Process

We had a few difficulties setting up the appropriate dependencies for the program, as we had to make use of Torch7, loadcaffe, and Google protocol buffers in order to process our images. After fixing those errors and getting the dependencies set up appropriately, the process was relatively simple. Some custom settings were utilized atop a GPU-enhanced neural network used for analyzing images.

We did some research and collected sets of iconic photos as well as key paintings from various genres of art in the 20th century. We then paired the photos with paintings from similar time periods, and that we believed would complement the photos, or produce something interesting. We tested the combinations by running them with smaller image sizes, to ensure that we would not waste time processing larger scale images that we ultimately wouldn't use. There were some combinations that simply didn't seem to work together, a few of which are shown below. Finally, we curated our final set of images by picking the most interesting outcomes and had them printed to be displayed.