Generate Image Augmentations with Roboflow

Image augmentation is a technique used to improve model performance by creating new images from existing ones in a dataset, enabling models to better identify classes underrepresented in the training set. Roboflow offers a platform that simplifies this process, providing a visual interface to apply up to 23 different augmentations, such as brightness adjustments, to a dataset. Users can upload annotated or unannotated data, create new versions with selected augmentations, and configure these settings to reflect specific use cases. The augmentations are applied during dataset generation, which speeds up training time and reduces costs, as augmented images are created independently of the training process. This method allows for experimentation with various augmentations to optimize model performance, with the flexibility to revert changes if needed. Once created, augmented datasets can be used for training models directly on Roboflow or exported for custom training processes.