What about running lots of iterations? Turns out, it makes the features much clearer:
For scenes that don't have a lot of colour, here's what it comes up with:
You can see that the approximately vertical line (where the tree line is) is retained across the various images.
What are all these Filters?
What about variability?
Turns out, there's a randomization element in the algorithm, so running the same image with the
same parameters yields many different results.
The interesting thing is to note where the images are the same and where they differ:
For some reason, the algorithm doesn't like my train tracks.
Giving it a 640x480 image costs a lot more in CPU, and yields some nicer images (this is the Prague Rails picture from above):
Note that with this particular filter, setting the iter_n to 100 didn't cause any visible changes
in the last set of iterations — I suppose the network had already decided on what it was going to show,
and that was that.
Memory was around 1GB for python.
Giving it a 1280x960 image costs even more in CPU, and yields even nicer images:
Doing camera resolution (the image was taken with a 2272x1704 (4MPixel) camera), produces awesome images (and takes 8GB of memory):
For someone like me who doesn't have a whole bunch of artistic talent, my question is, “can deepdream help
me generate some art using guided drawings?”