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https://github.com/wiltodelta/remove-ai-watermarks.git
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Victor Kuznetsov
be14eca207
Ran the isolated raiw-controlnet-cert Modal app (raiw-app/modal_cert.py) over a
strength x seed grid, restore OFF, --max-resolution 1536, each vendor checked on its
OWN oracle (OpenAI -> openai.com/verify, Gemini -> the Gemini app). Certified
controlnet SynthID-removal floors:
- OpenAI 0.20: 2 photoreal images (9-face grid + bracelet) x seed {1,2,3} = 6/6 clean;
the bracelet that flipped at 0.15 is seed-robust at 0.20. Transfers to prod (OpenAI
removal is resolution-independent).
- Gemini 0.30: 0.20 detected -> 0.30 clean on 2/2 seeds (hardest face). Holds only at
<= 1536; Gemini is resolution-sensitive and raiw.cc runs NATIVE, so cap Gemini
<= 1536 + use 0.30, or native-calibrate (~0.35+).
Prod recipe recorded: controlnet + a controlnet-specific per-vendor schedule in
resolve_strength (OpenAI 0.20 / Gemini 0.30, NOT the default 0.10/0.15 ladder) +
FIXED prod seed (kills the near-threshold non-determinism) + restore reworked/off.
Added to docs/controlnet-removal-pipeline-research.md (certified floors table),
docs/synthid.md 5.5, and the CLAUDE.md controlnet bullet. Docs only.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>