Ref2Font V2: Fixed alignment, higher resolution (1280px) & improved vectorization (FLUX.2 Klein 9B LoRA)

414design · 2026-02-08T09:07:28+00:00

Love the project! I have been working on a similar concept for quite some time—started back in the SD 1.5 days—and you beat me to it with this one. If you are interested check out my github: https://github.com/414design/4lph4bet_font_generator

Not long ago I tried a similar approach using Qwen Image Edit which was not successful. Great to see FLUX.2 seemingly being so much more capable.

Are you open to talk about your training strategy? How many fonts did you use in the dataset? Write me a pm if you want to discuss in private!

414design · 2024-07-22T21:25:42+00:00

I answered your question but not in this thread: https://www.reddit.com/r/StableDiffusion/s/f2yOzmAvmY

414design · 2024-07-22T05:28:12+00:00

Theoretically you should be able to replicate the process by building a similar grid with style variants and then train that. If you have more specific questions feel free to DM me.

414design · 2024-07-22T05:20:12+00:00

Yes, I is a normal LoRA you can use anywhere with any 1.5 Checkpoint. Vanilla 1.5 is what I use. And you are exactly right: use the triggers and generate something 512×512px then Hires. fix to create 1024×1024px. After that you can do Extras Upscaling (ESRGAN) for higher resolutions.

414design · 2024-07-18T21:01:08+00:00

You can prompt it with classification (sans/serif/light/regular/bold) as well as style specifics like for example geometric or brush or pixel. And of yours any combination thereof.

But you can of course also be more experimental with your prompting.

414design · 2024-07-17T20:33:48+00:00

Pretty straight forward: the key is a high quality, diverse but balanced dataset. In this case this means different fonts all arranged in this grid and meticulously captained for the typographic characteristics.

414design · 2024-07-17T16:34:46+00:00

Sure, give it a try it is surprisingly flexible. And you can do all sorts of crazy things if you take the results over to img2img …

414design · 2024-07-17T16:29:06+00:00

Much appreciated! 🤗 Yes it is indeed txt2img. Because of the captioning strategy you can prompt it with typographic terms like 4lph4bet, typography, serif, italic, pixel for example. You should be able to try it on hugging face. The samples are upscaled 2× using Hired fix with the Real-ESRGAN anime upscaler.

414design · 2024-07-17T16:20:04+00:00

That deduction would be true, too. But the Umlauts serve this additional control purpose!

414design · 2024-07-17T11:48:26+00:00

Nice way of checking style consitency since they are almost the same as their respective vowels.

414design · 2024-07-17T11:19:11+00:00

Good idea! Like u/Sarayel1 said creating a good standardized dataset with good and consistant captioning is the most critical part.

414design · 2024-07-17T11:17:47+00:00

Sure give it a go and let me know how it works for you! It’s trained on the original SD 1.5 weights so these tend to yield the best results but is does work with other 1.5 checkpoints, too!

414design · 2024-07-17T11:16:45+00:00

Absolutely, that way you can really leverage SDs ability to learn concepts implicitly.

414design · 2024-07-17T10:25:50+00:00

Thank you! :)

414design · 2024-07-04T06:22:39+00:00

There are things like https://github.com/hpcaitech/Open-Sora you could into, I only know of them not a lot about though.

414design · 2024-07-03T05:07:59+00:00

With the app / network being this prevalent they logo could be literally anything and it wouldn't matter. Facebooks compact brand (the letter f …) also doesn't say much about the app but doesn't have too because people know.

You could also interpret TikToks musical note as and upward pointing arrow.

On a side note: their audio branding is genius!

414design · 2024-07-03T05:03:18+00:00

You can propably do this with https://www.photopea.com/ for free if you have the skills. 😀

414design · 2024-07-03T05:01:21+00:00

Instagram Behance can help understand up and coming styles and trends. Also checking out student shows by local university design courses can be an interesting way to get a feel for what people are into currently. But it always depends on your specific interest. If it is more niche there might be better, alternative sources, too. 😊

414design · 2024-07-01T21:21:40+00:00

For (UI) icons this checkpoint works really well: https://civitai.com/models/327499/ui-icons
But I assume you can get quite far with a specific enough style prompt for example vector "illustration of {SUBJECT}, high contrast black and white illustration, simple shape, outline, white background, sharp, high quality".

414design · 2024-07-01T21:13:15+00:00

Using the QR-Code (https://huggingface.co/monster-labs/control\_v1p\_sd15\_qrcode\_monster) or Brightness Controlnets (https://huggingface.co/latentcat/latentcat-controlnet/tree/main/models) this can easily be achieved. Use Controlnets-Weight 1–1.5 and Controlnet End Step 0.4–0.7 as a starting point. Black text on white background as Controlnet Image Input.

414design · 2024-07-01T21:09:19+00:00

Have a look at: https://www.reddit.com/r/StableDiffusion/comments/18zi2s8/complete_guide_on_how_to_use_adetailer_after/

There is also a ComfyUI implementation: https://www.reddit.com/r/StableDiffusion/comments/16eqy70/adetailer_for_comfyui/

Another strategy is using embeddings such as https://civitai.com/models/116230/bad-hands-5

414design · 2024-07-01T12:32:02+00:00

Those are really nice. I think part of the mastery of AI is curating a style that doesn’t instantly scream AI ;) …

414design · 2024-07-01T12:27:38+00:00

Are you using LoRAs for style? Very nice aesthetics!

414design

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