mlsanityData to 7 Oct 2026

Augmentor: An Image Augmentation Library for Machine Learning

arXiv 1708.04680 ↗First posted 11 Aug 2017cs.CV cs.LG stat.MLcited by 14

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Abstract (arXiv)

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.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Aug 2017.

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Citing papers per year: 2021: 5; 2022: 3; 2023: 2; 2024: 1; 2025: 1; 2026: 2.

14 papers.

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