mosiac/mosiac.py

#! /usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Does mosiacs.
"""
import os
import time
import random

import numpy as np
from PIL import Image

class Mosiac():
	def __init__(self):
		self.images = []
		self.means = []
		self.imageBank = {}
		self.numClusters = 8
		self.clusters = []
		self.clusterMeans = []
		self.bigImageSize = None
		self.bigImage = None
		self.smallImage = None
		self.imageMatrix = []
		self.tileSize = None
		self.matrixSize = None


	def openBigImage(self, imagePath, mat=(40,20)):
		"""
		Opens and initializes the big image.
		"""
		self.matrixSize = mat
		self.bigImage = Image.open(imagePath).convert("RGB")
		self.tileSize = (self.bigImage.size[0] // mat[0],
			self.bigImage.size[1] // mat[1])
		self.smallImage = self.bigImage.resize(mat)
		self.bigImageSize = (self.tileSize[0]*mat[0], self.tileSize[1]*mat[1])


	def initImageBank(self, root, size=(200,200)):
		"""
		Calculates the average pixel value of all the images in the directory.
		"""
		then = time.time()
		for file in os.listdir(os.path.join(root, "images")):
			image = Image.open(os.path.join(root, "images", file))

			if image.mode == "P":
				image = image.convert(image.palette.mode)
			if image.mode == "RGBA":
				image = alpha_composite_with_color(image).convert("RGB")
			# image = image.convert("RGBA")

			image = image.resize(self.tileSize, Image.ANTIALIAS)
			mean = tuple(np.mean(image, axis=(0,1)))
			# img = Image.new("RGBA", image.size)
			# img.putdata(list(map(lambda pixel: (255,255,255,0) if pixel == (255,255,255,255) else pixel, image.getdata())))

			self.imageBank[mean] = image
		print(f"initImageBank took: {time.time()-then} seconds.")


	def debugImageBank(self):
		"""
		Create a bank of test images.
		"""
		then = time.time()
		self.images = []
		self.means = []
		for i in range(0, 257, 16):
			for j in range(0, 257, 16):
				for k in range(0, 257, 16):
					image = Image.new("RGB", self.tileSize, (i,j,k, 255))
					self.images.append(image)
					mean = tuple(np.mean(image, axis=(0,1)))
					self.means.append(mean)
		print(f"debugImageBank took: {time.time()-then} seconds.")


	def initClusters(self):
		"""
		Divides the images into clusters.
		"""
		then = time.time()
		sort = sorted(self.imageBank.keys(), key=lambda pixel: step(*pixel,8))
		num = len(sort) // self.numClusters

		for n in range(self.numClusters):
			cluster = dict(0: pixel for pixel in sort[n*num:n*num+num])
		cluster
		"""
		indexs = list(range(len(self.images)))
		step = len(self.images) // self.numClusters
		self.clusters = [indexs[i*step : (i+1)*step] for i in
			range(self.numClusters)]
		for cluster in self.clusters:
			means = [self.means[i] for i in cluster]
			mean = tuple(np.mean(means, axis=(0)))
			self.clusterMeans.append(mean)
		"""
		print(f"initClusters took: {time.time()-then} seconds.")


	def nearestImage(self, pixel):
		"""
		Finds the nearest image within the mosiac image bank to the provided
		pixel.
		"""
		dists = []
		for mean in self.clusterMeans:
			dist = np.linalg.norm(np.array(pixel)-np.array(mean))
			dists.append(dist)
		clusterMean = self.clusterMeans[dists.index(min(dists))]
		cluster = self.clusters[self.clusterMeans.index(clusterMean)]

		dists = []
		for n in cluster:
			dist = np.linalg.norm(np.array(pixel)-np.array(self.means[n]))
			dists.append(dist)
		choice = random.choice(sorted(dists)[:10])
		return self.images[cluster[dists.index(choice)]]


	def buildMatrix(self):
		"""
		Build the image matrix.
		"""
		then = time.time()
		# for row in range(self.smallImage.size[1]):
		# 	new_row = []
		# 	for col in range(self.smallImage.size[0]):
		# 		image = self.nearestImage(self.smallImage.getpixel((col, row)))
		# 		new_row.append(image)
		# 	self.imageMatrix.append(new_row)
		pixels = list(self.smallImage.getdata())
		for pixel in pixels:
			image = self.nearestImage(pixel)
			self.imageMatrix.append(image)
		print(f"buildMatrix took: {time.time()-then} seconds.")


	def buildMosiac(self, root):
		"""
		Builds the final mosiac image.
		"""
		then = time.time()
		image = Image.new("RGB", self.bigImageSize, (255,255,255))
		# self.bigImage = self.bigImage.crop((0,0,self.bigImageSize[0],self.bigImageSize[1]))
		n = 0
		for y in range(0, self.bigImageSize[1], self.tileSize[1]):
			for x in range(0, self.bigImageSize[0], self.tileSize[0]):
				image.paste(self.imageMatrix[n], box=(x,y))
				n += 1
		# self.bigImage.save(os.path.join(root, "mosiac.png"), "PNG")
		image.save(os.path.join(root, "mosiac.jpg"), "JPEG", optimize=True, quality=90)
		print(f"buildMosiac took: {time.time()-then} seconds.")


def step (r,g,b, repetitions=1):
	lum = math.sqrt( .241 * r + .691 * g + .068 * b )

	h, s, v = colorsys.rgb_to_hsv(r,g,b)

	h2 = int(h * repetitions)
	lum2 = int(lum * repetitions)
	v2 = int(v * repetitions)

	return (h2, lum, v2)


def alpha_composite(front, back):
	"""Alpha composite two RGBA images.

	Source: http://stackoverflow.com/a/9166671/284318

	Keyword Arguments:
	front -- PIL RGBA Image object
	back -- PIL RGBA Image object

	"""
	front = np.asarray(front)
	back = np.asarray(back)
	result = np.empty(front.shape, dtype='float')
	alpha = np.index_exp[:, :, 3:]
	rgb = np.index_exp[:, :, :3]
	falpha = front[alpha] / 255.0
	balpha = back[alpha] / 255.0
	result[alpha] = falpha + balpha * (1 - falpha)
	old_setting = np.seterr(invalid='ignore')
	result[rgb] = (front[rgb] * falpha + back[rgb] * balpha * (1 - falpha)) / result[alpha]
	np.seterr(**old_setting)
	result[alpha] *= 255
	np.clip(result, 0, 255)
	# astype('uint8') maps np.nan and np.inf to 0
	result = result.astype('uint8')
	result = Image.fromarray(result, 'RGBA')
	return result


def alpha_composite_with_color(image, color=(255, 255, 255)):
	"""Alpha composite an RGBA image with a single color image of the
	specified color and the same size as the original image.

	Keyword Arguments:
	image -- PIL RGBA Image object
	color -- Tuple r, g, b (default 255, 255, 255)

	"""
	back = Image.new('RGBA', size=image.size, color=color + (255,))
	return alpha_composite(image, back)


if __name__ == "__main__":
	import argparse

	parser = argparse.ArgumentParser(
		description="Generates a mosiac of images.")
	parser.add_argument(
		"root",
		help="Root directory to work in.")
	# parser.add_argument(
	# 	"-s",
	# 	"--size",
	# 	default=(200,200),
	# 	help="Size each image should be.")
	args = parser.parse_args()

	mosiac = Mosiac()
	mosiac.openBigImage(os.path.join(args.root, "big.jpg"))
	# mosiac.initImageBank(**vars(args))
	mosiac.debugImageBank()
	mosiac.initClusters()
	# mosiac.buildMatrix()
	# mosiac.buildMosiac(args.root)