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))