When applying deep learning models to tasks on a different dataset, the image augmentation operations must often be modified to account for differing image characteristics. For instance, images within the ImageNet dataset are typically larger and possess varying dimensions, in stark contrast to the images found in the CIFAR-10 dataset. Consequently, an augmentation pipeline designed for one dataset must be explicitly adjusted to suit the resolution and geometric properties of the new target dataset.