复现SCI图像增强（Toward fast, flexible, and robust low-light image enhancement.）

运行train.py报错

> File "/home/uriky/桌面/SCI-main/SCI-main/train.py", line 105, in main
>     train_queue = torch.utils.data.DataLoader(   File "/home/uriky/anaconda3/envs/AA/lib/python3.8/site-packages/torch/utils/data/dataloader.py",
> line 277, in __init__
>     sampler = RandomSampler(dataset, generator=generator)  # type: ignore[arg-type]   File
> "/home/uriky/anaconda3/envs/AA/lib/python3.8/site-packages/torch/utils/data/sampler.py",
> line 97, in __init__
>     raise ValueError("num_samples should be a positive integer " ValueError: num_samples should be a positive integer value, but got
> num_samples=0

原因是没有切换自己的数据集路径

  train_low_data_names = './data/train_images'  # 替换为实际的训练数据集路径test_low_data_names = './data/3dgspicture'

报错

yield from torch.randperm(n, generator=generator).tolist()
RuntimeError: Expected a ‘cuda’ device type for generator but found
‘cpu’

将随机数生成器移动到 GPU 上

再运行train.py训练

成功！！！！