (e.g. GPU), you will have to build OpenCV yourself. The binary files of OpenCV for OpenCvSharp for Windows are created in the opencv_files repository. See the README.
git clone --recursive https://github.com/shimat/opencv_filesbuild_windows.ps1 or build_uwp.ps1 to customize the CMake parameters .git clone https://github.com/shimat/opencvsharp.git
cd opencvsharp
git fetch --all --tags --prune && git checkout ${OPENCVSHARP_VERSION}
OpenCvSharpExtern
cd opencvsharp/src
mkdir build
cd build
cmake -D CMAKE_INSTALL_PREFIX=${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"
OpenCvSharp4 NuGet package to your projectdotnet new console -n ConsoleApp01
cd ConsoleApp01
dotnet add package OpenCvSharp4
# -- edit Program.cs --- #
dotnet run
Refer to the Dockerfile and Wiki pages.
If you find the OpenCvSharp library useful and would like to show your gratitude by donating, here are some donation options. Thank you.
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