| import random | |
| import os | |
| # 设定文件路径 | |
| train_file = 'train.txt' # 训练集输出文件 | |
| eval_file = 'eval.txt' # 验证集输出文件 | |
| test_file = 'test.txt' # 测试集输出文件 | |
| # 读取数据 | |
| data = sorted(os.listdir('/storage/chenqi/data/BraTS_2019_Data_Training/All')) | |
| # 随机打乱数据 | |
| random.shuffle(data) | |
| # 计算各个数据集的大小 | |
| train_size = 290 | |
| eval_size = 8 | |
| test_size = 37 | |
| # 划分数据集 | |
| train_data = data[:train_size] | |
| eval_data = data[train_size:train_size + eval_size] | |
| test_data = data[train_size + eval_size:] | |
| # 保存到txt文件 | |
| with open(train_file, 'w') as file: | |
| for i in train_data: | |
| file.write(i) | |
| file.write('\n') | |
| with open(eval_file, 'w') as file: | |
| for i in eval_data: | |
| file.write(i) | |
| file.write('\n') | |
| with open(test_file, 'w') as file: | |
| for i in test_data: | |
| file.write(i) | |
| file.write('\n') | |
| print(f"数据集已划分完成,并分别保存为: {train_file}, {eval_file}, {test_file}") | |