wxy-ControlAR / test_dataset_t2icontrol.py
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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()