The Distant Viewing Toolkit (DVT)

The Distant TV Toolkit is a Python package designed to facilitate the computational analysis of visual culture. It contains low-level architecture for applying state-of-the-art computer vision algorithms to still and moving images. The higher-level functionality of the toolkit allows users to quickly extract semantic metadata from digitized collections. Extracted information can be visualized for search and discovery or aggregated and analyzed to find patterns across a corpus.

More information about the toolkit and project is available on the following pages:

• Search and discovery interface example: DVT Video Visualization
• Example analysis using aggregated metadata: “Visual Style in Two Network Era Sitcoms”
• Theory of the project: “Distant Viewing: Analyzing Large Visual Corpora.”
• Project homepage: The Distant Viewing Lab
• Source code
• PyPI repository

See the links to the left-hand side for instructions to install and run the toolkit. If you have any trouble using the toolkit, please open a GitHub issue. If you have further questions or are interested in collaborating, please contact us at tarnold2@richmond.edu and ltilton@richmond.edu.

The Distant Viewing Toolkit is supported trough a Digital Humanities Advancement grant from the National Endowment for the Humanities.