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Release 0.31.1 with calibrated provider strengths
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@@ -521,7 +521,7 @@ held by its masked ArcFace vector -- no original pixel copied.
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drift, NOT a perfect face swap. Set expectations; PuLID/InstantID are the higher-fidelity (heavier)
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paths if needed.
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- **Value scales with strength:** at low strength (OpenAI 0.10) faces barely drift, so FaceID is
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marginal; at the higher strength a hard vendor (Google 0.30) needs, FaceID earns its keep.
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marginal; at the higher strength then used for a hard vendor (Google 0.30), FaceID earned its keep.
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### Build plan (staged)
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@@ -177,13 +177,14 @@ path has not yet answered.
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The two profiles resolve an unset strength differently, because different things
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were measured for each.
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`qwen-zimage` reads it from image area, through the resolution-adaptive denoise
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curve. The vendor is deliberately ignored for openai/unknown content: the curve,
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not the issuer, is what was calibrated. One measured exception (0.27.2):
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Google-provenance content takes the flat `QWEN_ZIMAGE_GOOGLE_STRENGTH` 0.30 floor
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- the curve's 0.154 top left a 4.33 MP fixture oracle-detected on the full
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production path (2026-08-18), while 0.30 anchors measured clean on two fixtures
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in two accounts.
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`qwen-zimage` reads unknown content from the resolution-adaptive denoise curve.
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Measured provider cohorts instead take flat operating points: OpenAI `0.07675`,
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Google `0.27`, and Microsoft InvisMark `0.15`. OpenAI and Microsoft add one full
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observed cross-source boundary spread to the worst clean source; Microsoft's three
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first-clean boundaries were `0.04125`, `0.055`, and `0.095`, giving `0.14875` before
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rounding up. Google's candidate was separately repeated across three valid sources
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and three accounts. The small corpora make these operating points, not universal
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thresholds.
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`sdxl-zimage` reads it from the C2PA issuer, on a flat ladder:
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@@ -876,6 +876,11 @@ are CUDA-only. `controlnet`, `sdxl`, `qwen` and `default` were removed rather th
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kept as a CPU path, and are rejected rather than aliased onward. There is no
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content-dependent automatic router.
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`qwen-zimage` normally resolves global denoise from image area for unknown content.
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Measured provider cohorts bypass that curve with flat operating points. The values,
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measurement derivations, and corpus limits are canonical in
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[`known-limitations.md`](known-limitations.md#strength-is-content-and-seed-dependent).
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For serverless cold starts, `InvisibleEngine.preload(global_only=True)` loads the
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mandatory global stage and YuNet while leaving the optional Z-Image and SAM face
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stack lazy until a face is detected. The default `preload()` still loads every
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+11
-11
@@ -537,8 +537,8 @@ study (section 2.2) gives empirical floors:
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> were removed, and `OPENAI_STRENGTH` / `GEMINI_STRENGTH` / `UNKNOWN_STRENGTH` went
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> with them. Everything from here to the end of this section is a record of what was
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> measured on those profiles, kept because the oracle verdicts are still the evidence
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> base. For the strength policy in force now see `module-internals.md`: `qwen-zimage`
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> uses `resolution_adaptive_denoise`, `sdxl-zimage` a flat vendor ladder.
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> base. For the strength policy in force now see
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> [`known-limitations.md`](known-limitations.md#strength-is-content-and-seed-dependent).
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The default was **vendor-adaptive** (`watermark_profiles.resolve_strength` +
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`vendor_for_strength`): the tool read the C2PA issuer on the original input and picked
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@@ -691,9 +691,9 @@ solid at 0.10 but at 0.15 it is near-threshold noise; (2) for reliable removal p
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a strength with MARGIN above the borderline (controlnet >= 0.20), not exactly on
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it; (3) **historical engineering conclusion:** this dated run argued for a
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higher ControlNet strength than the then-current default. That proposal was
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later superseded. The current resolver intentionally shares the 0.10/0.15
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ladder between SDXL and ControlNet and uses a separate Qwen ladder; see
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`_internal/watermark_profiles.py`.
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later superseded. The resolver of that period shared the 0.10/0.15 ladder between
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SDXL and ControlNet; the current policies are recorded in
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[`known-limitations.md`](known-limitations.md#strength-is-content-and-seed-dependent).
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Source images are private (faces / product shots), not committed; reproduce on any
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photoreal + flat-graphic gpt-image pair, varying the seed, and re-checking the
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oracle.
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@@ -770,14 +770,14 @@ reproducible verification requires a fixed seed.
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Watermarking.** arXiv:2505.21620.
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https://arxiv.org/abs/2505.21620
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**Google floor on qwen-zimage (0.27.2, 2026-08-19).** The bracket above did not
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**Google floor on qwen-zimage (0.27.2, remeasured 2026-08-25).** The bracket above did not
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survive the full production path: on the 4.33 MP CJK-sign fixture (visible-stage
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sparkle removal -> qwen-zimage seed 0 at the curve's 0.154 top -> resize-back ->
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metadata strip), the Gemini verifier detected SynthID x3 with a valid
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pixel-identical stripped control in the same session. Google-provenance content
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now takes a flat `QWEN_ZIMAGE_GOOGLE_STRENGTH = 0.30` floor instead of the area
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curve - 0.30 anchors measured clean in Gemini on two fixtures (CJK sign +
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18-face) at 3/3 checks across two work accounts, and stayed clean with the
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vae-glyphs donor layer on top; openai/unknown content keeps the resolution
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curve. An explicit strength still wins. Certification artifacts: raiw-app
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initially took a flat `0.30` floor instead of the area curve. The later provider
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remeasurement established a common pass at `0.25` across three valid sources and
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separately repeated `QWEN_ZIMAGE_GOOGLE_STRENGTH = 0.27` across those sources and
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three accounts. OpenAI now has its own measured flat operating point; unknown
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content keeps the resolution curve. An explicit strength still wins. Certification artifacts: raiw-app
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`data/certification/text-restoration-2026-08-18/` (the failing re-baseline).
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@@ -20,8 +20,8 @@ filter applied to every candidate below.
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## Problem recap
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The `invisible` pipeline is SDXL base 1.0 img2img to defeat SynthID. The default
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strength has risen over time as Google hardens SynthID (0.05 -> 0.10 -> **~0.30**, the
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current threshold for fresh Gemini output); higher strength deforms text more, which is
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strength rose over time as Google hardened SynthID (0.05 -> 0.10 -> **~0.30** in
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this experiment; the later measured operating point is 0.27); higher strength deforms text more, which is
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exactly why text protection matters. Text is protected via Differential Diffusion with a
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per-pixel change map (`preserve` ~0.9) driven by the PP-OCRv3 DB detector
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(`text_protector.py`). Large text survives; **small text (sub ~8 px strokes) softens or
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