A nice writeup of how to get a cross compiling enviroment for the Pi going on OSX with Eclipse: Raspberry PI – Cross Compiling unter Mac OS X mit Eclipse | Wel!s Blog (German).
AForge.NET Framework is a C# framework designed for developers and researchers in the fields of Computer Vision and Artificial Intelligence – image processing, neural networks, genetic algorithms, machine learning, robotics, etc.
The framework is comprised by the set of libraries and sample applications, which demonstrate their features:
- AForge.Imaging – library with image processing routines and filters;
- AForge.Vision – computer vision library;
- AForge.Neuro – neural networks computation library;
- AForge.Genetic – evolution programming library;
- AForge.Fuzzy – fuzzy computations library;
- AForge.MachineLearning – machine learning library;
- AForge.Robotics – library providing support of some robotics kits;
- AForge.Video – set of libraries for video processing
The work on the framework’s improvement is in constants progress, what means that new feature and namespaces are coming constantly. To get knowledge about its progress you may track source repository’s log or visit project discussion group to get the latest information about it.
The framework is provided not only with different libraries and their sources, but with many sample applications, which demonstrate the use of this framework, and with documentation help files, which are provided in HTML Help format. The documentation is also available on-line.
In the case you have found an issue in any component of the framework or you would like to request for a new feature, you may feel free to submit an issue/request in the issues tracking system.
In case you are interested in the project and would like to learn more about it or in case you would like to contribute it, you are more than welcome to participate in the project’s discussion group.
Xamarin the company behind Mono the .NET runtime for Linux, iOS, MacOS and Android has just announced that they got the Java part of Android ported to C# via machine translation. They claim some serious performance gains over Dalvik. For them, this is an experiment that they are not planning to focus on, but they will be using some of the technologies in Mono for Android. As Part of the project they improved the automated Java to C# translator “Sharpen”. Their version of Sharpen besides the code of the Android port itself is available on Github.