OpenCvSharp

A cross-platform .NET wrapper for OpenCV, providing image processing and computer vision functionality.

Supported Platforms

Target OpenCV version: 4.13.0 (with opencv_contrib)

Quick Start

Windows

dotnet add package OpenCvSharp4.Windows

Linux / Ubuntu

dotnet add package OpenCvSharp4
dotnet add package OpenCvSharp4.official.runtime.linux-x64

macOS

dotnet add package OpenCvSharp4
# Intel (x64):
dotnet add package OpenCvSharp4.runtime.osx.x64
# Apple Silicon (arm64):
dotnet add package OpenCvSharp4.runtime.osx.arm64

For more installation options, see Installation on GitHub.

Requirements

Windows

• (Windows Server only) Media Foundation:

  Install-WindowsFeature Server-Media-Foundation
  

Linux (Ubuntu and other distributions)

The official OpenCvSharp4.official.runtime.linux-x64 package is built on manylinux_2_28 (glibc 2.28) and works on Ubuntu 20.04+, Debian 10+, RHEL/AlmaLinux 8+, and other Linux distributions.

• Full package: uses GTK3 for highgui support (Cv2.ImShow, Cv2.WaitKey, etc.). GTK3 (libgtk-3.so.0) is pre-installed on standard Ubuntu/Debian/RHEL environments and typically requires no action. In minimal or container environments where GTK3 is absent, install it manually: Ubuntu/Debian: apt-get install libgtk-3-0; RHEL/AlmaLinux: dnf install gtk3. Alternatively, use the slim package which has no GUI dependencies.
• Slim package (OpenCvSharp4.official.runtime.linux-x64.slim): highgui is disabled; no GTK3 or other GUI dependencies. Suitable for headless and container environments.

macOS (Intel and Apple Silicon)

The OpenCvSharp4.runtime.osx.x64 and OpenCvSharp4.runtime.osx.arm64 packages provide native bindings for macOS. FFmpeg, Tesseract, Freetype, and all standard OpenCV modules are statically linked.

Slim Profile

The slim runtime packages (OpenCvSharp4.Windows.Slim, OpenCvSharp4.official.runtime.linux-x64.slim, etc.) bundle a smaller native library:

Usage

Always release Mat and other IDisposable resources using the using statement:

using OpenCvSharp;

// Edge detection using Canny algorithm
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();
}

For complex pipelines, use ResourcesTracker to manage multiple resources automatically:

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 blurred = t.T(dst.Blur(new Size(3, 3)));
t.T(new Window("src image", src));
t.T(new Window("dst image", blurred));
Cv2.WaitKey();

Note: OpenCvSharp does not support Unity, Xamarin, CUDA or UWP.

Resources

• GitHub Repository
• Code Samples
• API Documentation
• Issue Tracker