感知哈希算法 python 3.4

#!/usr/bin/python
# -*- coding: UTF-8 -*-
#Less than 10 add to list and sort
import glob
import os
import sys
from functools import reduce
from PIL import Image  

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

def avhash(im):
    if not isinstance(im, Image.Image):
        im = Image.open(im)
    if im.mode=='RGBA':
        im=ConvertRBGA(im)
    im = im.resize((8, 8), Image.ANTIALIAS).convert('L')
    avg = reduce(lambda x, y: x + y, im.getdata()) / 64.0
    return reduce(lambda x, y_z:  x | (y_z[1] << y_z[0]),  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 

def ConvertRBGA(img):
    x,y = img.size
    #   # (alpha band as paste mask).
    p = Image.new('RGBA', img.size, (255,255,255))
    p.paste(img, (0, 0, x, y),img)
    return p

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]
        im, wd = 'gs6.png', '.' 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:
            result=avhash(f)
            seq.append((f, hamming(result, 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))