I’m not sure as I’m not familiar with your code, but it could represent the number of channels.
Preprocessing should be done in all datasets (using the same parameters as for the training).
Data augmentation is usually only done during training, although you could also use test time augmentation, average your predictions, and hope for a slight performance boost.
What have you tried so far? Doesn’t cv2.resize() work?