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ofxRapidLib

github.com/mzed/ofxRapidLib · @mzed
OF 0.11 Machine Learning

openFrameworks wrapper for the RapidLib machine learning library

30 4 Last commit 4y ago Created 9y ago

README

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GitHub license

ofxRapidLib

ofxRapidLib is an openFrameworks wrapper for the RapidLib library. RapidLib is a lightweight, interactive machine learning library intended to be used in interactive music and visual projects. It was directly inspired by Rebecca Fiebrink's Wekinator, and was written in collaboration with her at Goldsmiths, University of London, as part of the RAPID-MIX project.

RapidLib is an open source, cross-platform project and is avaiable under a BSD license.

The master branch of ofxRapidLib has been tested with:

Documentation

RapidLib DOxygen documentation



Interactive machine learning



The interactive machine learning API has the following classes: There are also two classes for holding the data that are used to train machine learning models:

Basic signal processing



In addition to machine learning, ofxRapidLib provides users with some basic signal processing algorithms for pre-processing incoming sensor data. This is centered around a buffer class, called rapidStream. It offers the following functions:

Examples

Description of examples

JavaScript

RapidLib has been ported to JavaScript. A node module is maintained here Add it to your node app with:
npm install rapidlib
The RapidLib JavaScript library also runs client side. It is extensively documented on CodeCircle. Search for the tag "#RapidLib"

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