Hello Fikrat!



 Fikrat:

I have RandomScaleCrop function in train set, such that it scales RGB images which leads  images to be descructive, in other words, plenty of reasonable pixels are destroied.
…
I shoud eliminated RandomScaleCrop in order to remove such an occurence, or I have to leave it as now.


Without knowing more about your actual problem, it’s hard to
give reliable advice.
I believe that you have a segmentation problem, in that you
classify individual pixels within an  image to be, for example,
foreground vs. background.
This is distinct from a classification problem, where you classify
individual images to be, say, an image of a cat vs. a dog.
Some thoughts:
I speculate that you are using RandomScaleCrop /
RandomResizedCrop to augment your data.  (RandomScaleCrop
looks like it’s a third-party class that isn’t part of pytorch proper.)
My intuition is that rescaling / resizing in order to augment your
data could make sense for image classification, but would make
less sense for image segmentation (where boundaries between
different kinds of pixels that define the segments could get blurred
by the rescaling).  That’s just my guess, though.
(As an aside, it might be better to ask new questions like this
by starting a new topic, rather than adding them to an existing
thread.  You can always link to the old thread if there is useful
context you don’t want to repeat.)
Best.
K. Frank