Image Analysis at Scale in the Undergraduate Humanities Classroom

Today Kristen Mapes and I presented at the Chicago Colloquium on DH and Computer Science about some of our work we’ve done to support undergraduates learning about distant viewing techniques. Our work builds upon the classroom work that we have been doing with collaborators such as David Bering-Porter and Cody Mejeur to think about how distant viewing techniques may provide additional options for looking at visual content in DH and Cultural Studies work.

As part of the presentation, we discussed some of the simple shell scripts we’ve written to support our work and make it easier/less time intensive to do some of the tasks. For those who may be interested doing similar work we have provided several scripts on our GitLab instance. We have also made the slides from the presentation available.

Abstract for the talk is below:

We are interested in sharing approaches and examples of teaching computational image analysis to a non-computer science student population in a humanities context. Digital humanities curricula usually include methodological introductions to such topics as text mining and analysis, mapping, network analysis, metadata, preservation, and archival curation. Since 2015, we have incorporated large scale image analysis into introductory digital humanities courses at the undergraduate level.

Incorporating image analysis into the suite of digital humanities methods adds to the possibilities of DH: it makes digitized collections and born digital image and video content available for analysis at scale beyond those currently available for study with text analysis methods. By expanding this potential corpus of material available for study, we also open up digital humanities to more topics that resonate with our students. Teaching digital humanities to undergraduates is a process of eliciting excitement about an expanded methodological toolkit, and including large scale image analysis is a striking way to get students engaged in thinking about corpora, metadata, method, and presentation.

In the Introduction to DH class at the undergraduate level, we have demonstrated the use of ImagePlot ( and have given students the opportunity to use the software as well. This approach has led several students to pursue a final project using this method (for example: This presentation will share how we have used a corpus of Harlem Renaissance art images to tie the software instruction into the content of the course and how we are now extending computational image analysis instruction beyond ImagePlot to incorporate Distant Viewing ( tools into the classroom in early Fall 2018. This extension of image analysis instruction to algorithmic face detection and classification opens up new possibilities for analyzing material in the classroom and engaging in critical conversations about how such programs work in the corpora we create as well as those used in the corporate world.