Show HN: Huemint – Machine learning for color design
huemint.com
huemint.com
You can guide the ML model by locking one or more colors, then clicking generate again. (click the circular swatch on top to lock a color)
edit: I forgot where I saw the list for 2021 but it included stuff like this https://twitter.com/ML4CDworkshop/status/1467661464400183298...
It's interesting to think what would happen if a tool / technique like this one became super popular. Would we see more variation, as more people could choose schemes that look good? Or would we see convergence as there are no longer people actively making decisions (similar to what may be happening in the stock market due to the rise of index funds: [1])?
[1] https://www.theatlantic.com/ideas/archive/2021/04/the-autopi...
> You might ask at this point, if we can enumerate all possible solutions like this, why not just generate colors from first principles - why is machine learning even needed? The answer is basically that translation and rotation in colorspace might be contrast-invariant, but they're not preference invariant. Humans have subjective preferences for certain color combinations over others, so to generate pleasing color combinations we need to quantify which areas in the configuration space people generally prefer.
> To quantify which color combinations graphic designers prefer, I started by scraping design thumbnails from the web.
> At this point we have a decent sized dataset to train our ML model. The overall approach is to treat the problem as conditional image generation - the color contrast graph is the input and the corresponding color palette is the output.
My one suggestion is since you have Bootstrap support, maybe add TailwindCSS utility support as well
Huge kudos!
I'd imagine a series of left/right comparisons, like a visit to an eye doctor, where the machine learning is rewarded for its ability to predict my preferences. Eventually (a time commitment for me) it will be able to build from scratch color designs that I love.
This is like an early application of machine learning: What are the odds of victory for this backgammon position? Here, instead, we've estimating a preference function on color triples. Is RGB even the right domain, or do we want to work in some frequency transform, to capture the equivalent to musical chords. This is an empirical question, that can only be answered by trying to estimate this preference function, and noticing ripples better resolved by a different parametrization.
This would be easy, compared to the Riemannian geometry used in medical imaging. There's more money there.
For commercial use one cares what others think. There's the speciation question: You won't synthesize deep jazz tracks and deep blues tracks without separating the advice into species. Identifying clusters in data is something statisticians have worried about since the dawn of statistics.
I see a few requests for practical features here, but I have one incredibly silly request: how plausible would it be to restrict the colors to a set list of RGB values, so one could, say, generate color palettes for physical mediums based on medium color -> RGB conversion lists, such as painting, cross stitch thread[0], or yarn[1]?
Also would be nice to "apply" the colors from an upload image to the various scenarios. I.e. grab X colors from image and generate would cycle through various forms of those (possible adding extra complementary colors as needed).
But this project creates some pretty good ones on the fly. I'd be interested in knowing what features of colors it's uncovered, that it uses to generate new swatches.
I need to play with it some more, and understand how to use it, but good job!
Is there anything that checks for contrast/accessibility?
(Also, I couldn't find any credit or name on the site?)
One project I wish someone would build is an ML-powered algorithm for perceptually even saturation, drawing on crowdsourced data to help pick colors that most people would perceive as being equally colorful
I clicked around and got the same color palettes on multiple occasions. Is that because I have to give the system some input for it to work?
Your websites are fantastic, by the way. Google and/or NASA should contact you. ;)
When I use the tool myself, I usually start with the transformer model to lock the first few colors, then switch to the diffusion model if I see a repeat. When all colors are locked except one or two, the "random" mode starts working if you still need more variations.
If able, would it be possible to add Material-UI as a section similar to the Bootstrap section?
(I almost didn’t click through, got distracted by touch-rotating it on my iPad)
Well done!
( the api caps out at 12 colors )
Is there a way to run this locally?
Few days back I was trying to decide a colr theme which woul work for both light and dark mode. Would this be able to solve that ?
there's also a dark mode preset in the (gear icon) menu.
I concede this is not totally obvious just from the UX, maybe it needs a tutorial or something...