It probably makes art.
imcmc (im-sea-em-sea) is a small library for turning 2d images into probability distributions
and then sampling from them to create images and gifs. Right now it is best at logos and shape based images.
This is actually pip installable from git!
pip install git+https://github.com/ColCarroll/imcmcSee imcmc.ipynb for a few working examples as well.
import imcmc
image = imcmc.load_image('python.png', 'L')
# This call is random -- rerun adjusting parameters until the image looks good
trace = imcmc.sample_grayscale(image, samples=1000, tune=500, nchains=6)
# Lots of plotting options!
imcmc.plot_multitrace(trace, image, marker='o', markersize=10,
colors=['#0000FF', '#FFFF00'], alpha=0.9);
# Save as a gif, with the same arguments as above, plus some more
imcmc.make_gif(trace, image, dpi=40, marker='o', markersize=10,
colors=['#0000FF', '#FFFF00'], alpha=0.9,
filename='example.gif')See crosshatch.ipynb for a few working examples as well.
import matplotlib.pyplot as plt
from imcmc.color import (
ImageLines,
IntensityMCMCStrategy,
UniformLinesStrategy,
GibbsIntensityStrategy
)
pete = plt.imread('color/pete2.jpg')
ImageLines(pete, UniformStrategy()).plot()munchen = plt.imread('color/munchen.jpg')
ImageLines(munchen, IntensityMCMCStrategy(step_size=500)).plot(10_000)beach = plt.imread('color/beach.jpg')
ImageLines(beach, UniformLinesStrategy()).plot(1500, linewidth=1)karwendel = plt.imread('color/karwendel.jpg')
ImageLines(karwendel, GibbsIntensityStrategy()).plot(1_000)Pillow does not have a logo, but the other tools do!
I get to do lots of open source work for The Center for Civic Media at MIT. Even better, they have a super multi-modal logo that I needed to use 98 chains to sample from!