Download check.py from LanguageBind/StyleVideoDataSet: direct link, hf CLI and curl.
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- Download file 1.84 kB
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https://huggingface.co/datasets/LanguageBind/StyleVideoDataSet/resolve/6fbeedaf6953a722f735fe72d8f2aa1a3505f1cf/check.py
- Command line
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hf download hf://datasets/LanguageBind/StyleVideoDataSet@6fbeedaf6953a722f735fe72d8f2aa1a3505f1cf/check.py
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curl -L -o check.py https://huggingface.co/datasets/LanguageBind/StyleVideoDataSet/resolve/6fbeedaf6953a722f735fe72d8f2aa1a3505f1cf/check.py
1.84 kB
| import json | |
| from tqdm import tqdm | |
| def check_text_fields(json_file_path): | |
| """ | |
| 检查JSON文件中所有字典的text字段是否为空 | |
| Args: | |
| json_file_path (str): JSON文件路径 | |
| """ | |
| try: | |
| # 读取JSON文件 | |
| with open(json_file_path, 'r', encoding='utf-8') as f: | |
| data = json.load(f) | |
| # 检查是否为列表 | |
| if not isinstance(data, list): | |
| raise ValueError("JSON文件应该包含一个列表") | |
| # 检查每个字典的text字段 | |
| errors = [] | |
| for i, item in tqdm(enumerate(data)): | |
| if not isinstance(item, dict): | |
| errors.append(f"索引 {i}: 不是字典类型") | |
| continue | |
| print(len(item['text'])) | |
| if 'text' not in item: | |
| errors.append(f"索引 {i}: 缺少text字段") | |
| elif item['text'] is None or item['text'].strip() == '': | |
| errors.append(f"索引 {i}: text字段为空") | |
| else: | |
| print(f"索引 {i}: text字段正常") | |
| # 输出检查结果 | |
| if errors: | |
| print(f"发现 {len(errors)} 个错误:") | |
| for error in errors: | |
| print(f" - {error}") | |
| raise ValueError("存在空的text字段") | |
| else: | |
| print("所有text字段都正常") | |
| except FileNotFoundError: | |
| print(f"错误: 文件 {json_file_path} 不存在") | |
| except json.JSONDecodeError: | |
| print(f"错误: {json_file_path} 不是有效的JSON文件") | |
| except Exception as e: | |
| print(f"错误: {str(e)}") | |
| # 使用示例 | |
| json_file_path = "/mnt/new_cpfs/zhubin/VideoX-Fun/datasets/TriData/step2_multi_style_data_2w.json" # 替换为你的JSON文件路径 | |
| check_text_fields(json_file_path) |