Answer
These transformations generate varied versions of the same image so the model learns to recognize objects under different conditions instead of memorizing exact pixel patterns.
Real-world example A team training a plant disease detector uses image augmentation to rotate and flip leaf photos, helping the model recognize diseased leaves from any angle.