python查找相似图片或重复图片

小灰灰 2022-11-25 04:16 177阅读 0赞

# 1.查找重复图片 #

利用文件的MD5值可查找完全一样的重复图片

import os,time,hashlib
    
    def getmd5(file):
        if not os.path.isfile(file):  
            return  
        fd = open(file,'rb')
        md5 = hashlib.md5()
        md5.update(fd.read())
        fd.close()
        return md5.hexdigest() 
    
    if __name__ == "__main__":
        allfile = []
        md5list = []
        list_delete = []
    
        start = time.time()
        path = 'D:\\_PLAY\\新建文件夹\\'
    
        for filepath,dir,filelist in os.walk(path):
            for filename in filelist:
                allfile.append(os.path.join(filepath,filename))
    
        #根据MD5值比较
        for photo in allfile:
            md5sum = getmd5(photo)
            if md5sum not in md5list:
                md5list.append(md5sum)
            else:
                list_delete.append(photo)
        print('重复的照片有:',list_delete)
        
        #删除图片
        for i in range(len(list_delete)):
            os.remove(list_delete[i])

# 二.查找相似图片 #

本文采用四种哈希值进行比较：  
1.感知哈希(perception hashing)  
2.平均散列(average hashing)  
3.梯度散列(difference hashing)  
4.离散小波变换(wavelet hashing)

import os,imagehash
    from PIL import Image
    
    def hash(path):
        highfreq_factor = 4 # resize的尺度
        hash_size = 32 # 最终返回hash数值长度
        image_scale = 64
        img_size = hash_size * highfreq_factor
        list_file = []
        list_phash = []
        list_ahash = []
        list_dhash = []
        list_whash = []
        for file in os.listdir(path):
            if os.path.splitext(file)[1] == '.jpg':  
                path_file = os.path.join(path, file)  # 拼路径
                list_file.append(file)
                phash = imagehash.phash(Image.open(path_file),hash_size=hash_size,highfreq_factor=highfreq_factor)#感知哈希(perception hashing)
                ahash = imagehash.average_hash(Image.open(path_file),hash_size=hash_size)#平均散列(average hashing)
                dhash = imagehash.dhash(Image.open(path_file),hash_size=hash_size)#梯度散列(difference hashing)
                whash = imagehash.whash(Image.open(path_file),image_scale=image_scale,hash_size=hash_size,mode = 'db4')#离散小波变换(wavelet hashing)
                list_phash.append(phash)
                list_ahash.append(ahash)
                list_dhash.append(dhash)
                list_whash.append(whash)
        #print(list_hash)
        for i in range(len(list_file)):
            for j in range(i+1,len(list_file)):
                phash_value = 1-(list_phash[i]-list_phash[j])/len(list_phash[i].hash)**2
                ahash_value = 1-(list_ahash[i]-list_ahash[j])/len(list_ahash[i].hash)**2
                dhash_value = 1-(list_dhash[i]-list_dhash[j])/len(list_dhash[i].hash)**2
                whash_value = 1-(list_whash[i]-list_whash[j])/len(list_whash[i].hash)**2
                value_hash = max(phash_value,ahash_value,dhash_value,whash_value)
                if(value_hash > 0.9):#阈值设为0.9
                    size_i = os.path.getsize(path + '\\' + list_file[i])
                    size_j = os.path.getsize(path + '\\' + list_file[j])
                    print(list_file[i],str(size_i/1024)+'KB')
                    print(list_file[j],str(size_j/1024)+'KB')
                    print(value_hash)
                    print('***********************')
    
    if __name__ == '__main__':
        path = r'D:\_PLAY\新建文件夹\Excel\ALL_Daily'
        hash(path)