Metadata-Version: 1.1
Name: kmeans
Version: 0.2.0
Summary: python wrapper for basic c implementation of kmeans
Home-page: http://github.com/numberoverzero/kmeans/
Author: Joe Cross
Author-email: joe.mcross@gmail.com
License: MIT
Description: kmeans
        ===================
        .. image:: https://travis-ci.org/numberoverzero/kmeans.png?branch=master
           :target: https://travis-ci.org/numberoverzero/kmeans
        
        python wrapper for a basic c implementation of the k-means algorithm.
        
        Installation
        ===================
        ::
        
            pip install kmeans
        
        Documentation
        ===================
        `kmeans documentation <https://kmeans.readthedocs.org/en/latest/>`_
        
        
        Usage
        ===================
        ::
        
            import kmeans
            means = kmeans.kmeans(population, k)
        
        ``population`` should be a list of tuples of the form ``(data, weight)`` where ``data`` is a list.
        
        For example, finding two mean colors for a group of pixels::
        
            pixels = [
                [(15, 20, 25), 1],  # [(r,g,b), count]
                [(17, 31, 92), 5],
                # ... Lots more ...
            ]
        
            mean_pixels = kmeans.kmeans(pixels, 2)
        
        In this case, the weights passed in may be the frequency of the pixels occuring in an image, or some preference to pull the means towards a color.
        
        Inspiration
        ===================
        
        http://charlesleifer.com/blog/using-python-to-generate-awesome-linux-desktop-themes/
        
        I wanted to apply the implementation there to images much larger than 200x200.  Running a 4k x 3k image was approaching 60 seconds on a nice computer, so I decided to rewrite the kmeans implementation in c.
        
Platform: any
Classifier: Programming Language :: Python
Classifier: Development Status :: 3 - Alpha
Classifier: Natural Language :: English
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development :: Libraries :: Python Modules
