宜配屋

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【听图阁-专注于Python设计】。