这段代码实用pil模块比较两个图片的相似度，根据实际实用，代码虽短但效果不错，还是非常靠谱的，前提是图片要大一些，太小的图片不好比较。附件提供完整测试代码和对比用的图片。

#!/usr/bin/python  # Filename: histsimilar.py  # -*- coding: utf-8 -*-     import Image     def make_regalur_image(img, size = (256, 256)):      return img.resize(size).convert('RGB')     def split_image(img, part_size = (64, 64)):      w, h = img.size      pw, ph = part_size             assert w % pw == h % ph == 0             return [img.crop((i, j, i+pw, j+ph)).copy() \                  for i in xrange(0, w, pw) \                  for j in xrange(0, h, ph)]     def hist_similar(lh, rh):      assert len(lh) == len(rh)      return sum(1 - (0 if l == r else float(abs(l - r))/max(l, r)) for l, r in zip(lh, rh))/len(lh)     def calc_similar(li, ri):  #   return hist_similar(li.histogram(), ri.histogram())      return sum(hist_similar(l.histogram(), r.histogram()) for l, r in zip(split_image(li), split_image(ri))) / 16.0                    def calc_similar_by_path(lf, rf):      li, ri = make_regalur_image(Image.open(lf)), make_regalur_image(Image.open(rf))      return calc_similar(li, ri)     def make_doc_data(lf, rf):      li, ri = make_regalur_image(Image.open(lf)), make_regalur_image(Image.open(rf))      li.save(lf + '_regalur.png')      ri.save(rf + '_regalur.png')      fd = open('stat.csv', 'w')      fd.write('\n'.join(l + ',' + r for l, r in zip(map(str, li.histogram()), map(str, ri.histogram()))))  #   print >>fd, '\n'  #   fd.write(','.join(map(str, ri.histogram())))      fd.close()      import ImageDraw      li = li.convert('RGB')      draw = ImageDraw.Draw(li)      for i in xrange(0, 256, 64):          draw.line((0, i, 256, i), fill = '#ff0000')          draw.line((i, 0, i, 256), fill = '#ff0000')      li.save(lf + '_lines.png')            if __name__ == '__main__':      path = r'testpic/TEST%d/%d.JPG'      for i in xrange(1, 7):          print 'test_case_%d: %.3f%%'%(i, \              calc_similar_by_path('testpic/TEST%d/%d.JPG'%(i, 1), 'testpic/TEST%d/%d.JPG'%(i, 2))*100)         #   make_doc_data('test/TEST4/1.JPG', 'test/TEST4/2.JPG')