from PIL import Image
import os
#import hashlib 
 
def getGray(image_file):
 tmpls=[]
 for h in range(0, image_file.size[1]):#h
 for w in range(0, image_file.size[0]):#w
 tmpls.append( image_file.getpixel((w,h)) )
 
 return tmpls
 
def getAvg(ls):#獲取平均灰度值
 return sum(ls)/len(ls)
 
def getMH(a,b):#比較100個(gè)字符有幾個(gè)字符相同
 dist = 0;
 for i in range(0,len(a)):
 if a[i]==b[i]:
 dist=dist+1
 return dist
 
def getImgHash(fne):
 image_file = Image.open(fne) # 打開(kāi)
 image_file=image_file.resize((12, 12))#重置圖片大小我12px X 12px
 image_file=image_file.convert("L")#轉(zhuǎn)256灰度圖
 Grayls=getGray(image_file)#灰度集合
 avg=getAvg(Grayls)#灰度平均值
 bitls=''#接收獲取0或1
 #除去變寬1px遍歷像素
 for h in range(1, image_file.size[1]-1):#h
 for w in range(1, image_file.size[0]-1):#w
 if image_file.getpixel((w,h))>=avg:#像素的值比較平均值 大于記為1 小于記為0
 bitls=bitls+'1'
 else:
 bitls=bitls+'0'
 return bitls
''' 
 m2 = hashlib.md5() 
 m2.update(bitls)
 print m2.hexdigest(),bitls
 return m2.hexdigest()
'''
 
 
a=getImgHash("./Test/測(cè)試圖片.jpg")#圖片地址自行替換
files = os.listdir("./Test")#圖片文件夾地址自行替換
for file in files:
 b=getImgHash("./Test/"+str(file))
 compare=getMH(a,b)
 print file,u'相似度',str(compare)+'%'