mirror of
https://github.com/wiltodelta/remove-ai-watermarks.git
synced 2026-10-14 13:30:55 +02:00
Victor Kuznetsov
5c6588b3ef
Repair image and metadata publication contracts, detection routing, research artifact validation, release verification, and the published agent skill. Refresh the dependency lock and reconcile documentation with verified behavior. Add regression coverage and record the completed audit and corrected VideoSeal measurements. Preserve the existing Accelerate and Lightning versions. Validation: Ruff and Pyright pass; 2358 tests pass with 3 skipped. The maintenance gate exits 2 on the documented Accelerate and Lightning security findings.
101 lines
5.3 KiB
Markdown
101 lines
5.3 KiB
Markdown
# Repository data
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Tracked data is organized by purpose:
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```text
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data/
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fixtures/
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provenance/ Real format and provenance fixtures used by tests
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(source records live in fixtures/README.md)
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visible/ Per-mark example gallery: one synthetic canonical example per
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registered mark plus documented provider originals where available
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(see fixtures/visible/README.md)
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calibration/
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<vendor>/ Minimal controlled inputs needed to rebuild detector assets
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synthid/
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originals/ Canonical provider-oracle fixtures, stored once
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manifest.csv Provenance and verification record for each original
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full-pipeline-quality.csv
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Reusable full-pipeline evaluation selection
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evaluations/
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engine-selection/
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Prompt-matched, publication-cleared AI content matrix for
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deterministic auto-engine and watermark benchmark research
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fidelity/ Evaluation instructions and hand-verified ground truth
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video-synthid-oracle.csv
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Reproducible full-clip Gemini SynthID verdicts
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```
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[`image-watermark-examples.csv`](image-watermark-examples.csv) and
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[`video-watermark-examples.csv`](video-watermark-examples.csv) are the coverage
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indexes for real carriers. They point to each canonical binary instead of
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duplicating it and record unsupported gaps and source-specific licensing.
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## Storage rules
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Use only publication-cleared inputs in tracked data paths. Keep generated
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evaluation outputs outside the repository.
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1. Store each binary image once. Evaluation manifests and documentation point
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to its canonical location.
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2. Put executable test fixtures in `fixtures/`.
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3. Put only the minimal reproducible detector inputs in `calibration/`.
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4. Put externally verified SynthID originals in `synthid/originals/` and keep
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both CSV files synchronized.
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5. Keep evaluation outputs outside the repository. Record reproducible
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commands, hashes, and oracle verdicts instead of committing another corpus
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copy. A small curated before-and-after example may live in `docs/images/`
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when it is part of the public documentation.
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Local benchmark manifests may point to these canonical inputs or to an
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untracked corpus; every artifact and reference must carry its SHA-256 digest.
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`evaluations/engine-selection/` is the bounded exception for ORIGINAL study
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inputs: its manifest tracks a prompt-matched OpenAI/Meta content matrix, not
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generated model outputs or watermark-oracle evidence.
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6. Keep third-party fixture license notices in `licenses/`, outside directories
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that tests enumerate as media inputs.
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7. Runtime detector assets belong in `src/remove_ai_watermarks/assets/`.
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Unregistered research candidates belong in
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`scripts/assets/visible-mark-candidates/` so they are not shipped in the
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wheel.
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The source distribution excludes `data/`; the wheel contains only package
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runtime assets.
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## Video SynthID oracle manifest
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`evaluations/video-synthid-oracle.csv` is the only evidence that the shipped
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video removal profile works, so it is also the source of truth for three shipped
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defaults: `tests/test_video_invisible.py` asserts that `noise_std`, `long_side`,
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and `fps` together match a row this manifest records as certified. Changing one
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of those three without adding the row that certifies it fails the suite. Both
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historical rows mark `vae` as `unrecorded`: the repository must not infer a model
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identity from the current default. Add it to the assertion in the same commit as
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the first oracle row that records and verifies one.
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| Column | Meaning |
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| --- | --- |
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| `date`, `source_url`, `source_sha256` | Identify the carrier. |
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| `source_width`, `source_height`, `source_fps` | Carrier geometry. Without it the actual downscale factor of a row cannot be recovered later. |
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| `duration_seconds`, `source_verdict` | Clip length submitted and the verifier's reading of the untouched carrier. |
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| `vae`, `noise_std`, `long_side`, `fps`, `seed` | The run configuration. `unrecorded` means the historical run did not preserve the VAE identity. |
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| `output_sha256` | Identifies the exact submitted file. |
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| `output_verdict` | One of `detected`, `not_detected`, `indeterminate`, `refused`. |
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| `output_verdict_text` | The verifier's wording, verbatim. |
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| `output_detected_range` | Time range the verifier reported for the output. |
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| `track` | `visual`, `audio`, `both`, or empty. The verifier scores tracks separately and this path copies source audio unchanged. |
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| `session_id` | Groups rows submitted in one oracle session, so per-session drift stays visible. |
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| `stratum` | Content class of the carrier, for stratified certification. |
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| `psnr_db`, `temporal_residual_ratio` | Fidelity measurements. Neither is a watermark verdict. |
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Record `indeterminate` when the verifier answers with its unclear state rather
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than a negative: an unclear reading logged as `not_detected` is exactly the
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silent regression this manifest exists to prevent. Leave a field empty when it
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was not recorded, and never backfill it with a plausible value.
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`psnr_db` is measured against the already-resized frame and before the encode,
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so it excludes the downscale, the decimation, and the codec. Rows stay
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comparable to each other only while that definition holds.
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The two 2026-07-31 rows predate this schema; their empty fields were never
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recorded and are not recoverable from the row.
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