OpenCvSharp4.Windows 4.10.0.20241108 

dotnet add package OpenCvSharp4.Windows --version 4.10.0.20241108                

                    
                

            
NuGet\Install-Package OpenCvSharp4.Windows -Version 4.10.0.20241108
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="OpenCvSharp4.Windows" Version="4.10.0.20241108" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
paket add OpenCvSharp4.Windows --version 4.10.0.20241108                

                    
                

            
#r "nuget: OpenCvSharp4.Windows, 4.10.0.20241108"
#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 OpenCvSharp4.Windows as a Cake Addin
#addin nuget:?package=OpenCvSharp4.Windows&version=4.10.0.20241108

// Install OpenCvSharp4.Windows as a Cake Tool
#tool nuget:?package=OpenCvSharp4.Windows&version=4.10.0.20241108

OpenCV 4.x wrapper. All-in-one package for Windows users.

There are no supported framework assets in this package.

Learn more about Target Frameworks and .NET Standard.

NuGet packages (38)

Showing the top 5 NuGet packages that depend on OpenCvSharp4.Windows:

Package Downloads
our1314.work

Package Description
RatEye

Image processing library for Escape from Tarkov
UnionSoft.UiAuto.Automation

Library to use UnionSoft automaion project.
OpenVinoSharp.win

基于C#平台调用OpenVINO套件部署深度学习模型。 Based on the C # platform, call the OpenVINO suite to deploy a deep learning model.
MxNet.Sharp

C# Binding for the Apache MxNet library. NDArray, Symbolic and Gluon Supported MxNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines. MXNet is more than a deep learning project. It is a collection of blue prints and guidelines for building deep learning systems, and interesting insights of DL systems for hackers.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last updated
4.10.0.20241108 3,365 11/8/2024
4.10.0.20241107 486 11/7/2024
4.10.0.20240616 45,146 6/16/2024
4.10.0.20240615 396 6/15/2024
4.9.0.20240103 72,692 1/3/2024
4.8.0.20230708 97,833 7/10/2023
4.7.0.20230115 170,419 1/15/2023
4.6.0.20220608 155,149 6/8/2022
4.5.5.20211231 96,813 12/31/2021
4.5.3.20211228 26,832 12/28/2021
4.5.3.20211207 10,084 12/7/2021
4.5.3.20211204 804 12/5/2021
4.5.3.20210817 49,658 8/21/2021
4.5.3.20210725 11,007 7/25/2021
4.5.2.20210404 83,023 4/4/2021
4.5.1.20210210 19,851 2/10/2021
4.5.1.20210208 1,263 2/8/2021
4.5.1.20210206 643 2/6/2021
4.5.1.20210123 5,058 1/24/2021
4.5.1.20201229 38,782 12/29/2020
4.5.1.20201226 6,246 12/26/2020
4.5.0.20201013 28,526 10/13/2020
4.4.0.20200915 15,383 9/16/2020
4.4.0.20200725 14,603 7/25/2020
4.3.0.20200701 35,332 7/8/2020
4.3.0.20200524 23,734 5/27/2020
4.3.0.20200421 32,059 4/21/2020
4.3.0.20200405 11,697 4/5/2020
4.2.0.20200208 31,069 2/8/2020
4.2.0.20200108 16,042 1/8/2020
4.2.0.20191223 5,474 12/23/2019
4.1.1.20191216 6,416 12/17/2019
4.1.1.20191110 46,587 11/10/2019
4.1.1.20191026 5,683 10/27/2019
4.1.1.20191025 705 10/25/2019
4.1.1.20191021 817 10/23/2019
4.1.1.20191017 1,561 10/18/2019
4.1.0.20190416 106,895 4/16/2019
4.0.1.20190326 11,460 3/26/2019
4.0.0.20190108 5,463 1/8/2019
4.0.0.20181225 3,115 12/25/2018