Christopher Kermorvant, Eva Bardou, Manon Blanco, Bastien Abadie
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Callico: a Versatile Open-Source Document Image Annotation Platform
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.