OpenCvSharp

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

Supported Platforms

Platform	Target Framework
.NET 8.0 or later	`net8.0`
.NET Standard 2.1	`netstandard2.1`
.NET Standard 2.0	`netstandard2.0`
.NET Framework 4.6.1+	via `netstandard2.0`
.NET Framework 4.8	direct target (WpfExtensions only)

Target OpenCV version: 4.13.0 (with opencv_contrib)

Quick Start

Windows

bash

dotnet add package OpenCvSharp4.Windows

Linux / Ubuntu

bash

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

For more installation options, see Installation on GitHub.

Requirements

Windows

Visual C++ 2022 Redistributable
(Windows Server only) Media Foundation:
powershell
```
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.

Slim Profile

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

	Modules
Enabled	`core`, `imgproc`, `imgcodecs`, `calib3d`, `features2d`, `flann`, `objdetect`, `photo`, `ml`, `video`, `stitching`, `barcode`
Disabled	`contrib`, `dnn`, `videoio`, `highgui`

Usage

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

csharp

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:

csharp

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.