Python PIL自动定位消消乐

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先看定位好的效果图：自动定位黄色的星星。

from PIL import Image, ImageDraw
import math
import operator
from functools import reduce

src_img = Image.open("xxl.png")
tpl_img = Image.open("xx.png")

# tpl_colours = tpl_img.getcolors()
hist_tpl = tpl_img.histogram()

src_width, src_height = src_img.size
tpl_width, tpl_height = tpl_img.size

blocks_x = int(src_width / tpl_width)
blocks_y = int(src_height / tpl_height)
draw = ImageDraw.Draw(src_img)

for y in range(blocks_y):
    for x in range(blocks_x):
        img = src_img.crop((x * tpl_width, y * tpl_height, (x+1) * tpl_width, (y+1) * tpl_height))
        hist_img = img.histogram()
        differ = math.sqrt(reduce(operator.add, list(map(lambda a, b: (a - b) ** 2, hist_img, hist_tpl))) / len(hist_tpl))
        if differ < 15:
            draw.rectangle((x * tpl_width, y * tpl_height, (x+1) * tpl_width, (y+1) * tpl_height), outline= (255,0,0))
            print("画矩形")
src_img.save("1.jpg")

素材图：

图片汉明距离

#!/usr/bin/python

import glob
import os
import sys

from PIL import Image

EXTS = 'jpg', 'jpeg', 'JPG', 'JPEG', 'gif', 'GIF', 'png', 'PNG'

def avhash(im):
    if not isinstance(im, Image.Image):
        im = Image.open(im)
    im = im.resize((8, 8), Image.ANTIALIAS).convert('L')
    avg = reduce(lambda x, y: x + y, im.getdata()) / 64.
    return reduce(lambda x, (y, z): x | (z << y),
                  enumerate(map(lambda i: 0 if i < avg else 1, im.getdata())),
                  0)

def hamming(h1, h2):
    h, d = 0, h1 ^ h2
    while d:
        h += 1
        d &= d - 1
    return h

if __name__ == '__main__':
    if len(sys.argv) <= 1 or len(sys.argv) > 3:
        print "Usage: %s image.jpg [dir]" % sys.argv[0]
    else:
        im, wd = sys.argv[1], '.' if len(sys.argv) < 3 else sys.argv[2]
        h = avhash(im)

        os.chdir(wd)
        images = []
        for ext in EXTS:
            images.extend(glob.glob('*.%s' % ext))

        seq = []
        prog = int(len(images) > 50 and sys.stdout.isatty())
        for f in images:
            seq.append((f, hamming(avhash(f), h)))
            if prog:
                perc = 100. * prog / len(images)
                x = int(2 * perc / 5)
                print '\rCalculating... [' + '#' * x + ' ' * (40 - x) + ']',
                print '%.2f%%' % perc, '(%d/%d)' % (prog, len(images)),
                sys.stdout.flush()
                prog += 1

        if prog: print
        for f, ham in sorted(seq, key=lambda i: i[1]):
            print "%d\t%s" % (ham, f)

参考：
https://www.jianshu.com/p/3d608bf33fe2
http://www.ruanyifeng.com/blog/2011/07/principle_of_similar_image_search.html