计算图像相似度——《Python也可以》之一

#!/usr/bin/env python
# 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 = make_regalur_image(Image.open(lf))
    ri = 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()))))
    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 =‘#F00‘)
        draw.line((i,0,i,256),fill=‘#F00‘)
    li.save(lf+‘_lines.png‘)

if __name__==‘__main__‘:
    path = r‘test/TEST%d/%d.JPG‘
    for i in xrange(1,7):
        print ‘test_case_%d: %.3f%%‘%(i,calc_similar_by_path(‘test/TEST%d/%d.JPG‘%(i,1),‘test/TEST%d/%d.JPG‘%(i,2))*100)

    make_doc_data(‘test/TEST4/1.JPG‘,‘test/TEST4/2.JPG‘)