Looking at this document:
There is a way to implement albumentations transforms for segmentation, via ItemTransform.
There is a way to implement different albumentations transforms in training vs. validation, via RandTransform.before_call().
What I can’t seem to do is having separate albumentations transforms in training vs validation for a segmentation problem (image + mask). ItemTransform takes tuples, but doesn’t have before_call, so I can’t tell whether it’s training or validation. RandTransform has before_call and I can set split_idx but I don’t see a way to handle image/mask tuples there.
How to do both?