随机分配训练集，验证集

随机分配训练集，验证集

目录

coco json格式分配训练集，验证集

单个文件分配训练集，验证集

coco json格式分配训练集，验证集

import glob
import os.path
import random
import shutilif __name__ == '__main__':train_img=r'D:workimages'train_dir=r'D:worktrain'train_val=r'D:workval'os.makedirs(train_dir,exist_ok=True)os.makedirs(train_val,exist_ok=True)label_dir=r'D:workjsons'files = glob.glob(train_img + '/*.jpg')random.shuffle(files)data_len = len(files)train_len=int(data_len*0.7)for index, file in  enumerate(files):if index<train_py(file,train_py(os.path.join(label_dir,os.path.basename(file)[:-4]+".json"),train_dir)py(file, train_py(os.path.join(label_dir, os.path.basename(file)[:-4] + ".json"), train_val)

单个文件分配训练集，验证集

import random
import os
if __name__ == '__main__':file = r'E:/project/'with open(file, 'r',encoding="utf-8") as f:datas = f.readlines()random.shuffle(datas)file_train=r'E:/project/'file_val=r'E:/project/'data_len = len(datas)train_len=int(data_len*0.7)trains=[]vals=[]for index, file in enumerate(datas):if index<train_len:trains.append(file)else:vals.append(file)with open(file_train, 'w',encoding="utf-8") as f:f.writelines(trains)with open(file_val, 'w',encoding="utf-8") as f:f.writelines(vals)