A collection of faces for a workshop in http://jentery.github.io/507/ at UVic.
A fork of Terence Eden's Tate-Hack: https://github.com/edent/Tate-Hack. Thanks, Terence! And thanks, too, Philipp Wagner.
This script uses Python and runs images through OpenCV's face recognition.
If a face is detected in the Beinecke's "Picturing Literary Modernism" exhibit (http://beinecke.library.yale.edu/collections/highlights/picturing-literary-modernism), then the script crops the face and saves it as a separate image. This will detect multiple faces per image. The images are saved in the detected subdirectory of modfaces. The URLs for the "Picturing Literary Modernism" exhibit are stored in all.txt, which the Python script calls.
downloadface.py will crop the faces from ~30 images located at http://beinecke.library.yale.edu/collections/highlights/picturing-literary-modernism. (To add/remove URLs, simply edit all.txt.)
Run python downloadface.py face.xml to initiate the cropping.
eigensave.py will generate an Eigenface model and save it to disk.
recognise.py will compare a photograph to the model and print out the nearest match.
Full write up, by Terence Eden, at http://shkspr.mobi/blog/2014/06/which-painting-do-you-look-like-comparing-faces-using-python-and-opencv/.