fastai.dataset.ImageClassifierData.from_paths without transformations?

[rik (Rik de Deken)]

Just found a duplicate post here:

Transforms and ImageClassifierData

Is it possible to use ImageClassifierData without defining any transforms? For example, if I just want to quick and dirty play around with the functions, can I leave tfms=(None, None) as the default parameter to ImageClassifierData? If I try to do that I get an attribute error AttributeError: 'NoneType' object has no attribute 'sz' Is there a reason why data augmentation seems to be required? Is there a way to not augment your data? What does the sz parameter do? It seems to only be relevant t…

and also the answer to my question:

@yinterian

Harry, you need to get the data “ready” for training so it needs some basic transforms. If you use this you don’t get data augmentation. sz x sz x 3 is the size of the images that you will be training on.

tfms = tfms_from_model(f_model, sz)

Here is an example on why you need basic transformations. You may have images of different sizes but you need training batches to a consistent size. In order to get that your images need to have all the same size. In this library they all get transform into a square. The library has different ways of doing that.

So thanks again @yinterian !