Python比较两个图片的相似度详解编程语言

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')