MapReader | A computer vision pipeline for exploring and analyzing images at scale

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2024-04-26 21:00:03

MapReader was developed in the Living with Machines project to analyze large collections of historical maps but is a generalizable computer vision pipeline which can be applied to any images in a wide variety of domains.

MapReader is a groundbreaking interdisciplinary tool that emerged from a specific set of geospatial historical research questions. It was inspired by methods in biomedical imaging and geographic information science, which were adapted for use by historians, for example in our Journal of Victorian Culture and Geospatial Humanities 2022 SIGSPATIAL workshop papers. The success of the tool subsequently generated interest from plant phenotype researchers working with large image datasets, and so MapReader is an example of cross-pollination between the humanities and the sciences made possible by reproducible data science.

The MapReader pipeline consists of a linear sequence of tasks which, together, can be used to train a computer vision (CV) classifier to recognize visual features within maps and identify patches containing these features across entire map collections.