Monte Carlo noise effect

monte_carlo_filter.py

import Image
import random

target = Image.open('target.png').convert('RGB')

target_distance = 10

def make_image():
    return Image.new('RGB', target.size)

def random_pixel():
    return tuple(int(random.random() * 255) for i in xrange(3))

def distance(a, b):
    assert len(a) == len(b)
    accum = 0
    for i in xrange(len(a)):
        accum += b[i] - a[i]
    return accum / len(a)


i = 0
last_frame = make_image()
good_enough = set([])


def write_image(image):
    global i
    image.save('%d.bmp' % i)
    i += 1

for y in xrange(last_frame.size[1]):
    for x in xrange(last_frame.size[0]):
        last_frame.putpixel((x, y), random_pixel())

write_image(last_frame)

while 1:
    max_distance = 0
    next_frame = last_frame.copy()
    for y in xrange(last_frame.size[1]):
        for x in xrange(last_frame.size[0]):
            if (x, y) in good_enough:
                continue

            contender = random_pixel()
            target_pixel = target.getpixel((x, y))
            contender_distance = distance(contender, target_pixel)
            if contender_distance < distance(next_frame.getpixel((x, y)), target_pixel):
                next_frame.putpixel((x, y), contender)

                if contender_distance <= target_distance:
                    good_enough.add((x, y))

            current_distance = distance(next_frame.getpixel((x, y)), target_pixel)
            if current_distance > max_distance:
                max_distance = current_distance

    write_image(next_frame)
    last_frame = next_frame

    print max_distance

    if max_distance <= target_distance:
        break