> Use cases where the threat model fits: You are preserving art or historical record against false-positive "AI-generated" labels.
Sorry, how does using AI to generate images have anything to do with this? Image generators cannot insert watermarks into things they did not generate, and it seems highly unlikely that you will get a false-positive watermark on human-generated art, especially if, as the readme says, these watermarks have high enough fidelity to trace to a specific session id. Plus the modifications to the image needed to erase watermarks would necessarily change the thing being "preserved."
[edit]: the more I read the more I'm convinced, the claimed use cases in the README are bullshit and the real reason is to provide a tool that helps people bypass "AI-generated" labels on social media for AI slop.
I mostly agree about the justification in the repo being wrong, but wanted to engage about this point:
> Image generators cannot insert watermarks into things they did not generate
It's actually very easy to take a real image, ask Gemini/ChatGPT to modify some tiny part of it (could be something as silly as lighting/shadow/etc), and often the resulting image will be detected by their watermarking tools. This way you can easily present any real image as AI-generated.
Ignoring that a watermark removal tool does not help with this threat model, the claim is still true: the original image can not be changed, and instead a copy is created.
So what? I can also open an image in Photoshop and make sure it saves out some Photoshop specific EXIF data and try to claim the image was doctored. What I can't do is go and put my deceptive altered file up in place of the original in all the places on the Internet it exists.
I had to think about it, how about if the claim were:
If you take a photograph that is misidentified as AI generated, you can “preserve the historical record“ by using this tool before publishing the image.
(Anyone know the false positive rate with watermark IDs, would’ve hoped it’s like zero)