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= Sample project =
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= OpenCV 3.1 Haskell binding =
  
'''Contact''': The Lambda
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'''Homepage''': https://github.com/LumiGuide/haskell-opencv
  
'''Homepage''': http://haskell.org
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'''Contact''': Bas van Dijk
  
'''Required skills / skill level''': Suitable for beginners
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'''Required skill level''': Expert
  
This is an example project with its description.
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haskell-opencv is an in-development opensource Haskell binding to the popular OpenCV-3.1 C++ Computer Vision library. Note that other Haskell OpenCV bindings already exist but these target the older 2.4 version of OpenCV.
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The library comes with haddock documentation. Example programs are embedded in the documentation and are automatically build and run as part of the test-suite. They output images which are referenced from the documentation. Besides documentation the library also comes with a test-suite and the beginning of a benchmark suite. Finally, the library is already being used in production by LumiGuide for [https://bicycledutch.wordpress.com/2015/06/09/bicycle-parking-guidance-system-in-utrecht/ detecting available space to park your bicycle or car in big parking facilities].
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The library is not finished yet. A lot of functions still need to be bound. However, the basis is there to easily bind missing functionality. All the core pieces are in place: core datatypes like points, sizes,  polygons and most importantly matrices are there. It's also easy to bind missing datatypes. We use inline-c to inline C++ code in our Haskell code. We also have a way of dealing with exceptions originating from C++ code.
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The goal of this MuniHac project is simply to bind more functionality. Roel and Bas will be available as mentors and can help you get started quickly and provide advice on how to best represent OpenCV functions in Haskell.

Revision as of 18:21, 27 August 2016

OpenCV 3.1 Haskell binding

Homepage: https://github.com/LumiGuide/haskell-opencv

Contact: Bas van Dijk

Required skill level: Expert

haskell-opencv is an in-development opensource Haskell binding to the popular OpenCV-3.1 C++ Computer Vision library. Note that other Haskell OpenCV bindings already exist but these target the older 2.4 version of OpenCV.

The library comes with haddock documentation. Example programs are embedded in the documentation and are automatically build and run as part of the test-suite. They output images which are referenced from the documentation. Besides documentation the library also comes with a test-suite and the beginning of a benchmark suite. Finally, the library is already being used in production by LumiGuide for detecting available space to park your bicycle or car in big parking facilities.

The library is not finished yet. A lot of functions still need to be bound. However, the basis is there to easily bind missing functionality. All the core pieces are in place: core datatypes like points, sizes, polygons and most importantly matrices are there. It's also easy to bind missing datatypes. We use inline-c to inline C++ code in our Haskell code. We also have a way of dealing with exceptions originating from C++ code.

The goal of this MuniHac project is simply to bind more functionality. Roel and Bas will be available as mentors and can help you get started quickly and provide advice on how to best represent OpenCV functions in Haskell.