ValueError: Sequence must have length 1, got 3.

[markvvw]

class SegDataset(Dataset):
    def __init__(self, root_dir, train, size):
        self.root_dir = root_dir
        self.train = train
        self.size = size

    def __len__(self):
        list = os.listdir(self.root_dir + '/ss/')
        len_data = len(list)
        print(len_data)
        return len_data

    def __getitem__(self, index):
        # conect path
        pathImage = glob.glob(self.root_dir + '/ss/*')[index]
        pathLabel = glob.glob(self.root_dir + '/mask/*')[index]
        # read nii.gz
        Imgloader = LoadImage(image_only=True)
        Labloader = LoadImage(image_only=True, dtype=np.uint8)
        img = Imgloader(pathImage)
        lab = Labloader(pathLabel)
        
        Totnsor = ToTensor(device="cuda:0")  # numpy TO tensor √
        img = Totnsor(img)
        lab = Totnsor(lab)
        img = img.unsqueeze(dim=0)  # add channel √
        lab = lab.unsqueeze(dim=0)
        # resize √
        Resizer = Resize(spatial_size=(self.size, self.size))
        img = Resizer(img)
        lab = Resizer(lab)
        print(pathImage,pathLabel, '//',index,img.shape,lab.shape) ###################################
        # normalization & rescale
        Normaler = NormalizeIntensity(subtrahend=0, divisor=.5, nonzero=True)
        img = Normaler(img)
        Rescler = ScaleIntensity(maxv=1, minv=0)
        img = Rescler(img)

        if self.train is True:
            # rotate flip
            if random.choice([True, False]):
                Rflip = Flip(spatial_axis=0)
                img = Rflip(img)
                lab = Rflip(lab)
            if random.choice([True, False]):
                RN = np.random.randint(-45, 45, 1).item()/100
                Rrotate = Rotate(angle=(0, 0, RN))
                img = Rrotate(img)
                lab = Rrotate(lab)
        return img, lab

---

print('mission start')
for epoch in range(start, start+2):
    loss, step = 0, 0
    model.train()

    for img, lab in loader_train:
        print(img.shape)

---

ValueError Traceback (most recent call last)
f:\jupyterlab\Project pipeline\mulStage.ipynb Cell 5 in <cell line: 2>()
3 loss, step = 0, 0
4 model.train()
----> 6 for img, lab in loader_train:
7 print(img.shape)

File f:\Python310\lib\site-packages\torch\utils\data\dataloader.py:530, in _BaseDataLoaderIter.next(self)
528 if self._sampler_iter is None:
529 self._reset()
--> 530 data = self._next_data()
531 self._num_yielded += 1
532 if self._dataset_kind == _DatasetKind.Iterable and
533 self._IterableDataset_len_called is not None and
534 self._num_yielded > self._IterableDataset_len_called:

File f:\Python310\lib\site-packages\torch\utils\data\dataloader.py:570, in _SingleProcessDataLoaderIter._next_data(self)
568 def _next_data(self):
569 index = self._next_index() # may raise StopIteration
--> 570 data = self._dataset_fetcher.fetch(index) # may raise StopIteration
571 if self._pin_memory:
572 data = _utils.pin_memory.pin_memory(data)

File f:\Python310\lib\site-packages\torch\utils\data_utils\fetch.py:49, in _MapDatasetFetcher.fetch(self, possibly_batched_index)
...
151 if len(tup) == dim:
152 return tuple(tup)
--> 154 raise ValueError(f"Sequence must have length {dim}, got {len(tup)}.")

ValueError: Sequence must have length 1, got 3.

How to address this error? thanks

[markvvw]

        if random.choice([True, False]):
            RN = np.random.randint(-45, 45, 1).item()/100
            Rrotate = Rotate(angle=(0, 0, RN)) <-----PROBLEM, 
            img = Rrotate(img)
            lab = Rrotate(lab)
    return img, lab

[wyli]

sure, for 2d images you can define one rotation angle.

[markvvw]

对的，我刚开始用jupyter，代码出问题的地方提示的不是很明确，因此找了好几天。感谢，早点睡吧。

[markvvw]

I have found the problem.