Make the resize anchor edge variable if size is scalar

🚀 Feature

Make the resize anchor edge variable if size is scalar.

Motivation

Right now torchvision.transforms.Resize() assumes that the smaller edge of the image should be resized to size if its an int.

https://github.com/pytorch/vision/blob/d1e134c71b94a5975dcbf16927ed608dac54fdfe/torchvision/transforms/transforms.py#L239-L240

That can be cumbersome if the user wants for example an image that is not larger than x or wants a specific edge to be this size.

Pitch

I propose we add a edge keyword argument which can be one of "short" (default), "long", "vert", and "horz". Based on this we calculate the size.

cc @vfdev-5

[NicolasHug]

I agree that edge="long", max_size=max_size doesn’t make much sense, we could warn or error in this case. Regarding min_size, I would also agree that this parameter is not needed (on top of the redundancy, it might be impossible to satisfy both min_size and max_size).

@fmassa would you mind sharing your thoughts on:

• introducing edge only
• introducing max_size only
• introducing both

My personal opinion is that they’re (mostly) orthogonal concepts and that usage wouldn’t be confusing as long as docs are properly informative. But I’m not familiar enough with the use-cases to really assess whether the added complexity is worth it.

[NicolasHug]

From what I can tell, detectron2’s ResizeShortestEdge corresponds to torchvision’s current resize with the max_size parameter.

Regarding the other transforms, they don’t allow size to be an int, which is what we’re concerned with (Detectron2.resize accepts an int but it will output a square size x size image). In tensorflow, preserve_aspect_ratio=True makes size act as a bounding box for the resized image, so it has a bit of a max_size flavour too.

I could not find similar things in classyvision or in PIL