python调用opencv做简单的dhash_python numpy dhash

原理很简单：
1 读取图像，变为灰度图，缩放到8*9
2 每行前8个像素，分别和后面一个像素比较，大于为1，否则为0，得到8*8的dhash
3 2个图片的dhash直接做汉明距比对，得到距离

# -*- coding: utf-8 -*- 

import os
import sys
import argparse

import numpy
from numpy import linalg as la  

import cv2

#差异hash
def dhashFeature(pic_name):
    print ("dhashFeature")
    image = cv2.imread(pic_name)
    res_image = cv2.resize(image,(9,8))
    gray = cv2.cvtColor(res_image,cv2.COLOR_RGB2GRAY)

    # 比较相邻像素
    difference = [0 for i in range(64)]
    for row in range(8):    
        for col in range(8): 
            if( gray[row][col] > gray[row][col+1] ):
                a = 1
            else:
                a = 0   
            difference[row*8+col] = a

    return (difference)

#汉明距离 按字符比较
def hammingSimilar(inA,inB):
    a = 0
    for i in range(len(inA)):
        if(inA[i] != inB[i]):
            a += 1
    return a    

#读取图片调用
feature1 = dhashFeature("image_0001.jpg")
#print(feature1)
feature2 = dhashFeature("image_0012.jpg")
#print(feature2)
diff = hammingSimilar(feature1,feature2)
print(diff)
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