id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
andromedayelton-com-2311		andromeda yelton			.html	text/html	8077	489	75	(Neural net: "I have 6% confidence this is Stevie Wonder!" How nice for you.) Clearly I'm going to need to build my own corpus of people, which I have a plan for (i.e. I spent some quality time thinking about numpy) but haven't yet implemented. This meant that my new dpla_cats script only had to import ImageUtility rather than * (from X import * is, of course, deeply unnerving), and that utility could pingpong around knowing how to do the things it knew how to do, whenever I needed to interact with image-y functions (like creating a generated image or saving outputs) rather than neural-net-ish stuff. I wanted to be able to play with it more and gain some insights, so I adapted the Coursera notebook code to something that works on localhost (more on that in a later post), found myself a nice historical cat image via DPLA, and started mashing it up with all manner of images of varying styles culled from DPLA's list of primary source sets.	./cache/andromedayelton-com-2311.html	./txt/andromedayelton-com-2311.txt