怎么在python中使用opencv对目录中的图片去重-创新互联
怎么在python中使用opencv对目录中的图片去重？针对这个问题，这篇文章详细介绍了相对应的分析和解答，希望可以帮助更多想解决这个问题的小伙伴找到更简单易行的方法。
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 + 1def 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关于怎么在python中使用opencv对目录中的图片去重问题的解答就分享到这里了，希望以上内容可以对大家有一定的帮助，如果你还有很多疑惑没有解开，可以关注创新互联成都网站设计公司行业资讯频道了解更多相关知识。
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