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I can't really share any images with you as its my customers PII, but the cleanup stage involves a decent amount of artistic interpretation which is why I didn'
by doctoboggan 6y ago
I can't really share any images with you as its my customers PII, but the cleanup stage involves a decent amount of artistic interpretation which is why I didn't think a normal image processing pipeline would work. They often come in smudged, missing lines, incomplete, or with some other error. Its not just a matter of playing with curves, levels, brightness, contrast, etc. I have to trace over them defining what I think the underlying print probably looked like.
- foerbert 6y agoNaively that doesn't seem like a major problem. I'd see it as largely setting up a bunch of constraints and methods to generate candidate solutions - after the initial image processing, obviously.
- notagoodidea 6y agoHow far could you go with some automatic cleaning, something like `maptrace` [0] and some topology rules when you have your vector file to finish with some manual artistic polish? Because, i don't believe that you will achieve easily the "do-it-like-me" result expected from either GAN or VAE or autoencoders. In case of you want to look, the classic examples about style transfer (Photo to Van Gogh style, etc.) seems to be the way to go. Specific to Julia, you can look at Flux.jl or KNet.jl. [0] https://github.com/mzucker/maptrace https://github.com/mzucker/maptrace
- syntaxing 6y agoI think it's a common misconception that OpenCV is Photoshop in coding form. There's a ton of powerful that you can use for what you described but hard to say without seeing the pics. A good example is noise removal in the PSD domain (power spectrum density, not PSD photoshop files). [1] https://docs.opencv.org/master/d2/d0b/tutorial_periodic_noise_removing_filter.html https://docs.opencv.org/master/d2/d0b/tutorial_periodic_nois...