python wrapper for a basic c implementation of the k-means algorithm.
pip install kmeans
import kmeans means = kmeans.kmeans(points, k)
points should be a list of tuples of the form (data, weight) where data is a list with length 3.
For example, finding four mean colors for a group of pixels:
pixels = [
[(15, 20, 25), 1], # [(r,g,b), count]
[(17, 31, 92), 5],
# ... Lots more ...
]
centers = kmeans.kmeans(pixels, 4)
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.
All values must be non-negative integers, with the following restrictions:
r, g, b [0, 255] (uint8_t) count [0, 4294967295] (uint32_t) maximum points 4294967296 (uint32_t) maximum means 256 (uint8_t) max iterations 65536 (uint16_t) max tolerance 65536 (uint16_t)
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.