mirror of
https://github.com/wiltodelta/remove-ai-watermarks.git
synced 2026-06-05 02:28:00 +02:00
Victor Kuznetsov
411ef16ec3
Add an optional, commercial-safe face-restoration post-pass that recovers face identity the diffusion removal pass drifts (canny holds structure, not likeness) while still scrubbing the pixel watermark in the face regions. - face_restore.py: GFPGANer singleton (CPU unless CUDA), the basicsr torchvision.transforms.functional_tensor shim, and the pure feather _composite_faces helper (unit-tested without the model). GFPGAN re-synthesizes each face from a StyleGAN2 prior, so composited face pixels are GAN-generated (no watermark, no pixel-copy) -- oracle-clean at weight 0.5 with identity preserved. - InvisibleEngine.remove_watermark: restore_faces / restore_faces_weight, best-effort, auto-skips when the extra is absent or no face is detected. - CLI --restore-faces/--no-restore-faces + --restore-faces-weight on invisible/all/batch (on by default). - restore extra (gfpgan/facexlib/basicsr), numpy<2-pinned (scipy<1.18, numba<0.60) and kept out of `all`; basicsr needs Python <3.13 + setuptools<69 to build, so pin .python-version 3.12. Commercial-safe: GFPGAN Apache-2.0, RetinaFace MIT. The CodeFormer alternative is non-commercial and is not shipped. The earlier IP-Adapter FaceID layer was removed (footgun: needs high strength, corrupts faces at the low removal strength). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
53 lines
1.2 KiB
Plaintext
53 lines
1.2 KiB
Plaintext
# Dependencies
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.venv/
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__pycache__/
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*.egg-info/
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dist/
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build/
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# Environment secrets
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.env
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# OS files
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.DS_Store
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Thumbs.db
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# IDE
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.idea/
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.vscode/
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*.swp
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*.swo
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# Test results
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data/results/
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# SynthID corpus reference fills (synthetic black/white calibration tiles,
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# regenerable; the labeled pos/neg/cleaned images ARE tracked, see README)
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data/synthid_corpus/refs/
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# Reference materials
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_refs/
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# Downloaded model weights
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yolov8n.pt
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.coverage
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# Claude Code local settings
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.claude/settings.local.json
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.claude/scheduled_tasks.lock
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# Visible-watermark alpha calibration. The solid black/gray/white CAPTURES are
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# committed (content-free: a solid colour + the watermark; the source for
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# scripts/visible_alpha_solve.py so the alpha assets are reproducible). The
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# synthetic seeds (regenerable) and any real-content validation download (a real
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# generated scene, kept local for privacy) are NOT committed.
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data/doubao_capture/seeds/
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data/jimeng_capture/seeds/
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data/jimeng_capture/captures/jimeng_content_*.png
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data/gemini_capture/seeds/
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data/gemini_capture/captures/gemini_content_*.png
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# GFPGAN downloads its RetinaFace/parsing weights to a CWD ./gfpgan/weights/
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# working dir on first use (the restore extra). Runtime artifact, never committed.
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gfpgan/
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