text: import os
  
  import torch.utils.data as data
  import torchvision.transforms as T
  from PIL import Image
  
  
  class LowLightDatasetTest(data.Dataset):
      def __init__(self, root, reside=False):
          self.root = root
          self.items = []
  
          subsets = os.listdir(root)
          for subset in subsets:
              img_root = os.path.join(root, subset)
              img_names = list(sorted(os.listdir(img_root)))
  
              for img_name in img_names:
                  self.items.append((
                      os.path.join(img_root, img_name),
                      subset,
                      img_name
                  ))
  
          self.preproc = T.Compose(
              [T.ToTensor()]
          )
          self.preproc_raw = T.Compose(
              [T.ToTensor()]
          )
  
      def __getitem__(self, idx):
          img_path, subset, img_name = self.items[idx]
          img = Image.open(img_path).convert("RGB")
          img = img.resize((img.width // 8 * 8, img.height // 8 * 8), Image.ANTIALIAS)
          img_raw = self.preproc_raw(img)
  
          return img_raw, subset, img_name
  
      def __len__(self):
          return len(self.items)
  