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So if I understood well, this GIF shows you - human being - exploring possibilities / limitations of your method, hand tweaking it for one particular image?

http://nucl.ai/files/2016/03/MonetPainting.gif

That is, the final image, the one that looks the best, is the result of you doing tweaks to doodles to get something that neural net can then fill-in convincingly?

Or are these a different runs of the same method based on the same inputs, that have some natural variability, and you selected the one that looked the best?

Or are these progression steps in one run of the automated algorithm?

Language in the blog post is kinda ambiguous, not sure which steps were done by algorithm and which by a human being.



Exactly, the doodling is done by humans and the machine paints the HD images based on Renoir's original. I've edited the blog post to clarify.


That part was clear :)

What still isn't clear to me is how exactly that "workflow" demo (and consequently the "money-shot" final generated images) happened.

There is a progression of generated images with increasing quality. Who did which steps in those iterations?

Blog post uses ambiguous language: "N-th image tries / removes / fixes", etc.

It's not clear though if it was:

1) algorithm steps (keep computing more till generated image looks good), or

2) human being tweaking inputs to fixed algorithm (keep painting new input/output doodles till generated image looks good), or

3) human being tweaking algorithm itself (change code till generated image looks good).


The algorithm does the same thing every time (it's triggered on request), only the input is changed by the human modifying the doodle—as shown in the video.

The output gets better because through iteration the glitches are removed incrementally, and it converges on a final painting that looks good!




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