import os
import random
import argparse

parser = argparse.ArgumentParser()
#xml文件的地址，根据自己的数据进行修改 xml一般存放在Annotations下
parser.add_argument('--xml_path', default='paper_data/Annotations', type=str, help='input xml label path')
#数据集的划分，地址选择自己数据下的ImageSets/Main
parser.add_argument('--txt_path', default='paper_data/ImageSets/Main', type=str, help='output txt label path')
opt = parser.parse_args()

trainval_percent = 1.0
train_percent = 0.8
xmlfilepath = opt.xml_path
txtsavepath = opt.txt_path
total_xml = os.listdir(xmlfilepath)
if not os.path.exists(txtsavepath):
    os.makedirs(txtsavepath)

num = len(total_xml)
list_index = range(num)
tv = int(num * trainval_percent)
tr = int(tv * train_percent)
trainval = random.sample(list_index, tv)
train = random.sample(trainval, tr)

file_trainval = open(txtsavepath + '/trainval.txt', 'w')
file_test = open(txtsavepath + '/test.txt', 'w')
file_train = open(txtsavepath + '/train.txt', 'w')
file_val = open(txtsavepath + '/val.txt', 'w')

addtrain_path = r"D:\PycharmProjects\Zhanting\yolov5_1\img_data\getimg_6.30"
for i in list_index:
    name = total_xml[i][:-4] + '\n'
    addimg_name = name.strip() + ".jpg"
    # print(addimg_name,type(addimg_name),len(addimg_name))
    if i in trainval:
        file_trainval.write(name)
        if i in train:
            file_train.write(name)
        else:
            if addimg_name in os.listdir(addtrain_path):#把某些数据加入训练集中
                print("addimg_name:",addimg_name)
                file_train.write(name)
            else:
                file_val.write(name)
            # file_val.write(name)
    else:
        file_test.write(name)

file_trainval.close()
file_train.close()
file_val.close()
file_test.close()