I am about to build CNN for image classification. I have a rather small dataset and have done some data augmentation to make it bigger. While doing so, I got a little confused whether what I am doing is right or not.
If I have a dataset which contains a lot of augmented data and I split it into train/validation/test later, then test and validation sets will include my previously augmented data as well. Is it OK to do so or should I split my data at first and then do the augmentation only on train set images?