MuarAugment: Easiest Way to SOTA Data Augmentation

I wanted an easy way to get a state-of-the-art image augmentation pipeline with no manual iteration, no separate models to train and no thinking. To provide that, I created MuarAugment (Model Uncertainty- And Randomness-based Augmentation), a GPU-supported Python package built on Pytorch, Albumentations and Kornia. There are a few resources you can use to master MuarAugment. There are Colab tutorials demonstrating MuarAugment. Most of the material in this article comes from those.