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arXiv · 1708.04680

Augmentor: An Image Augmentation Library for Machine Learning

Marcus D. Bloice·Christof Stocker·Andreas Holzinger
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Abstract

The generation of artificial data based on existing observations, known as data augmentation, is a technique used in machine learning to improve model accuracy, generalisation, and to control overfitting. Augmentor is a software package, available in both Python and Julia versions, that provides a high level API for the expansion of image data using a stochastic, pipeline-based approach which effectively allows for images to be sampled from a distribution of augmented images at runtime. Augmentor provides methods for most standard augmentation practices as well as several advanced features such as label-preserving, randomised elastic distortions, and provides many helper functions for typical augmentation tasks used in machine learning.

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Marcus D. Bloice, Christof Stocker, Andreas Holzinger. 2017-08-11. Augmentor: An Image Augmentation Library for Machine Learning. https://arxiv.org/abs/1708.04680

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