This paper argues that deep learning for computer vision can tackle both challenges of theater photography – the medium’s precarious status and archive size –, enabling distant viewing approaches from Digital Literary Studies and Art History applied to Theater Studies.

This data paper examines the challenges and considerations involved in making pixel-level annotations to fine-tune a computer vision / object detection algorithm for recognising alchemical laboratory apparatus in early modern printed manuals.