版本：
平台：ubuntu 14 / I5 / 4G内存
python版本：python2.7
opencv版本：2.13.4
依赖：
如果系统没有python，则需要进行安装
sudo apt-get install python
sudo apt-get install python-dev
sudo apt-get install python-pip
sudo pip install numpy mathplotlib
sudo apt-get install libcv-dev
sudo apt-get install python-opencv
原理：对每个文件进行遍历所有进行去重，因此图片越多速度越慢，但是可以节省手动操作
感知哈希原理：
1、需要比较的图片都缩放成8*8大小的灰度图
2、获得每个图片每个像素与平均值的比较，得到指纹
3、根据指纹计算汉明距离
5、如果得出的不同的元素小于5则为相同（相似？）的图片
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#!/usr/bin/python# -*- coding: UTF-8 -*- import cv2import numpy as npimport os,sys,types |
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def cmpandremove2(path): dirs = os.listdir(path) dirs.sort() if len(dirs) <= 0: return dict={} for i in dirs: prepath = path + "/" + i preimg = cv2.imread(prepath) if type(preimg) is types.NoneType: continue preresize = cv2.resize(preimg, (8,8)) pregray = cv2.cvtColor(preresize, cv2.COLOR_BGR2GRAY) premean = cv2.mean(pregray)[0] prearr = np.array(pregray.data) for j in range(0,len(prearr)): if prearr[j] >= premean: prearr[j] = 1 else: prearr[j] = 0 print "get", prepath dict[i] = prearr dictkeys = dict.keys() dictkeys.sort() index = 0 while True: if index >= len(dictkeys): break curkey = dictkeys[index] dellist=[] print curkey index2 = index while True: if index2 >= len(dictkeys): break j = dictkeys[index2] if curkey == j: index2 = index2 + 1 continue arr1 = dict[curkey] arr2 = dict[j] diff = 0 for k in range(0,len(arr2)): if arr1[k] != arr2[k]: diff = diff + 1 if diff <= 5: dellist.append(j) index2 = index2 + 1 if len(dellist) > 0: for j in dellist: file = path + "/" + j print "remove", file os.remove(file) dict.pop(j) dictkeys = dict.keys() dictkeys.sort() index = index + 1 |
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def cmpandremove(path): index = 0 flag = 0 dirs = os.listdir(path) dirs.sort() if len(dirs) <= 0: return 0 while True: if index >= len(dirs): break prepath = path + dirs[index] print prepath index2 = 0 preimg = cv2.imread(prepath) if type(preimg) is types.NoneType: index = index + 1 continue preresize = cv2.resize(preimg,(8,8)) pregray = cv2.cvtColor(preresize, cv2.COLOR_BGR2GRAY) premean = cv2.mean(pregray)[0] prearr = np.array(pregray.data) for i in range(0,len(prearr)): if prearr[i] >= premean: prearr[i] = 1 else: prearr[i] = 0 removepath = [] while True: if index2 >= len(dirs): break if index2 != index: curpath = path + dirs[index2] #print curpath curimg = cv2.imread(curpath) if type(curimg) is types.NoneType: index2 = index2 + 1 continue curresize = cv2.resize(curimg, (8,8)) curgray = cv2.cvtColor(curresize, cv2.COLOR_BGR2GRAY) curmean = cv2.mean(curgray)[0] curarr = np.array(curgray.data) for i in range(0,len(curarr)): if curarr[i] >= curmean: curarr[i] = 1 else: curarr[i] = 0 diff = 0 for i in range(0,len(curarr)): if curarr[i] != prearr[i] : diff = diff + 1 if diff <= 5: print 'the same' removepath.append(curpath) flag = 1 index2 = index2 + 1 index = index + 1 if len(removepath) > 0: for file in removepath: print "remove", file os.remove(file) dirs = os.listdir(path) dirs.sort() if len(dirs) <= 0: return 0 #index = 0 return flag def main(argv): if len(argv) <= 1: print "command error" return -1 if os.path.exists(argv[1]) is False: return -1 path = argv[1] ''' while True: if cmpandremove(path) == 0: break ''' cmpandremove(path) return 0 if __name__ == '__main__': main(sys.argv) |
为了节省操作，遍历所有目录，把想要去重的目录遍历一遍
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#!/bin/bashindir=$1addcount=0function intest(){ for file in $1/* do echo $file if test -d $file then ~/similar.py $file/ intest $file fi done}intest $indir |
以上这篇使用python opencv对目录下图片进行去重的方法就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持服务器之家。
原文链接：https://blog.csdn.net/shan_xg/article/details/79448314
