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Then I use this metadata to present icons of (roughly) the same color. It’s kinda neat to be able to browse a wall of icons that are all the same color.
The thing is: I know there are a lot of icons I’ve missed tagging over the years. But I have no idea how many, and figuring that out seems like a really arduous task. How do I go through 2,000+ icons and find all the ones that look predominantly “orange” but haven’t been tagged as such yet?
Seems like a good task to throw at an LLM. But I don’t want to just say, “Go tag everything that’s missing” and blindly trust the output. I need to be able to make a decisions as to whether I think a particular color is “orange” or not.
What I need is a tool for the job. I’m a very visual thinker, so to continue curating these color categorizations, I need some way for the computer to do its thing really, really fast, and then pull me into the loop to visually make decisions.
Here’s how I am thinking about about accomplishing this task:
That seems like it would be a good tool to put me in control of visual decision making around color categorization. So I tell the LLM to run with it.
We chat back and forth. I think, “You probably need to run all the icons through some model to make the correlation?” But it’s like, “Nah bro, just make a ‘hue histogram’.” It tells me how. For a color like “orange”, I can:
[process] each PNG, skip transparent pixels, skip low-saturation gray, convert the rest to HSV, and score how much of the remaining mass sits in the orange hue band (roughly 15–45°). Rank icons that don’t already have colorId:
orange.
Ok, sure. That sounds reasonable.
[This] scores each icon PNG by share of opaque pixels per color bucket, then writes a standalone HTML page: tagged vs maybe-missing, per color.
Let’s just make it, and then I’ll decide whether it’s good enough.
After a few iterations, the computer going “brr…”, and me saying “explain that like I’m dumb”, I have a really effective little tool!
The little threshold slider is a nice touch. It lets me fiddle around with the fidelity of the matches. In some cases, sliding it down reveals more icons I would’ve otherwise missed. In other cases, I’m like “What are you thinking? I don’t see that as ‘yellow’ at all!”
Supper effective little tool. I go through each color, select the ones I think are missing, paste the IDs back into the LLM, and then have it update each icon's metadata.
Boom, done! That all would’ve taken so long before. I would’ve never done it.
Takeaways:
.html file that I can locate on my hard drive and open directly as a file:// URL. No bundling. No transpilation. None of that. I don’t even need a web server! Keeping things very basic on this project is paying off: I had really elemental building blocks that didn’t require additional third-party tooling. Just HTML, CSS, a little in-page JS, and images on a server!此内容由惯性聚合(RSS阅读器)自动聚合整理,仅供阅读参考。 原文来自 — 版权归原作者所有。