How to add augmented images to original dataset using Pytorch?
From my understanding, RandomHorizontalFlip etc. replace image rather than adding new images to dataset. How do I increase my dataset size by adding augmented images to dataset using PyTorch?

I have gone through the links posted &amp; haven't found a solution. I want to increase the data size by adding flipped/rotated images - but the post addresses the in-place processing of images.

Thanks.

Why do you want it? Generally speaking, it is enough to increase the number of epochs over the dataset, and your model will see the original and the augmented version of every image at least once (assuming a relatively high number of epochs).
Explanation:
For instance, if your augmentation has a chance of 50% to be applied, after 100 epochs, for every sample you will get ~50 samples of the original image and ~50 augmented samples. So, increasing the dataset size is equivalent to add epochs but (maybe) less efficient in terms of memory (need to store the images in memory to have high performances).
