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create_better_mosaic.py

# Main function. Takes the original image and a list of
# profile pictures, and returns the finished, improved, mosaic
def create_better_mosaic(original_image, profile_pictures):
  # Calculate the width and height of the scaled image, where
  # each profile picture maps to a pixel in the original image
  width, height = image_ratio(original_image, len(profile_pictures))
  # Get the pixel values of the scaled image, "unfolded" in
  # one dimension
  pixels = get_pixels_one_dimensional(original_image, width, height)
  # Get a list of tuples with (image, color) for each profile picture
  tiles = profile_colors(profile_pictures)

  # Put the profile pictures in their places!
  tiles = iterate(tiles, pixels, 1e6)

  mosaic = Image.new("RGB", (width * TILE_SIZE, height * TILE_SIZE))

  # Paste the profile pictures one after the other 
  for i, tile in enumerate(tiles):
    x, y = divmod(i, width)
    mosaic.paste(tile[0].resize((TILE_SIZE, TILE_SIZE), Image.ANTIALIAS), (x * TILE_SIZE, y * TILE_SIZE)

  return mosaic

initial_solution.py

# Massage our pixel data so we get it in a
# one dimensional array
def get_pixels_one_dimensional(image, width, height):
  pixels = get_pixels(image, width, height)
  return [pixels[x, y] for x in range(width) for y in range(height)]

# Sum the distances between all tiles (i.e. profile pictures)
# and the pixels in the corresponding place
def initial_solution(tiles, pixels):
  return sum([distance(tiles[i][1], color) for i, color in enumerate(pixels)])

iterate.py

import random

# Swap random tiles (profile pictures) and calculate
# the difference for each solution. Keep good solutions.
# Iterate num_iterations times
def iterate(tiles, pixels, num_iterations):
  for i in range(num_iterations):
    i1 = random.randint(0, len(pixels) - 1)
    i2 = random.randint(0, len(pixels) - 1)

    current_solution = distance(tiles[i1][1], pixels[i1]) + distance(tiles[i2][1], pixels[i2])
    new_solution = distance(tiles[i2][1], pixels[i1]) + distance(tiles[i1][1], pixels[i2])

    if new_solution < current_solution:
      tiles[i2], tiles[i1] = tiles[i1], tiles[i2]

  return tiles