Hi, I have “images” with a large number of channels and there are some transformations that I would like to apply to these. Specifically I would like to perform rotations, cropping etc. These are all implemented in torchvision, however these require PIL images as input. This is problem, as PIL images require a specific number range of channels. Is there a way to support an arbitrary number of channels?
If not, is there an efficient way to take a tensor, and for each channel convert it to a PIL image, perform my transformations, convert back to tensors and stack along the channel dimension? Kinda like a along-a-dimension map-reduce function (that is hopefully efficient, and in and of itself would be endlessly useful for other applications that I am working on).
Ideally I would like to not rely on PIL at all.