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。