I am creating some training samples for an Object Classification deep learning model, which I will then export. I know that chip/tile size is important because they need to be big enough to cover the objects of interest. However, how important is stride size? I know that for Object Detection, stride size is important because it ensures that there is some context surrounding the objects to be detected. However, for my model, the objects do not need to be detected as they are all already delineated, they only need to be classified. Also, for my model in question, the surroundings of the objects are not relevant to their classification.
So, when exporting the data, should I bother with a stride size or just leave this parameter blank?
