Analyzing 50k fonts using deep neural networks Coding experiment by Erik Bernhardsson uses neural networks to see if it is…
Analyzing 50k fonts using deep neural networks
Coding experiment by Erik Bernhardsson uses neural networks to see if it is possible to generate new fonts based on a dataset of existing ones:
For some reason I decided one night I wanted to get a bunch of fonts. A lot of them. An hour later I had a bunch of scrapy scripts pulling down fonts and a few days later I had more than 50k fonts on my computer.
I then decided to convert it to bitmaps. It turns out this is a bit trickier than it might seem like. You need to crop in such a way that each character of a font is vertically aligned, and scale everything to fit the bitmap. I started with 512 * 512 bitmaps of all character. For every font you find the max y and min y of the bounding box, and the same thing for each individual letter. After some more number juggling I was able to scale all characters down to 64 * 64.
If you take the average of all fonts, here’s what you get: