Comments (2)
Hi @tobiashepp
That's great! I'm glad you're finding it useful. Please don't hesitate to post more feedback or issues here.
It would be amazing to include your sampler here if you think it's worth it. You can create a PR whenever you're ready and I'll review it.
Someone told me about that bug when the patch size is the same as the image. I'll create an issue. Thanks for reporting!
from torchio.
FYI I've started working on more efficient samplers in #175.
from torchio.
Related Issues (20)
- Combined Affine/Elastic augmentations HOT 1
- The rotation given by Random Affine not accurate HOT 5
- (Optional) state_dict for each transform (reproducibility) HOT 2
- Wrong link to docs in Getting Started tutorial HOT 2
- 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
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from torchio.