I have a batch of images in the usual tensor form (B, C, H, W). To apply the usual sets of rotations and flips, I’m using the construction here: https://github.com/pytorch/vision/issues/566#issuecomment-814221986.
However, this isn’t quite doing what I want. Transforming and augmenting images — Torchvision 0.16 documentation states:
Randomized transformations will apply the same transformation to all the images of a given batch
I want a different random transform to be applied to each image in the batch, but I would still like to be able to process all the images together in a batch (avoiding an explicit loop). Is there any method available to do this?