Why should I use data augmentation as Keras layer
Data Augmentation is basically a technique to increase the diversity of your training set by applying random (but realistic) transformations such as image rotation. Training deep learning neural network models on more data can result in more skillful models, and the augmentation techniques can create variations of the images that can improve the ability of the fit models to generalize what they have learned to new images. So you can decrease the rate of overfitting or take some precautions for it.
The Keras deep learning neural network library provides the capability to fit models using image data augmentation via the ImageDataGenerator class. By using this class you are able to modify the dataset by using its a lot of functionality.