.ricap() and .cutmix() now available
I’m sorry for the delay, but I’ve been busy with some other stuff.
I’ve eventually created a notebook that contains examples of how ricap and cutmix can be used. You just need to add .ricap() or .cutmix() to learn in the same way we do with mixup.
I’ve also created some functionality to visualize how single-image transforms (flip, rotate, etc) or the multi-image transforms (mixup, ricap and cutmix). I think it really helps if you can see the output of these transformations.
I’ve run some very brief tests on Imagenette to check the callbacks work correctly and performance was: recap > cutmix > mixup. I just have a single GPU and it takes considerable time to run the tests, so bear this in mind, as there are very few runs.
I’d say though that both ricap and cutmix seem to be very competitive with mixup (if not slightly better), so it may be worth trying them.
Something interesting is that the impact on time performance is negligable.
You can find the notebook and required code in fast_extensions, where I’m planning to share some additional fastai code that I’m creating.
Please, feel free to use this code as you wish. I’d be interested to know if you use ricap or cutmix and get any performance improvement.