I would like to write a program that takes a number of elements as input (some images and some strings) and outputs a design (the program places the images and strings on a canvas, but also styles the strings).

Can someone point me in the right direction of a possible solution to this problem? I've looked for machine learning algorithms for design but have not found a single one to give me any tips on how to build one of these.

  • $\begingroup$ You must decide which is your target, quality factor: minimal gaps (total canvas size)? esthetics's ? $\endgroup$ – pasaba por aqui May 15 '18 at 8:11
  • $\begingroup$ Esthetics's, or at least something that looks human made. But I do not know how to define it. $\endgroup$ – Natanael May 15 '18 at 8:22
  • $\begingroup$ How would I define the quality measure? $\endgroup$ – Natanael May 16 '18 at 7:19
  • $\begingroup$ Why is my question down voted? Is there something wrong with it? $\endgroup$ – Natanael May 16 '18 at 7:23
  • $\begingroup$ Down voted due to too broad and low quality: you can not ask "I want made that, say me how". No pre-work is show. $\endgroup$ – pasaba por aqui May 16 '18 at 7:26

If you have images contain styled strings and images contain printed strings, you could use Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks to learn to translate between both distributions where paired training data does not exist (not styled string image, styled string image).

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