Callico: a Versatile Open-Source Document Image Annotation Platform

Christopher Kermorvant, Eva Bardou, Manon Blanco, Bastien Abadie
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Abstract

This paper presents Callico, a web-based open source platform designed to simplify the annotation process in document recognition projects. The move towards data-centric AI in machine learning and deep learning underscores the importance of high-quality data, and the need for specialised tools that increase the efficiency and effectiveness of generating such data. For document image annotation, Callico offers dual-display annotation for digitised documents, enabling simultaneous visualisation and annotation of scanned images and text. This capability is critical for OCR and HTR model training, document layout analysis, named entity recognition, form-based key value annotation or hierarchical structure annotation with element grouping. The platform supports collaborative annotation with versatile features backed by a commitment to open source development, high-quality code standards and easy deployment via Docker. Illustrative use cases - including the transcription of the Belfort municipal registers, the indexing of French World War II prisoners for the ICRC, and the extraction of personal information from the Socface project's census lists - demonstrate Callico's applicability and utility.
Callico:多功能开源文档图像注释平台
本文介绍的 Callico 是一个基于网络的开源平台,旨在简化文档识别项目中的注释过程。在机器学习和深度学习领域,人工智能正朝着以数据为中心的方向发展,这凸显了高质量数据的重要性,同时也说明需要专门的工具来提高生成此类数据的效率和有效性。在文档图像注释方面,Callico 为数字化文档提供了双显示注释功能,可同时对扫描图像和文本进行可视化和注释。这一功能对于OCR和HTR模型训练、文档布局分析、命名实体识别、基于表单的关键值注释或带有元素分组的层次结构注释至关重要。该平台支持协作注释,具有多功能,并致力于开源开发、高质量代码标准和通过 Docker 轻松部署。示例用例包括贝尔福市政登记簿的转录、为红十字国际委员会编制法国二战战俘索引,以及从 Socface 项目的人口普查名单中提取个人信息,这些都证明了 Callico 的适用性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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