Data augmentation: dynamic blend
I’ve created a new notebook in my fastai_extensions repo to show how you can easily apply many different types of data transformation dynamically to your image datasets. I call this approach dynamic blend.
I’ve been lucky Jeremy’s (thanks!) seen it and came up with a much better definition that mine on Twitter:
This is a powerful abstraction for image data augmentation that generalizes MixUp, Cutout, CutMix, RICAP, and more, and allows annealing of the amount of augmentation during training (to support curriculum learning) - Jeremy Howard
If you are interested, you can start using it an ‘invent’ your own transformation. There’s more info in this thread.