
The Four Painters: A Video Work Created with Deep Learning - noradaiko
http://odoruinu.net/blog/2015/12/23/the-four-painters-a-video-work-created-with-deep-learning/
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psycr
I produced something similar to this shortly after the release of
[https://github.com/karpathy/char-rnn](https://github.com/karpathy/char-rnn):

[http://i.imgur.com/rb0GJvQ.gifv](http://i.imgur.com/rb0GJvQ.gifv)

Basically, you create a video, dump the video's frames with ffmpeg, run each
frame through the RNN, and stitch them back together. It took me several hours
to produce just ten seconds of video. Unfortunately, unless you have a Titan X
GPU the max size of each image is quite small (certainly less than 1080p),
which may be why the frames in this video are split into four quadrants.

~~~
binarymax
Nice result! About 5 years ago, I did the same technique of frame
dump->process->join but with a custom algorithm instead of a NN for the
process stage. A more manual effort to tweak the filter, but it was fun and
came out nice.

I got a new GPU recently and have been doing mostly text RNN these days, but
it's fun to look back on this occasionally:

[http://binarymax.com/reality_remix.html](http://binarymax.com/reality_remix.html)

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pavlov
Something about the current deep learning hype reminds me of fractals and
cellular automata back in the day.

They're all very important and useful scientific advances that can be used to
produce visuals that seem to automatically create something strikingly
natural. This seems to make people kind of overreach about exactly how much of
nature can be represented by this one method alone.

The world is probably not a fractal, the universe is probably not a cellular
automaton, and the mind is probably not a "deep learning system" either (of
the specific type currently implied by the term).

~~~
cscurmudgeon
Deep learning shines when there is a lot of data and computation power. A lot
of important problems don't have that much data and there are much better
algorithms right now for those problems [1]. Deep learning is definitely
faddish though it has its uses.

[1]
[http://www.sciencemag.org/content/350/6266/1332.full.pdf](http://www.sciencemag.org/content/350/6266/1332.full.pdf)

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OvidStavrica
The trouble with neural networks is that they're just good enough to keep us
from continuing to question our assumptions about human intelligence.

A thousand years ago, even Ptolemy's geocentric model was good enough. After
all, it offered an effective means for simulating and predicting planet
movement and solar eclipses. But it was complex. It took men of "great
learning" to understand the solar system according to Ptolemy's model
--something that most current grade schoolers understand intuitively.

In all likelihood, concepts like string theory and neural networks are
comparable traps for us today. This is not a pleasant thought. So we're not
motivated to search for better alternatives until the current model evidences
an insurmountable flaw.

I'm not saying that string theory or the neural network approach is wrong.
Obviously it's not. Just remember that Ptolemy's model wasn't wrong either, at
least with regard to the moon.

~~~
dragonwriter
> Just remember that Ptolemy's model wasn't wrong either, at least with regard
> to the moon.

Yes, it was, even with regard to the moon. Though, since the Earth-Moon
barycenter is within the Earth, it may have managed to be _tolerably wrong_
with regard to the Earth-Moon system. But, still wrong.

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SCAQTony
I am making jellyfish, lily pads, whales and flowers via Fractal Flame
software. All expressionistic and/or impressionistic. [samples:
[https://twitter.com/SCAQTony/media](https://twitter.com/SCAQTony/media) ]

However, there is something about digital that degrades the art by allowing it
to be massed produced. One print is equal to another and therefore it almost
becomes trash. Example: Imagine an original Mickey Mouse drawing versus a
rendering of Woody and Buzz from Toy Story?

~~~
themodelplumber
As a fractal artist myself as well, I've been ranting about this to myself
lately. I've been thinking that the problem is inherent to algorithmic art in
particular; I guess I can actually see some worth in renderings of e.g. Pixar
characters, but maybe that's because I have kids who appreciate them, or
because I've browsed Pixar art books.

What I've noticed is that in order to make fractal art that typical art
gallery-types find worth their time, you have to take on a kind of Simon
Cowell role and inject your own intuition or library of culturally-attuned
sensation memories into the creation phase, turning it into more of an
audition phase. "This one just sucks...this one is OK...this one needs a
little tweak and it'd look great, kind of like a rainy summer day." In order
to make your product useful to other humans, you have to typologize, sometimes
really brutally, and especially moreso since your computer can just keep
pumping this stuff out.

If you go the other way and shun the story, shun the critique, and say
"typology is for the closed-minded," you can end up in scientism, completely
free of such hyperbolic typology but lacking a compelling presentation of a
set of convergences. Lacking a story, lacking any depth with which humans
really identify.

No matter how much machinery goes into computing scientific results, the
results are still somewhere along a normal curve, and unfortunately that's not
super useful to humans. But psychologically we find extreme typologies very
useful. As a group, we'd rather say "ooh, a sports car" or "oh wow, dripping
ice cream!" than "oh, it's a blob that could be any number of things."

At its most vain, the typology-free approach can end up as a sort of
pornography, an obsession with process to the exclusion of context, and to the
deep satisfaction of barely anybody.

That's why I really get frustrated with fractal art or generative art. After a
point I have to put on my designer hat, and I might as well have painted the
thing from scratch anyway. Or I might as well have used the software more like
an artist would use Alchemy, as a sort of imagination cue.

[https://www.youtube.com/watch?v=zYYSxZZzgjc](https://www.youtube.com/watch?v=zYYSxZZzgjc)

~~~
SCAQTony
I am going straight to the public - I am also going to diversify (Catwoman
panting in the works). Going to rent a gallery, have a party, get photos of
people staring at a few giant Chromaluxe prints on aluminum and then set up a
site. The art will feature anchoring pricing: 60'x80" limited edition
Chromaluxe prints for $4,000 or a 24x36" lithograph for $35. Hoping I sell
10-posters a month of each. I wish you well.

~~~
themodelplumber
Hey, I really appreciate you sharing that. Those seem like great ideas to me.
Best of luck to you as you get that into motion!

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jameshart
Would be more interesting to apply this photo transformation given, as an
input, not only the painting the artist produced but also a photograph of the
thing the artist was trying to represent. Otherwise all you are doing is
recreating the artist's visual tools, not the way the artist translates what
they see into the visual palette.

But then, if you tell the algorithm that _The Scream_ is just a painting of a
man on a bridge... you're not going to get a very good result.

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soperj
Does anyone have any idea the style of painting that he was actually doing?
(In the first one)

~~~
sp332
It looks like colored paper covered with black pigment, then then black was
scraped away to make the lines.

~~~
soperj
thanks.

