Comments (4)
Will take a look to research it a bit more. I ment Subject is inheriting dict in my previous comment btw
from torchio.
I saw that torchio.Image is inheriting from dict class Image(dict):, so that was leading to some confusion.
I think this is an important feature. Because Image is already inheriting from dict it should not be that much work? Do you have ideas? Maybe I want to contribute, but I am still taking a dive into the codebase
At the moment, transforms are applied to all images by default (although intensity transforms are only applied to scalar images). Maybe the easiest would be to add an exclude
kwarg in Transform
. This kwarg will be used within each transform like:
if image_name in self.excluded_images:
continue
from torchio.
Yes, I understood!
from torchio.
Don't hesitate to ask if you need anything.
from torchio.
Related Issues (20)
- Suggestions the modifying default value of prefetch_factor and the argument to set it for minimize the blocking-bottleneck between fetch subject and generate patch in Queue HOT 1
- Different transforms applied to CT and label HOT 11
- The Affine matrix does not change after applying the augmentations HOT 3
- Custom loader not used when loading data lazily HOT 2
- Seed is not working HOT 2
- Silenced exception makes it harder to debug custom Transforms HOT 5
- Resample
- tio.Resample does not work with custom image class HOT 2
- Setting NUM_SAMPLES when using sampler with Queue HOT 3
- RescaleIntensity - multiple calls HOT 9
- Return sampled parameters upon request HOT 3
- Halve queue length when using DDP HOT 2
- bug in rotation part of tio.transforms.RandomAffine HOT 4
- get_subjects_from_batch has a hick-up with int metadata HOT 5
- masking_method in Mask class is not saved as argument (preventing applying the inverse transform)
- RandomAffine raises an error when isotropic=True and 3 elements are given for scales HOT 10
- Queue is not respecting the batch size HOT 1
- Resample an image by providing only the target affine HOT 1
- Supporting PyTorch 2.3 HOT 17
- Cannot copy subclass of Subject with keyword arguments HOT 2
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from torchio.