Datasets:
Formats:
webdataset
Size:
1M - 10M
Tags:
sgt
semantic-generative-tuning
unified-multimodal
image-segmentation
visual-understanding
visual-generation
License:
| import os | |
| os.chdir('/workspace/public_datasets/sam_selection/') | |
| import tarfile | |
| from tqdm import tqdm | |
| def extract_tar_files(tar_file_list, output_directory): | |
| # 读取 tar_file.txt 文件,获取所有 .tar 文件名 | |
| with open(tar_file_list, 'r') as f: | |
| tar_files = f.read().splitlines() | |
| # 确保输出目录存在 | |
| if not os.path.exists(output_directory): | |
| os.makedirs(output_directory) | |
| # 遍历每个 .tar 文件并解压 | |
| for tar_file in tqdm(tar_files, desc="Extracting files", unit="file"): | |
| tar_path = os.path.join(os.path.dirname(tar_file_list), tar_file) | |
| if os.path.exists(tar_path): | |
| with tarfile.open(tar_path, 'r') as tar: | |
| members = tar.getmembers() | |
| for member in tqdm(members, desc=f"Extracting {tar_file}", unit="file", leave=False): | |
| tar.extract(member, path=output_directory) | |
| else: | |
| print(f"Warning: File {tar_file} does not exist.") | |
| # 指定 tar_file.txt 文件路径和输出目录 | |
| tar_file_list = 'tar_file.txt' | |
| output_directory = '/group/40033/public_datasets/sam_selection/' | |
| # 调用函数 | |
| extract_tar_files(tar_file_list, output_directory) | |
| print("所有文件已解压完成。") |