| |
| |
|
|
| |
| |
|
|
| |
| |
| |
| |
| |
| |
| |
| |
| import os |
| import json |
| from PIL import Image |
| from tqdm import tqdm |
|
|
| def generate_jsonl_from_folder( |
| image_dir, |
| output_jsonl_path, |
| code_dir_name='code', |
| caption_emb_dir_name='caption_emb', |
| control_dir_name='control', |
| label_dir_name='label' |
| ): |
| """ |
| 自动从 image 文件夹构建 .jsonl 文件，记录 image_path 和 code_name |
| 适配 Text2ImgDataset 类的数据读取格式 |
| """ |
| image_files = sorted([f for f in os.listdir(image_dir) if f.endswith('.png')]) |
| parent_dir = os.path.basename(os.path.normpath(image_dir)) |
|
|
| with open(output_jsonl_path, 'w') as f: |
| for file in tqdm(image_files, desc="Generating .jsonl"): |
| image_path = os.path.join(image_dir, file) |
| code_name = os.path.splitext(file)[0] |
|
|
| |
| code_path = os.path.join(os.path.dirname(image_dir), code_dir_name, f"{code_name}.npy") |
| caption_emb_path = os.path.join(os.path.dirname(image_dir), caption_emb_dir_name, f"{code_name}.npz") |
| control_path = os.path.join(os.path.dirname(image_dir), control_dir_name, f"{code_name}.png") |
| label_path = os.path.join(os.path.dirname(image_dir), label_dir_name, f"{code_name}.png") |
|
|
| if not (os.path.exists(code_path) and os.path.exists(caption_emb_path) |
| and os.path.exists(control_path) and os.path.exists(label_path)): |
| print(f"⚠️ 缺失对应文件: {code_name}") |
| continue |
|
|
| data = { |
| "image_path": image_path, |
| "code_name": int(code_name) |
| } |
| f.write(json.dumps(data) + '\n') |
|
|
| print(f"✅ 成功生成: {output_jsonl_path}") |
|
|
|
|
| if __name__ == '__main__': |
| |
| root_dir = '/media2/user/data/wxy/ControlAR_old/data/Captioned_ADE20K/train' |
| image_dir = os.path.join(root_dir, 'image') |
| output_jsonl = os.path.join(root_dir, 'train_to_use.jsonl') |
|
|
| generate_jsonl_from_folder( |
| image_dir=image_dir, |
| output_jsonl_path=output_jsonl, |
| code_dir_name='code', |
| caption_emb_dir_name='caption_emb', |
| control_dir_name='control', |
| label_dir_name='label' |
| ) |
|
|
