Discussion about default unnormalize method for pytorch tensor about torchshow HOT 3 OPEN

Good suggestion! I think we could do it if this is a common normalization preset. In fact, what you described can be extended to all the zero-centralize normalizations as well. The tricky part that I can think of is how to determine if the data is zero-centralized rather than just happen to fall between that range. In other word, is simply checking the [-1, 1] range (or [-M, M] for more general cases) sufficient to determine these kind of inputs?

from torchshow.

I think simply checking [-1, 1] is enough. Is there any other possible situation? For normal images it seems that these are the only cases. For other special cases, they can use set_image_mean and set_image_std.

from torchshow.

Right, maybe we can try to handle the [-1, 1] case for now. Would you be able to create an PR for this feature and some testing cases so we can review and discuss further?

from torchshow.