258 lines
6.8 KiB
Python
Executable File
258 lines
6.8 KiB
Python
Executable File
#! /usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Does mosiacs.
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"""
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import os
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import time
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import colorsys
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# import threading
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from multiprocessing import Pool
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from multiprocessing.dummy import Pool as ThreadPool
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import numpy as np
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from PIL import Image
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class Mosiac():
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def __init__(self):
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self.numClusters = 8
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self.tolerance = 0.1
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self.numThreads = 4
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self.imageBank = {}
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self.tilesDir = None
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self.clusters = []
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self.clusterMeans = []
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self.bigImageSize = None
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self.bigImage = None
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self.smallImage = None
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self.imageMatrix = []
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self.tileSize = None
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self.matrixSize = None
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def openBigImage(self, bigImagePath, mat=None):
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"""
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Opens and initializes the big image.
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"""
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self.bigImage = Image.open(bigImagePath).convert("RGB")
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# TODO: find a better way to do this
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if not mat:
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if self.bigImage.size[0] > self.bigImage.size[1]:
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mat = (40, 20)
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elif self.bigImage.size[0] < self.bigImage.size[1]:
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mat = (20, 40)
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else:
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mat = (20, 20)
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self.matrixSize = mat
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self.tileSize = (
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self.bigImage.size[0] // mat[0],
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self.bigImage.size[1] // mat[1])
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self.smallImage = self.bigImage.resize(mat)
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self.bigImageSize = (self.tileSize[0]*mat[0], self.tileSize[1]*mat[1])
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self.bigImage = self.bigImage.crop(
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(0, 0, self.bigImageSize[0], self.bigImageSize[1]))
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def initImageBank(self, tilesDir):
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"""
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Calculates the average pixel value of all the images in the directory.
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This is the thread controller.
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"""
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then = time.time()
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self.tilesDir = tilesDir
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files = os.listdir(self.tilesDir)
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pool = ThreadPool()
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pool.map(self.initImageBankWorker, files)
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pool.close()
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pool.join()
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print(f"initImageBank took: {time.time()-then} seconds.")
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def initImageBankWorker(self, file):
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"""
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Thread worker.
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"""
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image = Image.open(os.path.join(self.tilesDir, file))
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if image.mode == "P":
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image = image.convert(image.palette.mode)
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if image.mode == "RGBA":
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image = alpha_composite(image).convert("RGB")
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if image.mode == "L":
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image = image.convert("RGB")
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image = image.resize(self.tileSize, Image.ANTIALIAS)
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mean = tuple(np.mean(image, axis=(0,1)))
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self.imageBank[mean] = image
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def debugImageBank(self):
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"""
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Create a bank of test images.
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"""
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then = time.time()
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for i in range(0, 256, 15):
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for j in range(0, 256, 15):
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for k in range(0, 256, 15):
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image = Image.new("RGB", self.tileSize, (i,j,k, 255))
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mean = tuple(np.mean(image, axis=(0,1)))
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self.imageBank[mean] = image
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print(f"debugImageBank took: {time.time()-then} seconds.")
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def initClusters(self):
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"""
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Divides the images into clusters.
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"""
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then = time.time()
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sort = sorted(self.imageBank.keys(), key=lambda pixel: step(*pixel,8))
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num = len(sort) // self.numClusters
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for n in range(self.numClusters):
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cluster = {pixel: self.imageBank[pixel] for pixel in \
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sort[n*num:n*num+num]}
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self.clusters.append(cluster)
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# shove the left overs into the last cluster
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self.clusters[-1].update({pixel: self.imageBank[pixel] for pixel in \
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sort[-(len(sort) % num):]})
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for cluster in self.clusters:
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mean = tuple(np.mean(list(cluster.keys()), axis=(0)))
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self.clusterMeans.append(mean)
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print(f"initClusters took: {time.time()-then} seconds.")
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def nearestImage(self, pixel):
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"""
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Finds the nearest image within the mosiac image bank to the provided
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pixel.
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"""
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dists = []
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for mean in self.clusterMeans:
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dist = np.linalg.norm(np.array(pixel)-np.array(mean))
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dists.append(dist)
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clusterMean = self.clusterMeans[dists.index(min(dists))]
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cluster = self.clusters[self.clusterMeans.index(clusterMean)]
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nodes = np.array(list(cluster.keys()))
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dist = np.sum((nodes - np.array(pixel))**2, axis=1)
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tol = int(len(dist) * self.tolerance)
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tol += int(tol == 0)
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indexs = dist.argsort()[:tol]
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# choice = indexs.argmin() # closet value
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choice = np.random.choice(indexs)
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return cluster[tuple(nodes[choice])]
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def buildMatrix(self, tileAlpha):
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"""
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Build the image matrix.
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"""
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then = time.time()
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pixels = list(self.smallImage.getdata())
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for pixel in pixels:
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image = self.nearestImage(pixel)
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if tileAlpha:
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image = image.convert("RGBA")
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comp = Image.new("RGBA", image.size, pixel + (tileAlpha,))
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image = Image.alpha_composite(image, comp).convert("RGB")
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self.imageMatrix.append(image)
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print(f"buildMatrix took: {time.time()-then} seconds.")
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def buildMosiac(self, output, bigAlpha):
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"""
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Builds the final mosiac image.
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"""
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then = time.time()
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image = Image.new("RGB", self.bigImageSize, (255,255,255))
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n = 0
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for y in range(0, self.bigImageSize[1], self.tileSize[1]):
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for x in range(0, self.bigImageSize[0], self.tileSize[0]):
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image.paste(self.imageMatrix[n], box=(x,y))
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n += 1
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if bigAlpha:
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image = image.convert("RGBA")
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self.bigImage.putalpha(bigAlpha)
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image = Image.alpha_composite(image, self.bigImage).convert("RGB")
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# self.bigImage.save(output, "PNG")
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image.save(output, "JPEG", optimize=True, quality=90)
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print(f"buildMosiac took: {time.time()-then} seconds.")
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def step (r,g,b, repetitions=1):
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lum = ( .241 * r + .691 * g + .068 * b )**0.5
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h, s, v = colorsys.rgb_to_hsv(r,g,b)
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h2 = int(h * repetitions)
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lum2 = int(lum * repetitions)
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v2 = int(v * repetitions)
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return (h2, lum, v2)
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def alpha_composite(image, color=(255, 255, 255)):
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"""
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Alpha composite an RGBA Image with a specified color.
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Source: http://stackoverflow.com/a/9166671/284318
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"""
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image.load() # needed for split()
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background = Image.new('RGB', image.size, color)
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background.paste(image, mask=image.split()[3]) # 3 is the alpha channel
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return background
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if __name__ == "__main__":
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import argparse
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parser = argparse.ArgumentParser(
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description="Stiches together a series of smaller images in the \
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likeliness of a larger image. The 'big image' should be quite large.")
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parser.add_argument(
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"bigImagePath",
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help="The big image that will be used as the 'guide'.")
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parser.add_argument(
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"tilesDir",
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help="Directory full of images to be used as the tiles.")
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parser.add_argument(
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"output",
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help="File to be outputed.")
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parser.add_argument(
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"--matrix-size",
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dest="matrixSize",
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nargs=2,
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type=int,
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help="Size of the tile matrix. A 40x20 matrix would be '40 20'")
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parser.add_argument(
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"--tile-alpha",
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dest="tileAlpha",
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default=50,
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help="Alpha channel value of the color filter that is applied to each \
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tile. Range should be 0-255.")
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parser.add_argument(
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"--big-alpha",
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dest="bigAlpha",
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default=50,
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help="Alpha channel value of big image when it is transposed onto the \
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matrix. Range should be 0-255")
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args = parser.parse_args()
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if args.matrixSize:
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args.matrixSize = tuple(args.matrixSize)
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mosiac = Mosiac()
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mosiac.openBigImage(args.bigImagePath, args.matrixSize)
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mosiac.initImageBank(args.tilesDir)
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# mosiac.debugImageBank()
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mosiac.initClusters()
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mosiac.buildMatrix(args.tileAlpha)
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mosiac.buildMosiac(args.output, args.bigAlpha)
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