FileNotFoundError: File not found: "affine"

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Problem summary

Hi,

I am trying to apply the Torchio tutorial on a different dataset (Promise12 data set), first I converted the data into NiFti (.mhd)—>(.nii), then I followed the steps found on the google colab but after I applied the # Visualize axial slices of one batch step I got this error “FileNotFoundError: File not found: “affine””

Code for reproduction

images_dir = Path("TargetImage")
labels_dir = Path("Targetlabel")
image_paths = sorted(images_dir.glob('*.nii'))
label_paths = sorted(labels_dir.glob('*.nii'))
assert len(image_paths) == len(label_paths)

subjects = []
for (image_path, label_path) in zip(image_paths, label_paths):
    subject = tio.Subject(
        prostate=tio.ScalarImage(image_path),
        mask=tio.LabelMap(label_path),
    )
    subjects.append(subject)
dataset = tio.SubjectsDataset(subjects)
print('Dataset size:', len(dataset), 'subjects')

#Patch-based:
training_batch_size = 32
validation_batch_size = 2 * training_batch_size

patch_size = 24
samples_per_volume = 5
max_queue_length = 300
sampler = tio.data.UniformSampler(patch_size)

patches_training_set = tio.Queue(
    subjects_dataset=training_set,
    max_length=max_queue_length,
    samples_per_volume=samples_per_volume,
    sampler=sampler,
    num_workers=num_workers,
    shuffle_subjects=True,
    shuffle_patches=True,
)
print (patches_training_set)

patches_validation_set = tio.Queue(
    subjects_dataset=validation_set,
    max_length=max_queue_length,
    samples_per_volume=samples_per_volume,
    sampler=sampler,
    num_workers=num_workers,
    shuffle_subjects=False,
    shuffle_patches=False,
)
training_loader_patches = torch.utils.data.DataLoader(patches_training_set, batch_size=training_batch_size)

validation_loader_patches = torch.utils.data.DataLoader(patches_validation_set, batch_size=validation_batch_size)
# Visualize axial slices of one batch
one_batch = next(iter(training_loader_patches))
k = int(patch_size // 4)
batch_mri = one_batch['prostate'][tio.DATA][..., k]
batch_label = one_batch['mask'][tio.DATA][:, 1:, ..., k]
slices = torch.cat((batch_mri, batch_label))
image_path = 'batch_patches.png'
torchvision.utils.save_image(
    slices,
    image_path,
    nrow=training_batch_size,
    normalize=True,
    scale_each=True,
)
display.Image(image_path)

Actual outcome

It should appear the training result

Error messages

FileNotFoundError: File not found: "affine"

Expected outcome

It should appear the training result

System info

No response

[shathaa1983]

Hi, Thank you, the code is working fine after I update the Torchio version.

[fepegar]

Also, can you please upgrade TorchIO and see if that solves your issue?