Encounter "TypeError: only integer scalar arrays can be converted to a scalar index" when using random flip #529
Closed
Description
🐛Bug
To reproduce
augment = tio.Compose([
tio.RandomFlip(p=0.5),
#tio.RandomAffine(),
#tio.RandomGamma(p=0.5),
#tio.RandomNoise(p=0.5)
])
trainset = tio.SubjectsDataset(subjects=train_subjects, transform=tio.Compose([augment, preprocess]))
train_queue = tio.Queue(subjects_dataset=trainset,
max_length=max_length,
sampler=sampler,
samples_per_volume=samples_per_volume,
num_workers=0,
shuffle_patches=False,
shuffle_subjects=False)
train_loader = DataLoader(train_queue, batch_size=batch_size, num_workers=0, pin_memory=False)
for step, batch_data in enumerate(loader):
...Expected behavior
Training patches shall be augmented.
Actual behavior
Traceback (most recent call last):
File "<input>", line 85, in <module>
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/tqdm/std.py", line 1178, in __iter__
for obj in iterable:
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 435, in __next__
data = self._next_data()
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 475, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torchio/data/queue.py", line 165, in __getitem__
self._fill()
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torchio/data/queue.py", line 229, in _fill
subject = self._get_next_subject()
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torchio/data/queue.py", line 239, in _get_next_subject
subject = next(self.subjects_iterable)
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 435, in __next__
data = self._next_data()
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 1085, in _next_data
return self._process_data(data)
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 1111, in _process_data
data.reraise()
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torch/_utils.py", line 428, in reraise
raise self.exc_type(msg)
TypeError: Caught TypeError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torch/utils/data/_utils/worker.py", line 198, in _worker_loop
data = fetcher.fetch(index)
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torchio/data/dataset.py", line 85, in __getitem__
subject = self._transform(subject)
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torchio/transforms/transform.py", line 121, in __call__
transformed = self.apply_transform(subject)
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torchio/transforms/augmentation/composition.py", line 47, in apply_transform
subject = transform(subject)
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torchio/transforms/transform.py", line 121, in __call__
transformed = self.apply_transform(subject)
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torchio/transforms/augmentation/composition.py", line 47, in apply_transform
subject = transform(subject)
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torchio/transforms/transform.py", line 121, in __call__
transformed = self.apply_transform(subject)
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torchio/transforms/augmentation/spatial/random_flip.py", line 60, in apply_transform
transformed = transform(subject)
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torchio/transforms/transform.py", line 121, in __call__
transformed = self.apply_transform(subject)
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torchio/transforms/augmentation/spatial/random_flip.py", line 91, in apply_transform
_flip_image(image, axes)
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/torchio/transforms/augmentation/spatial/random_flip.py", line 128, in _flip_image
data = np.flip(data, axis=spatial_axes)
File "/home/zhao/anaconda3/envs/torch/lib/python3.6/site-packages/numpy/lib/function_base.py", line 206, in flip
indexer[axis] = slice(None, None, -1)
TypeError: only integer scalar arrays can be converted to a scalar indexSystem info
When I cancel random flip augmentation, the code would work fine.
I suppose this is because of the version of numpy. For latest numpy the error would occur, but for numpy version 1.19.1 the error won't happen.
System ubuntu 16.04, torchio version 0.18.37, python 3.6, pytorch 1.7.1, numpy 1.19.5.