Saturday 13 December 2008
Roger Alsing has made a fascinating image hack: reproduce an image with randomly-placed translucent polygons: Genetic Programming: Evolution of Mona Lisa. At each step, a random polygon is placed on the image, and a simple image comparison function determines whether a new proposed polygon makes it look more or less like the goal image. It’s not fast, but the results are kind of startling. A photo of me and a friend:
And a polygonal reproduction with 108 polygons:
This reminds me a little of the CSS Homer, recreating an image by amassing unlikely components in just the right way. BTW: the comments on Roger’s post contain a number of AI nerds debating whether this is truly genetic programming, and if so what kind, or if it is simply a hill-climbing algorithm. In any case, it’s very cool.
Comments
Any chance you could make your code available? (I'm assuming you wrote a little Python script for this...)
@André: I don't know what I can do to make it clearer: I didn't write this at all, Roger Alsing did. There's a link to his blog post in the first sentence..
cool find
ps. i think you meant 'genetic' programming, instead of generic
oops, yes "genetic".
Oops, sorry. I had seen the post by Roger Alsing some time last week and I assumed that you had written a program reproducing this idea. My mistake - sorry :-(
It would be very interesting to produce a variation of this technique that works with randomly-placed translucent font characters, mixing Roger Alsing's idea with that of Román Cortés' Homer technique.
Anybody have enough time on their hands to try it?
How do non-human images look? People see faces everywhere so not very close is often close enough. For instance if I only saw the final image I'd guess you were sitting in a diner in front of a mirror. Or maybe on the Red Line at a station.
I'm surprised nobody tried yet to reproduce that in Python. I'm looking right now at the source code of the project. The core features seem to be simple. There is a lot of GUI stuff and config files that could be avoided.
Add a comment: