import os
import random
# trainval_percent = 1 # trainval占總數的比例
# train_percent = 0.8 # train占trainval的比例
# xmlfilepath = r'E:\正課\大二上\計算機網絡\網絡編程\tensorflow-deeplab_v3_plus\data\Taidi\Annotations'
picturepath = r'E:\正課\大二上\計算機網絡\網絡編程\tensorflow-deeplab_v3_plus\picture'
txtsavepath = r'E:\正課\大二上\計算機網絡\網絡編程\tensorflow-deeplab_v3_plus\data'
# total_xml = os.listdir(xmlfilepath)
total_pic = os.listdir(picturepath)
# num = len(total_xml)
num = len(total_pic)
list = range(num)
# tv = int(num * trainval_percent)
# tr = int(tv * train_percent)
#
# trainval = random.sample(list, tv)
# train = random.sample(trainval, tr)
# ftrainval = open(txtsavepath + r'\trainval.txt', 'w')
ftest = open(txtsavepath + r'\test.txt', 'w') # w可以覆蓋
# ftrain = open(txtsavepath + r'\train.txt', 'w')
# fval = open(txtsavepath + r'\val.txt', 'w')
# for i in list:
# name = total_pic[i][:-4] + '\n'
# if i in trainval:
# ftrainval.write(name)
# if i in train:
# ftrain.write(name)
# else:
# fval.write(name)
for i in list:
name = total_pic[i][:-4] + '\n'
ftest.write(name)
# ftrainval.close()
# ftrain.close()
# fval.close()
ftest.close()