I made a Photomosaic program with a book tutorial heres the code with proper credit<\/p>\n\n\n\n
“””<\/p>\n\n\n\n
photomosaic.py<\/p>\n\n\n\n
Creates a photomosaic given a target image and a folder of input images<\/p>\n\n\n\n
Author: Mahesh Venkitachalam<\/p>\n\n\n\n
“””<\/p>\n\n\n\n
import sys, os, random, argparse<\/p>\n\n\n\n
from PIL import Image<\/p>\n\n\n\n
import imghdr<\/p>\n\n\n\n
import numpy as np<\/p>\n\n\n\n
def<\/em> getAverageRGBOld(image<\/em>):<\/p>\n\n\n\n “””<\/p>\n\n\n\n Given PIL Image, return average value of color as (r, g, b)<\/p>\n\n\n\n “””<\/p>\n\n\n\n # no. of pixels in image<\/p>\n\n\n\n npixels = image<\/em>.size[0]*image<\/em>.size[1]<\/p>\n\n\n\n # get colors as [(cnt1, (r1, g1, b1)), …]<\/p>\n\n\n\n cols = image<\/em>.getcolors(npixels)<\/p>\n\n\n\n # get [(c1*r1, c1*g1, c1*g2),…]<\/p>\n\n\n\n sumRGB = [(x[0]*x[1][0], x[0]*x[1][1], x[0]*x[1][2]) for x in cols]<\/p>\n\n\n\n # calculate (sum(ci*ri)\/np, sum(ci*gi)\/np, sum(ci*bi)\/np)<\/p>\n\n\n\n # the zip gives us [(c1*r1, c2*r2, ..), (c1*g1, c1*g2,…)…]<\/p>\n\n\n\n avg = tuple([int(sum(x)\/npixels) for x in zip(*sumRGB)])<\/p>\n\n\n\n return avg<\/p>\n\n\n\n def<\/em> getAverageRGB(image<\/em>):<\/p>\n\n\n\n “””<\/p>\n\n\n\n Given PIL Image, return average value of color as (r, g, b)<\/p>\n\n\n\n “””<\/p>\n\n\n\n # get image as numpy array<\/p>\n\n\n\n im = np.array(image<\/em>)<\/p>\n\n\n\n # get shape<\/p>\n\n\n\n w,h,d = im.shape<\/p>\n\n\n\n # get average<\/p>\n\n\n\n return tuple(np.average(im.reshape(w*h, d), axis<\/em>=0))<\/p>\n\n\n\n def<\/em> splitImage(image<\/em>, size<\/em>):<\/p>\n\n\n\n “””<\/p>\n\n\n\n Given Image and dims (rows, cols) returns an m*n list of Images<\/p>\n\n\n\n “””<\/p>\n\n\n\n W, H = image<\/em>.size[0], image<\/em>.size[1]<\/p>\n\n\n\n m, n = size<\/em><\/p>\n\n\n\n w, h = int(W\/n), int(H\/m)<\/p>\n\n\n\n # image list<\/p>\n\n\n\n imgs = []<\/p>\n\n\n\n # generate list of dimensions<\/p>\n\n\n\n for j in range(m):<\/p>\n\n\n\n for i in range(n):<\/p>\n\n\n\n # append cropped image<\/p>\n\n\n\n imgs.append(image<\/em>.crop((i*w, j*h, (i+1)*w, (j+1)*h)))<\/p>\n\n\n\n return imgs<\/p>\n\n\n\n def<\/em> getImages(imageDir<\/em>):<\/p>\n\n\n\n “””<\/p>\n\n\n\n given a directory of images, return a list of Images<\/p>\n\n\n\n “””<\/p>\n\n\n\n files = os.listdir(imageDir<\/em>)<\/p>\n\n\n\n images = []<\/p>\n\n\n\n for file in files:<\/p>\n\n\n\n filePath = os.path.abspath(os.path.join(imageDir<\/em>, file))<\/p>\n\n\n\n try:<\/p>\n\n\n\n # explicit load so we don’t run into resource crunch<\/p>\n\n\n\n fp = open(filePath, “rb”)<\/p>\n\n\n\n im = Image.open(fp)<\/p>\n\n\n\n images.append(im)<\/p>\n\n\n\n # force loading image data from file<\/p>\n\n\n\n im.load()<\/p>\n\n\n\n # close the file<\/p>\n\n\n\n fp.close()<\/p>\n\n\n\n except:<\/p>\n\n\n\n # skip<\/p>\n\n\n\n print(“Invalid image: %s” % (filePath,))<\/p>\n\n\n\n return images<\/p>\n\n\n\n def<\/em> getImageFilenames(imageDir<\/em>):<\/p>\n\n\n\n “””<\/p>\n\n\n\n given a directory of images, return a list of Image file names<\/p>\n\n\n\n “””<\/p>\n\n\n\n files = os.listdir(imageDir<\/em>)<\/p>\n\n\n\n filenames = []<\/p>\n\n\n\n for file in files:<\/p>\n\n\n\n filePath = os.path.abspath(os.path.join(imageDir<\/em>, file))<\/p>\n\n\n\n try:<\/p>\n\n\n\n imgType = imghdr.what(filePath)<\/p>\n\n\n\n if imgType:<\/p>\n\n\n\n filenames.append(filePath)<\/p>\n\n\n\n except:<\/p>\n\n\n\n # skip<\/p>\n\n\n\n print(“Invalid image: %s” % (filePath,))<\/p>\n\n\n\n return filenames<\/p>\n\n\n\n def<\/em> getBestMatchIndex(input_avg<\/em>, avgs<\/em>):<\/p>\n\n\n\n “””<\/p>\n\n\n\n return index of best Image match based on RGB value distance<\/p>\n\n\n\n “””<\/p>\n\n\n\n # input image average<\/p>\n\n\n\n avg = input_avg<\/em><\/p>\n\n\n\n # get the closest RGB value to input, based on x\/y\/z distance<\/p>\n\n\n\n index = 0<\/p>\n\n\n\n min_index = 0<\/p>\n\n\n\n min_dist = float(“inf”)<\/p>\n\n\n\n for val in avgs<\/em>:<\/p>\n\n\n\n dist = ((val[0] – avg[0])*(val[0] – avg[0]) +<\/p>\n\n\n\n (val[1] – avg[1])*(val[1] – avg[1]) +<\/p>\n\n\n\n (val[2] – avg[2])*(val[2] – avg[2]))<\/p>\n\n\n\n if dist < min_dist:<\/p>\n\n\n\n min_dist = dist<\/p>\n\n\n\n min_index = index<\/p>\n\n\n\n index += 1<\/p>\n\n\n\n return min_index<\/p>\n\n\n\n def<\/em> createImageGrid(images<\/em>, dims<\/em>):<\/p>\n\n\n\n “””<\/p>\n\n\n\n Given a list of images and a grid size (m, n), create<\/p>\n\n\n\n a grid of images.<\/p>\n\n\n\n “””<\/p>\n\n\n\n m, n = dims<\/em><\/p>\n\n\n\n # sanity check<\/p>\n\n\n\n assert m*n == len(images<\/em>)<\/p>\n\n\n\n # get max height and width of images<\/p>\n\n\n\n # ie, not assuming they are all equal<\/p>\n\n\n\n width = max([img.size[0] for img in images<\/em>])<\/p>\n\n\n\n height = max([img.size[1] for img in images<\/em>])<\/p>\n\n\n\n # create output image<\/p>\n\n\n\n grid_img = Image.new(‘RGB’, (n*width, m*height))<\/p>\n\n\n\n # paste images<\/p>\n\n\n\n for index in range(len(images<\/em>)):<\/p>\n\n\n\n row = int(index\/n)<\/p>\n\n\n\n col = index – n*row<\/p>\n\n\n\n grid_img.paste(images<\/em>[index], (col*width, row*height))<\/p>\n\n\n\n return grid_img<\/p>\n\n\n\n def<\/em> createPhotomosaic(target_image<\/em>, input_images<\/em>, grid_size<\/em>,<\/p>\n\n\n\n reuse_images<\/em>=True):<\/p>\n\n\n\n “””<\/p>\n\n\n\n Creates photomosaic given target and input images.<\/p>\n\n\n\n “””<\/p>\n\n\n\n print(‘splitting input image…’)<\/p>\n\n\n\n # split target image<\/p>\n\n\n\n target_images = splitImage(target_image<\/em>, grid_size<\/em>)<\/p>\n\n\n\n print(‘finding image matches…’)<\/p>\n\n\n\n # for each target image, pick one from input<\/p>\n\n\n\n output_images = []<\/p>\n\n\n\n # for user feedback<\/p>\n\n\n\n count = 0<\/p>\n\n\n\n batch_size = int(len(target_images)\/10)<\/p>\n\n\n\n # calculate input image averages<\/p>\n\n\n\n avgs = []<\/p>\n\n\n\n for img in input_images<\/em>:<\/p>\n\n\n\n avgs.append(getAverageRGB(img))<\/p>\n\n\n\n for img in target_images:<\/p>\n\n\n\n # target sub-image average<\/p>\n\n\n\n avg = getAverageRGB(img)<\/p>\n\n\n\n # find match index<\/p>\n\n\n\n match_index = getBestMatchIndex(avg, avgs)<\/p>\n\n\n\n output_images.append(input_images<\/em>[match_index])<\/p>\n\n\n\n # user feedback<\/p>\n\n\n\n if count > 0 and batch_size > 10 and count % batch_size is 0:<\/p>\n\n\n\n print(‘processed %d of %d…’ %(count, len(target_images)))<\/p>\n\n\n\n count += 1<\/p>\n\n\n\n # remove selected image from input if flag set<\/p>\n\n\n\n if not reuse_images<\/em>:<\/p>\n\n\n\n input_images<\/em>.remove(match)<\/p>\n\n\n\n print(‘creating mosaic…’)<\/p>\n\n\n\n # draw mosaic to image<\/p>\n\n\n\n mosaic_image = createImageGrid(output_images, grid_size<\/em>)<\/p>\n\n\n\n # return mosaic<\/p>\n\n\n\n return mosaic_image<\/p>\n\n\n\n # Gather our code in a main() function<\/p>\n\n\n\n def<\/em> main():<\/p>\n\n\n\n # Command line args are in sys.argv[1], sys.argv[2] ..<\/p>\n\n\n\n # sys.argv[0] is the script name itself and can be ignored<\/p>\n\n\n\n # parse arguments<\/p>\n\n\n\n parser = argparse.ArgumentParser(description<\/em>=’Creates a photomosaic from input images’)<\/p>\n\n\n\n # add arguments<\/p>\n\n\n\n parser.add_argument(‘–target-image’, dest<\/em>=’target_image’, required<\/em>=True)<\/p>\n\n\n\n parser.add_argument(‘–input-folder’, dest<\/em>=’input_folder’, required<\/em>=True)<\/p>\n\n\n\n parser.add_argument(‘–grid-size’, nargs<\/em>=2, dest<\/em>=’grid_size’, required<\/em>=True)<\/p>\n\n\n\n parser.add_argument(‘–output-file’, dest<\/em>=’outfile’, required<\/em>=False)<\/p>\n\n\n\n args = parser.parse_args()<\/p>\n\n\n\n ###### INPUTS ######<\/p>\n\n\n\n # target image<\/p>\n\n\n\n target_image = Image.open(args.target_image)<\/p>\n\n\n\n # input images<\/p>\n\n\n\n print(‘reading input folder…’)<\/p>\n\n\n\n input_images = getImages(args.input_folder)<\/p>\n\n\n\n # check if any valid input images found <\/p>\n\n\n\n if input_images == []:<\/p>\n\n\n\n print(‘No input images found in %s. Exiting.’ % (args.input_folder, ))<\/p>\n\n\n\n exit()<\/p>\n\n\n\n # shuffle list – to get a more varied output?<\/p>\n\n\n\n random.shuffle(input_images)<\/p>\n\n\n\n # size of grid<\/p>\n\n\n\n grid_size = (int(args.grid_size[0]), int(args.grid_size[1]))<\/p>\n\n\n\n # output<\/p>\n\n\n\n output_filename = ‘mosaic.png’<\/p>\n\n\n\n if args.outfile:<\/p>\n\n\n\n output_filename = args.outfile<\/p>\n\n\n\n # re-use any image in input<\/p>\n\n\n\n reuse_images = True<\/p>\n\n\n\n # resize the input to fit original image size?<\/p>\n\n\n\n resize_input = True<\/p>\n\n\n\n ##### END INPUTS #####<\/p>\n\n\n\n print(‘starting photomosaic creation…’)<\/p>\n\n\n\n # if images can’t be reused, ensure m*n <= num_of_images<\/p>\n\n\n\n if not reuse_images:<\/p>\n\n\n\n if grid_size[0]*grid_size[1] > len(input_images):<\/p>\n\n\n\n print(‘grid size less than number of images’)<\/p>\n\n\n\n exit()<\/p>\n\n\n\n # resizing input<\/p>\n\n\n\n if resize_input:<\/p>\n\n\n\n print(‘resizing images…’)<\/p>\n\n\n\n # for given grid size, compute max dims w,h of tiles<\/p>\n\n\n\n dims = (int(target_image.size[0]\/grid_size[1]),<\/p>\n\n\n\n int(target_image.size[1]\/grid_size[0]))<\/p>\n\n\n\n print(“max tile dims: %s” % (dims,))<\/p>\n\n\n\n # resize<\/p>\n\n\n\n for img in input_images:<\/p>\n\n\n\n img.thumbnail(dims)<\/p>\n\n\n\n # create photomosaic<\/p>\n\n\n\n mosaic_image = createPhotomosaic(target_image, input_images, grid_size,<\/p>\n\n\n\n reuse_images)<\/p>\n\n\n\n # write out mosaic<\/p>\n\n\n\n mosaic_image.save(output_filename, ‘PNG’)<\/p>\n\n\n\n print(“saved output to %s” % (output_filename,))<\/p>\n\n\n\n print(‘done.’)<\/p>\n\n\n\n # Standard boilerplate to call the main() function to begin<\/p>\n\n\n\n # the program.<\/p>\n\n\n\n if __name__ == ‘__main__’:<\/p>\n\n\n\n main()<\/p>\n","protected":false},"excerpt":{"rendered":" I made a Photomosaic program with a book tutorial heres the code with proper credit “”” photomosaic.py Creates a photomosaic 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