使用python opencv对目录下图片进行去重的方法
程序员文章站
2023-12-05 10:09:46
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,...
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
使用感知哈希算法进行图片去重
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
#!/usr/bin/python # -*- coding: utf-8 -*- import cv2 import numpy as np import os,sys,types
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
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
#!/bin/bash indir=$1 addcount=0 function 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。