It says not to use these tools to misrepresent AI-generated content as human-created. But the project is a watermark removal tool with a pip-installable CLI and

It says not to use these tools to misrepresent AI-generated content as human-created. But the project is a watermark removal tool with a pip-installable CLI and strength settings named "aggressive" and "maximum." Calling this research while shipping turnkey watermark stripping is trying to have it both ways in a way that's uncomfortable to read. The README itself reads like unedited AI output with several layers of history baked in. - V1 and V2 appear in tables and diagrams but are never explained. V3 gets a pipeline diagram that hand-waves its fallback path. - The same information is restated three times across Overview, Architecture, and Technical Deep Dive. ~1600 words padded to feel like a paper without the rigor. - Five badges, 4 made up, for a project with 88 test images, no CI, and no test suite. "Detection Rate: 90%" has no methodology behind it. "License: Research" links nowhere and isn't a license. - No before/after images, anywhere, for a project whose core claim is imperceptible modification. - Code examples use two different import styles. One will throw an ImportError. - No versioning. If Google changes SynthID tomorrow, nothing tells you the codebook is stale. The underlying observations about resolution-dependent carriers and cross-image phase consistency are interesting. The packaging undermines them.