Augraphy: A Data Augmentation Library for Document Images

• URL: http://arxiv.org/abs/2208.14558v2
• Date: Fri, 24 Mar 2023 21:49:21 GMT
• Title: Augraphy: A Data Augmentation Library for Document Images
• Authors: Alexander Groleau, Kok Wei Chee, Stefan Larson, Samay Maini, Jonathan Boarman
• Abstract summary: Augraphy is a Python library for constructing data augmentation pipelines. It provides strategies to produce augmented versions of clean document images that appear to have been altered by standard office operations.
• Score: 59.457999432618614
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper introduces Augraphy, a Python library for constructing data augmentation pipelines which produce distortions commonly seen in real-world document image datasets. Augraphy stands apart from other data augmentation tools by providing many different strategies to produce augmented versions of clean document images that appear as if they have been altered by standard office operations, such as printing, scanning, and faxing through old or dirty machines, degradation of ink over time, and handwritten markings. This paper discusses the Augraphy tool, and shows how it can be used both as a data augmentation tool for producing diverse training data for tasks such as document denoising, and also for generating challenging test data to evaluate model robustness on document image modeling tasks.

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