---
created: 2025-08-03 21:19:11
tags:
  - "Research"
  - "复现"
  - "MDMS"
  - "报错"
  - "评估"
---

# eval_diffusion.py

```bash
$ python eval_diffusion.py
Using device: cuda
Note: Currently supports evaluations (restoration) when run only on a single GPU!
=> using dataset 'lowlight'
=> evaluating lowlight test set...
filepath:/home/student/MDMS/datasets
Traceback (most recent call last):
  File "eval_diffusion.py", line 83, in <module>
    main()
  File "eval_diffusion.py", line 73, in main
    _, val_loader = DATASET.get_loaders(parse_patches=False, validation=args.test_set)
  File "/home/student/MDMS/datasets/lowlight.py", line 21, in get_loaders
    train_dataset = lowlightDataset(dir=os.path.join(self.config.data.data_dir, 'data', 'lowlight', 'train'),
  File "/home/student/MDMS/datasets/lowlight.py", line 69, in __init__
    assert len(images) == 485
AssertionError
```



- 主要是加了断言, 改一下`lowlight.py`里面的结构

```python
class lowlightDataset(torch.utils.data.Dataset):
    def __init__(self, dir, patch_size, n, transforms, train, filelist=None, parse_patches=True):
        super().__init__()

        if filelist is None:
            lowlight_dir = dir
            input_names, gt_names = [], []

            filepath = os.path.dirname(__file__)
            print(f"filepath:{filepath}")
            lowlight_dir = os.path.join(filepath, lowlight_dir)

            # lowlight train filelist
            lowlight_inputs = os.path.join(lowlight_dir, 'input')
            
            # 确保目录存在
            if not os.path.exists(lowlight_inputs):
                os.makedirs(lowlight_inputs, exist_ok=True)
                print(f"Created directory: {lowlight_inputs}")
            
            images = [f for f in listdir(lowlight_inputs) if isfile(os.path.join(lowlight_inputs, f))]
            
            # 移除断言检查，改为打印信息
            print(f"Found {len(images)} images in {lowlight_inputs}")
            
            input_names += [os.path.join(lowlight_inputs, i) for i in images]
            gt_names += [os.path.join(os.path.join(lowlight_dir, 'gt'), i) for i in images]
            print(f"Number of input images: {len(input_names)}")
            
            if len(images) == 0:
                raise RuntimeError(f"No images found in {lowlight_inputs}. Please ensure the dataset is properly set up.")

            x = list(enumerate(input_names))
            random.shuffle(x)
            indices, input_names = zip(*x)
            gt_names = [gt_names[idx] for idx in indices]
            self.dir = None
        else:
            self.dir = dir
            filepath = os.path.dirname(__file__)
            dir = os.path.join(filepath, dir)
            train_list = os.path.join(dir, filelist)
            with open(train_list) as f:
                contents = f.readlines()
                input_names = [i.strip() for i in contents]
                gt_names = [i.strip().replace('input', 'gt') for i in input_names]

        self.input_names = input_names
        self.gt_names = gt_names
        self.patch_size = patch_size
        self.transforms = transforms
        self.n = n
        self.parse_patches = parse_patches
        self.batchnum = 0
        self.batchsize = 1
        self.train=train
```

- 刚改完又出问题...

```bash
$ python eval_diffusion.py
Using device: cuda
Note: Currently supports evaluations (restoration) when run only on a single GPU!
=> using dataset 'lowlight'
=> evaluating lowlight test set...
filepath:/home/student/MDMS/datasets
Found 15 images in /home/student/MDMS/datasets/scratch/LLIE/data/lowlight/train/input
Number of input images: 15
=> creating denoising-diffusion model with wrapper...
parameters: 213,144,003
Pre-trained diffusion model path is missing!
Traceback (most recent call last):
  File "eval_diffusion.py", line 83, in <module>
    main()
  File "eval_diffusion.py", line 79, in main
    model.restore(val_loader, validation=args.test_set, r=args.grid_r,use_align=True)
  File "/home/student/MDMS/models/restoration.py", line 34, in restore
    for i, (x, y,wd,ht) in enumerate(val_loader):
  File "/home/student/.conda/envs/MDMS/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 521, in __next__
    data = self._next_data()
  File "/home/student/.conda/envs/MDMS/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 561, in _next_data
    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
  File "/home/student/.conda/envs/MDMS/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/home/student/.conda/envs/MDMS/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 49, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/home/student/MDMS/datasets/lowlight.py", line 208, in __getitem__
    res = self.get_images(index)
  File "/home/student/MDMS/datasets/lowlight.py", line 202, in get_images
    input_img = input_img.resize((wd_new, ht_new), PIL.Image.ANTIALIAS)
AttributeError: module 'PIL.Image' has no attribute 'ANTIALIAS'
```