Implementation of various data augmentation techniques in TensorFlow 2.x. They can be easily used in your training pipeline. This repository contain the supplementary notebooks for the Modern Data Augmentation Techniques for Computer Vision(Weights and Biases) report.
Note: Cutout, Mixup and CutMix are implememted in tf.data and can be found in the linked colab notebooks. I am using TensorFlow 2.x implementation of AugMix by Aakash Nain. His repo can be found here. The fork of this repo contains Weights and Biases integration and some additional command like arguments for more control.
Check out the linked report for:
- The comparative study of these augmentation techniques.
- Augmentation implementations.
- Evaluation of these augmentation techniques against Cifar-10-C dataset.
Alexnet model used