图片相似度比较_python

ゝ一纸荒年。 2023-10-18 21:42 11阅读 0赞

# -*- coding : UTF-8 -*-
    
    import cv2 as cv
    from PIL import Image
    import os
    import numpy as np
    import copy
    import matplotlib.pyplot as plt
    
    def openImg_opencv(filename = 'new.jpg'):
        if os.path.exists(filename):
            image = cv.imread(filename) #opencv
            return image
        else:
            print("image not found")
    
    def openImg_PIL(filename = 'new.jpg'):
        if os.path.exists(filename):
            temp = Image.open(filename) #PIL
            image = np.array(temp)
            return image
        else:
            print("image not found")
    
    def averageGray(image):
        image = image.astype(int)
        for y in range(image.shape[1]): # y is width
            for x in range(image.shape[0]): # x is height
                gray = (image[x,y,0] + image[x,y,1] + image[x,y,2]) // 3
                image[x,y] = gray
        return image.astype(np.uint8)
    
    def averageGrayWithWeighted(image):
        image = image.astype(int)
        for y in range(image.shape[1]): # y is width
            for x in range(image.shape[0]): # x is height
                gray = image[x,y,0] * 0.3 + image[x,y,1] * 0.59 + image[x,y,2] * 0.11
                image[x,y] = int(gray)
        return image.astype(np.uint8)
    
    def maxGray(image):
        for y in range(image.shape[1]): # y is width
            for x in range(image.shape[0]):
                gray = max(image[x,y]) # x is height
                image[x,y] = gray
        return image
    
    def resize_opencv(image,weight = 8,height = 8):
        smallImage = cv.resize(image,(weight,height),interpolation=cv.INTER_LANCZOS4)
        return smallImage
    
    def calculateDifference(image,weight = 8,height = 8):
        differenceBuffer = []
        for x in range(weight):
            for y in range(height - 1):
                differenceBuffer.append(image[x,y,0] > image[x,y + 1,0])
        return differenceBuffer
    
    def makeHash(differ):
        hashOrdString = "0b"
        for value in differ:
            hashOrdString += str(int(value))
        hashString = hex(int(hashOrdString,2))
        return hashString
    
    def stringToHash(filename = 'new.jpg'):
        image1 = openImg_opencv(filename)
        grayImage1 = averageGrayWithWeighted(copy.deepcopy(image1))
        plt.imshow(grayImage1)
        plt.show()
        smallImage1 = resize_opencv(copy.deepcopy(grayImage1))
        plt.imshow(smallImage1)
        plt.show()
        differ = calculateDifference(copy.deepcopy(smallImage1))
        return makeHash(differ)
    
    def calculateHammingDistance(differ1,differ2):
        difference = (int(differ1, 16)) ^ (int(differ2, 16))
        return bin(difference).count("1")
    
    def main():
        pic1 = stringToHash('/Desktop/img/deng1.jpg')
        pic2 = stringToHash('/Desktop/img/deng2.jpg')
        print("this two picture is " + str((8 * 8 - calculateHammingDistance(pic1,pic2)) / (8 * 8) * 100) + "% similarity")
    if __name__ == "__main__":
        main()

提供俩张图片给大家使用

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQwMzc0NjA0_size_16_color_FFFFFF_t_70][]![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQwMzc0NjA0_size_16_color_FFFFFF_t_70 1][]

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQwMzc0NjA0_size_16_color_FFFFFF_t_70]: https://img-blog.csdnimg.cn/20190715170127811.jpg?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQwMzc0NjA0,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQwMzc0NjA0_size_16_color_FFFFFF_t_70 1]: https://img-blog.csdnimg.cn/20190715170131923.jpg?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQwMzc0NjA0,size_16,color_FFFFFF,t_70