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sample_classification.py
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33 lines (25 loc) · 1014 Bytes
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# -*- coding: utf-8 -*-
"""
Created on Sat May 5 09:49:54 2018
样本归类输出到对应文件夹
@author: KANG
"""
import numpy as np
import pandas as pd
import cv2 as cv
import os
def sample_classification():
filedir = './datasets/'
jpg_trainSet = pd.read_csv(filedir+'train.txt',header=None,delim_whitespace=True,encoding='gbk')
jpg_testSet = pd.read_csv(filedir+'test.txt',header=None,delim_whitespace=True,encoding='gbk')
jpg_trainName = jpg_trainSet.loc[:,0].tolist()
jpg_trainLabel = jpg_trainSet.loc[:,1].tolist()
for index,jpgname in enumerate(jpg_trainName):
img = cv.imread(filedir+'train/'+ jpgname)
path = filedir + 'train_new/'
if(not os.path.exists(path+str(jpg_trainLabel[index]))):
os.makedirs(path+str(jpg_trainLabel[index]))
cv.imwrite(path+str(jpg_trainLabel[index])+'/'+jpgname,img)
else:
cv.imwrite(path+str(jpg_trainLabel[index])+'/'+jpgname,img)
#sample_classification()