| import os | |
| import argparse | |
| import torch | |
| from torchvision import transforms | |
| from torch.utils.data import DataLoader | |
| from PIL import Image | |
| from dataset.t2i_control import T2IControlCode | |
| from tqdm import tqdm | |
| def get_args(): | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--code_path', type=str, required=True, help='根目录,包含 code/control/image/caption_emb 等文件夹') | |
| parser.add_argument('--code_path2', type=str, default=None, help='第二组数据路径 (可选)') | |
| parser.add_argument('--image_size', type=int, default=512) | |
| parser.add_argument('--downsample_size', type=int, default=8) | |
| parser.add_argument('--condition_type', type=str, default='seg', choices=['seg', 'depth', 'canny', 'hed', 'lineart'], help='控制类型') | |
| parser.add_argument('--get_image', action='store_true', help='是否返回 image') | |
| parser.add_argument('--get_prompt', action='store_true', help='是否返回 prompt') | |
| parser.add_argument('--get_label', action='store_true', help='是否返回 label') | |
| parser.add_argument('--max_show', type=int, default=5, help='最多显示多少条样本') | |
| return parser.parse_args() | |
| def main(): | |
| args = get_args() | |
| dataset = T2IControlCode(args) | |
| print(f"\n📦 数据集大小: {len(dataset)}") | |
| loader = DataLoader(dataset, batch_size=1, shuffle=False, num_workers=2, collate_fn=dataset.collate_fn) | |
| for i, batch in enumerate(tqdm(loader)): | |
| print(f"\n🟡 Sample #{i}") | |
| print(f" - code shape: {batch['code'].shape}") | |
| print(f" - control shape: {batch['control'].shape}") | |
| print(f" - caption_emb shape: {batch['caption_emb'].shape}") | |
| print(f" - attention mask shape: {batch['attn_mask'].shape}") | |
| print(f" - valid: {batch['valid'].item()}") | |
| if args.get_image: | |
| print(f" - image shape: {batch['image'].shape}") | |
| if args.get_prompt: | |
| print(f" - prompt: {batch['prompt']}") | |
| if args.get_label: | |
| print(f" - label shape: {batch['label'].shape}") | |
| if i + 1 >= args.max_show: | |
| break | |
| if __name__ == "__main__": | |
| main() | |