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Launch HN: Rubbrband (YC W23) – Deformity detection for AI-generated images
Hey HN! We’re Jeremy, Abhi and Darren from Rubbrband (https://www.rubbrband.com/ https://www.rubbrband.com/). Rubbrband is software that evaluates the quality of images generated by Stable Diffusion (or Midjourney, DALL-e, etc…).
We actually stumbled into this idea while working on solving a different problem. While helping a few companies use Stable Diffusion in production, we found that these companies needed to use QA analysts to manually evaluate their images to make sure they were high quality once in prod. This process often took days just to go through thousands of images, so companies that have a text-to-image product with PMF couldn’t guarantee that their images were of high quality.
From our initial set of customers, we found that evaluating the quality of their outputs at scale was an even larger problem than just using the model itself. So we pivoted our company into working on solving this problem using our skills from CV research. All three of us did computer vision research at UC Berkeley, and Abhi worked with John Canny, who invented many CV techniques like the Canny Edge Detector.
We built a product that automates this process using computer vision. We’ve trained in-house several computer vision models that grade images based on different criteria.
These include: - Detecting human deformities, such as a person with 7 fingers on a hand (image generation models generate deformed hands over 80% of the time when generating a photo of a person! This includes the state of the art: Midjourney, SDXL, Runway, etc…); - A score that rates how well the image aligns with the prompt(we do this using our own finetuned Visual Question Answer model); - A composition score (how well composed the image is according to photography “rules”)
Using Rubbrband is pretty simple. You can send an image to us to process via our API or our web app, and you’ll get scores for each of those criteria back on your dashboard in less than 10 seconds. Here is a quick Loom demo: https://www.loom.com/share/961830347b3643dcbb92dfe80f8ca1f0?sid=faf1d9fb-5023-4dc8-96fc-5b3806ef3c6b https://www.loom.com/share/961830347b3643dcbb92dfe80f8ca1f0?....
You can filter your images based on certain criteria from the dashboard. For instance, if you want to see all images with deformed eyes, you can click the “deformed eyes” filter at the top of the screen to see all of those images.
We store images generated by your image generation model. We’re like a logging tool for images, with evaluations on top. We currently charge $0.01 per image, with your first 1000 images free.
We’re super excited to launch this to Hacker News. We’d love to hear what you think. Thanks in advance!
- bboylen 3y agoThis seems pretty useful for companies generating images at scale. Are you at all worried that generative models will get so good that you don't need to check for deformities?
- brucethemoose2 3y agoI can't see this ever happening. Every new genAI model and finetune I've seen brings fun new classes of distortion.
- zirgs 3y agoWe'll probably need higher resolution models. SD 1.5 is 512x512 and it usually outputs deformed faces in full body shots simply because its resolution is too small. SD XL is 1024x1024 and that no longer happens there. We'll see how outputs from 2048 and 4096 models are going to look like. But those models will need lots of VRAM.
- zirgs 3y agoIs there any model that doesn't output deformed hands?
- Utkarsh_Mood 3y agoiirc midjourney has figured it out although its closed source if you were wondering.
- zirgs 3y agoChecked midjourney discord - it still generates weird hands from time to time, but it's much better than before.
- jrmylee 3y agoIt's something we think about for sure We think that image-gen models are lagging behind LLMs by about a year, so the problems that these models will have should look quite different in the future. It'll require us to be adaptable and also to take chances on solving problems that aren't huge issues just yet, but are likely to be once models improve.