# AForgeNET

- **Website:** <https://aforgenet.com>
- **Primary alias:** `aforgenet.com`

## Description

AForgeNET is a C# framework specifically designed for developers and researchers in the fields of Computer Vision and Artificial Intelligence. It offers a wide range of functionalities such as image processing, neural networks, genetic algorithms, machine learning, and robotics. With the latest 2.2.5 version available, AForgeNET provides a powerful platform for working on computer vision and AI projects. In addition to the framework, AForgeNET offers several other software packages. The Computer Vision Sandbox is an open-source package that enables solving various computer vision tasks, including video surveillance, vision-based automation, and image/video processing. The GRATF (Glyph Recognition And Tracking Framework) library specializes in locating, recognizing, and estimating the pose of optical glyphs in still images and video streams and files. For those interested in image processing, the Image Processing Lab is an application written in C# that includes a range of image processing filters and tools available in the AForgeNET framework. The latest version, 2.8.0, is currently available. Stay up to date with the latest developments and articles on AForgeNET's dedicated forums and delve into the exciting world of computer vision and artificial intelligence.

## Industries

- 🖥 Computers Electronics and Technology
- 🖥 Artificial Intelligence and Machine Learning _(under Computers Electronics and Technology)_
- 🖥 Programming and Developer Software _(under Computers Electronics and Technology)_

## Logos & icons

- logo _(primary)_ — PNG — [download](https://cdn.brandfetch.io/id9zsoBdXm/w/1/h/1/theme/dark/logo.png?c=1bxid64Mup7aczewSAYMX&t=1764557361129)

## Colors

| Name | Hex | Theme |
| --- | --- | --- |
| Havelock Blue | #5080d0 | accent |
| Mine Shaft | #373737 | dark |
| White | #ffffff | light |

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_Source: <https://brandfetch.com/aforgenet.com>_
_See [/llms.txt](/llms.txt) for a full list of agent-readable pages, and [/auth.md](/auth.md) for how agents authenticate._