Image Augmentation

Summary

Applying random transformations (flips, rotations, color jitter) to training images to artificially expand a dataset and improve generalization.

• 1Add an augmentation pipeline (e.g. `torchvision.transforms`) to a training run.
• 2Compare validation accuracy with and without augmentation on a small dataset.
• 3Learn which augmentations make sense for your specific task (don't flip text-containing images, for example).