When creating computer vision models, data augmentation can improve model performance with an existing image dataset. Image augmentation increases the size and variability of a dataset, thereby improving model generalizability.
Machine learning algorithms are exceptionally data-hungry, requiring thousands – if not millions – of examples to make informed decisions. Providing high quality training data for our algorithms to learn is an expensive
The appeals of synthetic data are alluring: you can rapidly generate a vast amount of diverse, perfectly labeled images for very little cost and without ever leaving the comfort of your office. The good news is: it's easy to try! And we're about to show you how.