For the purposes of training a Convolutional Neural Network Classifier, should image augmentation be done before or after resizing the training images?
To reduce file size and speed up training time, developers often resize training images to a set height and width using something like PIL (Python Imaging Library).
If the images are augmented (to increase training set size), should it be done before or after resizing the members of the set?
For simplicity sake, it would probably be faster to augment the images after resizing, but I am wondering if any useful data is lost in this process. I assume it may depend on the method used to resize the images (cropping, scaling technique, etc.)