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https://github.com/wiltodelta/remove-ai-watermarks.git
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Victor Kuznetsov
1439eb0714
Adds the second face-restore mechanism, selectable via the new CLI option `--restore-faces-method=photomaker`. Unlike the existing GFPGAN path (which runs on the watermarked ORIGINAL and was oracle-confirmed to re-introduce SynthID by partial pixel blending), PhotoMaker carries identity in a SynthID-invariant OpenCLIP embedding and regenerates fresh face pixels conditioned on it — the pixels in the output are diffusion-fresh, so the watermark cannot be transported. The load-bearing assumption (embedding invariance to SynthID-magnitude pixel noise) was empirically validated in the prior commit (smoke test): cosine drift 0.002 under a ±2 LSB low-freq carrier, an order of magnitude less than JPEG90 drift which SynthID survives at >=99% TPR. End-to-end commercial-safe: - PhotoMaker-V2 weights: Apache-2.0 (TencentARC) - ID encoder: OpenCLIP-ViT-H/14 (MIT) - SDXL base: shared with the main pipeline - NO InsightFace (the non-commercial blocker for IP-Adapter FaceID / InstantID / PuLID / Arc2Face) Two-pass architecture (PhotoMaker has no ControlNetImg2img class in diffusers): 1) main controlnet/default removal pass cleans SynthID + drifts faces 2) PhotoMaker txt2img regenerates each face from its embedding, feather-composited back into the cleaned image New module `photomaker_restore.py` mirrors `face_restore.py`: lazy pipeline singleton (double-checked lock), `is_available()` gate, pure `_face_crop_square` and `_composite_faces` helpers, all unit-tested without the model (9 new tests). New `InvisibleEngine._restore_faces_photomaker` runs after the diffusion pass, mirroring `_restore_faces`. CLI flag `--restore-faces-method=[gfpgan|photomaker]` threaded through `cmd_invisible`/`cmd_all`/`cmd_batch` + `_process_batch_image`. New optional `photomaker` extra (Apache-2.0 + Apache-2.0/MIT deps, no basicsr). `[tool.hatch.metadata] allow-direct-references = true` is required because the upstream PhotoMaker package lives only on GitHub. The next step (separate work) is oracle validation: run a 6-image cert sweep through the new pipeline (default/controlnet at the certified strength + --restore-faces-method=photomaker) and confirm SynthID stays clean while face identity is recovered. The required infrastructure (`raiw-app/modal_cert.py`) is already in place. ruff + strict pyright(src/) clean; 586 tests pass (+ 9 new in tests/test_photomaker_restore.py). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>