Python比较两个图片相似度的方法

#!/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,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,i),fill = '#ff0000')
        draw.line((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')