Polygen uses a genetic algorithm to approximate an image with a small number of polygons.
You can generate a fairly good approximation with surprisingly few polygons. Here’s a sample that has only 50 polygons (~380K generations):
This one is 100 polygons:
A more challenging image- 500 polygons & 680,850 generations:
The algorithm is pretty simple:
Create an initial string of candidate "DNA" consisting of a set of polygons (a color and a set of points) via random number generation.
Render the DNA to an image (the "phenotype"). Compute its fitness by comparing to the reference image.
Apply random mutations to the candidate (change color, move polygon points, juggle the z-order) to create a population of offspring.
Evaluate the offspring, and if their fitness is better, replace the parent.
Repeat for N generations.
$ go get github.com/armhold/polygen/...
$ cd $GOPATH/src/github.com/armhold/polygen
polygen -source images/mona_lisa.jpg -poly 50
- Let it run until you are happy with the output (in
output.png), or until you notice that there is not much change between generations.
Polygen includes a built-in web server, so you can watch the image evolve in more or less realtime. Just point your browser to http://localhost:8080 .
This code is my own, but credit goes to Roger Johansson for the original idea, which he documented here .
The file "mona_lisa.jpg" contains a low-resolution portion of the painting Mona Lisa , by Leonardo da Vinci. It is in the Public Domain.
The file "starry.jpg" contains a low-resolution copy of the painting The Stary Night by Vincent van Gogh. It is in the Public Domain.
The file "Revolver.jpg" contains a low-resolution copy of the cover art for the album Revolver by the artist The Beatles. The cover art copyright is believed to belong to the label, Parlophone/EMI, or the graphic artist(s), Klaus Voormann. It is included under Fair Use .
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