I am working with convolutional neural networks, and I have seen that often we need to pre process the images before feeding them to the network. In particular, I have seen that often we have to do image augmentation using an image generator. Now, when looking for a clarification on why we need to do this, I came across an article which says:
Image Augmentations techniques are methods of artificially increasing the variations of images in our data-set by using horizontal/vertical flips, rotations, variations in brightness of images, horizontal/vertical shifts etc.
What I don't understand is what is the variation of a dataset.
Can somebody help me? Thanks in advance.