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Evaluate selective text restoration
This commit is contained in:
Victor Kuznetsov
@@ -7,31 +7,384 @@ ground truth and instructions.
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| Original | Provider | Content | Exercises |
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| --- | --- | --- | --- |
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| `ChatGPT Image May 31, 2026, 02_02_23 PM.png` | OpenAI | Light multilingual typography | Text preservation |
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| `ChatGPT Image May 31, 2026, 02_03_55 PM.png` | OpenAI | Multilingual typography | Text preservation |
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| `Gemini_Generated_Image_633uuy633uuy633u.png` | Google | Landscape with a Chinese sign | CJK text preservation |
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| `Gemini_Generated_Image_y48j3cy48j3cy48j.png` | Google | Portrait grid | Face identity and skin texture |
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## Text ground truth
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`ground-truth.json` contains hand-verified OCR for the two text-bearing
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`ground-truth.json` contains hand-verified OCR for the three text-bearing
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originals. To regenerate an OCR seed:
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```bash
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uv run scripts/fidelity_metrics.py ocr \
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"data/synthid/originals/ChatGPT Image May 31, 2026, 02_03_55 PM.png" \
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"data/synthid/originals/ChatGPT Image May 31, 2026, 02_02_23 PM.png" \
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data/synthid/originals/Gemini_Generated_Image_633uuy633uuy633u.png \
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--langs en,ru,ch \
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--out data/evaluations/fidelity/ground-truth.json
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```
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Verify and correct the generated text by hand before using it as ground truth.
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`text-lines.json` contains the verified per-line strings and source-space boxes
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used by the evaluation-only selective-restoration experiment. It is not an
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automatic scene-text annotation set.
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`scripts/infer_text_lines.py` can generate a draft from source pixels without
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existing annotations. On the two posters it proposed 20 and 18 lines at the
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default threshold, but exact-text precision was only 90.0% and 94.4% because
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high-confidence OCR still dropped an English comma and replaced a Chinese comma
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with ASCII. Its output therefore requires manual verification of every line;
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`accepted` means crop-stable, not ground-truth-correct.
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## Text-preservation benchmark
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`text-preservation-2026-08-13.csv` records a fixed-seed comparison of the two
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current profiles and a global Z-Image Turbo prototype on all three text
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fixtures. Each candidate ran through the
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complete `visible -> invisible -> metadata` route with its profile default
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strength and adaptive-polish setting. The Z-Image prototype instead sweeps
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0.08, 0.10, 0.15, 0.20, and 0.25 without polish because its provider-specific
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removal floor is not known. The output hash identifies the exact bytes
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measured; generated outputs remain outside the repository.
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The character-weighted added CER is 0.262 for `qwen-zimage` and 0.256 for
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`sdxl-zimage`. That 0.006 absolute difference is not a
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stable ordering: SDXL wins the light poster, Qwen wins the dark poster, and the
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Chinese sign is tied. A paired sign test on the two non-ties is 1-1 (`p=1.0`).
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The measured sample therefore does not support a general text-preservation
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winner. Both profiles substantially degrade the smallest multilingual poster
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text and preserve the larger Chinese sign.
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Z-Image Turbo is the clear fidelity lead. At strength 0.10 its
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character-weighted CER is 0.093, against the unchanged sources' 0.124 OCR
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floor, while whole-image LPIPS stays between 0.047 and 0.086. Visual inspection
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still finds substitutions in the smallest Cyrillic and Chinese poster lines,
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so a favorable OCR score does not mean pixel-exact text. Quality drops quickly
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above 0.15; at 0.25 the weighted CER is 0.428.
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Provider-oracle checks on 2026-08-13 bracket the OpenAI requirement at no more
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than 0.10 for this sample. Both original OpenAI controls were detected by
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`openai.com/verify`; the light poster was clean at 0.08, while the dark poster
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was detected at 0.08 and clean at 0.10. The light 0.10 output was not separately
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checked. Google fails the entire tested sweep. The original Gemini image was
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detected through C2PA, and a pixel-identical copy with AI metadata stripped was
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separately detected by Gemini's built-in SynthID verifier. Z-Image outputs at
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0.08, 0.10, 0.15, 0.20, and 0.25 were all still detected. At 0.25 the weighted
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CER has already risen to 0.428, worse than the raw weighted CER of both current
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profiles (Qwen 0.387, SDXL 0.381). Increasing strength beyond the measured grid
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would therefore no longer serve the text-preservation objective without a new
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mechanism or hypothesis. Z-Image is not a viable global replacement on this
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evidence: no clean Google operating point was found before it lost its fidelity
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advantage.
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Qwen-Image-2.0 was not added to the numeric comparison. Its weights are not
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published, and its hosted edit API exposes an editing instruction and seed but
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no low-strength denoise control. It can be evaluated as a separate hosted edit
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strategy when credentials are available, but it is not a drop-in replacement
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for the partial-regeneration mechanism measured here.
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The OCR floor is the source image scored against the hand-verified text. Use
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`added_cer = text_cer - ocr_floor` when interpreting pipeline damage, because the
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unchanged poster sources already score 0.127 CER. `oracle_rechecked=true` marks
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the exact Z-Image bytes checked above; the remaining rows were not rechecked.
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The table does not certify other seeds, content classes, or strengths beyond
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the recorded provider verdicts.
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## Text-restoration prototype
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`text-restoration-2026-08-13.csv` evaluates an OCR-driven post-pass on the exact
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Qwen outputs above. The prototype recognizes English and Russian with macOS
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Vision and CJK with PaddleOCR, derives glyph masks independently from the
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source and Qwen output, removes both sets of glyphs with block-wise LaMa, and
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draws the recognized strings with new system-font pixels. It never composites
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source pixels back into the result.
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On the two multilingual posters, character-weighted CER fell from 0.338 and
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0.305 to 0.007 on both. OpenAI Verify reported no OpenAI signals for both Qwen
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controls and both restored outputs in the same run. The improvement comes with
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a substantial whole-image fidelity cost: LPIPS rose from 0.107 to 0.174 and
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from 0.095 to 0.162, while PSNR fell by about 10.5-11.4 dB. Visual inspection
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found one residual shadow in the smallest English line of the light poster;
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the dark poster was clean but the substitute fonts visibly changed typography.
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The Chinese sign did not improve: CER rose from 0.074 to 0.111 because the OCR
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and renderer changed punctuation. The Gemini verifier returned detected for
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both the restored output and its byte-identical Qwen control on a third work
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account, although that Qwen hash had previously returned clean on another work
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account. This run therefore does not isolate a restoration-stage regression;
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its Google verdict is inconclusive until a source-positive, Qwen-negative
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control can be reproduced in the same available account.
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This prototype is not ready to ship. Its strongest result establishes that
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fresh-glyph reconstruction can recover literal text without reintroducing an
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OpenAI signal, but portable OCR, font/style reconstruction, a tighter mask, and
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a reproducible Google oracle control remain prerequisites.
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### Selective restoration follow-up
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`selective-text-restoration-2026-08-13.csv` compares that full compositor with
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a selective prototype on the same two posters. The prototype leaves a Qwen line
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unchanged when padded source and output recognition agree, and applies the same
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LaMa plus fresh-system-font reconstruction only to lines whose recognized text
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changed. This reduced the edited area from 15.4% and 17.0% to 5.5% on both
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posters.
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Under one consistent Paddle `en+ru+ch` measurement route, selective restoration
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reduced Qwen CER from 0.378 to 0.101 on the light poster and from 0.413 to 0.112
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on the dark poster. Its image LPIPS was 0.120 and 0.103, substantially closer to
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Qwen than the full compositor's 0.174 and 0.162. These CER values must not be
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mixed with the preceding table's Vision/Paddle hybrid values: the comparison
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file remeasures all three variants through Paddle so their relative result is
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valid on one OCR route.
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OpenAI Verify returned `No OpenAI signals detected` for both selective outputs,
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then detected the original light poster as `Generated with OpenAI tools` in the
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same Chrome sequence. Visual inspection found the dark output clean, but the
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light output still retained a local shadow around one replaced fine-text line.
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Selective restoration is therefore the strongest current direction, not a
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production-ready default. The next implementation needs automatic line matching
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and a tighter source-plus-candidate glyph mask before it can be proposed for the
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pipeline.
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A mask-only follow-up added two pixels of dilation around every selected glyph.
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It visually removed the light poster's shadow and improved its CER from 0.101 to
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0.081 with effectively unchanged LPIPS, but increased the edited area from 5.5%
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to 7.0%. Applying the same rule to the dark poster worsened CER from 0.112 to
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0.147. These expanded-mask rows were not resubmitted to the provider oracle.
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The opposing result rules out one global dilation constant and makes per-line
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residual detection the next fidelity gate.
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An automatic follow-up removed the hand-selected line list. For each known
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source line, it runs a recognition-only model on padded, upscaled source and
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Qwen crops. It preserves a line only when both confidence scores are at least
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0.75, the source recognition is within 0.25 normalized edit distance of the
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verified line, and normalized source and candidate recognition match exactly.
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This reproduced the manual dark-poster line selection and additionally kept one
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correct large Russian line on the light poster.
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The automatic prototype also replaced uniform dilation with a second measured
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LaMa pass. After the first erase, it extracts contrast remaining at the original
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glyph positions, dilates only that residual, and inpaints it before drawing fresh
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text. Visual inspection found no remaining double glyphs on either output. The
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effective edited fractions were 4.1% and 5.7%. Image LPIPS was 0.113 and 0.104,
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against 0.120 and 0.103 for the manual selective version. Detector-based page CER
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was 0.123 and 0.119; the light value is inflated by the detector splitting the
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preserved Cyrillic line into Latin-like fragments even though the padded Russian
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recognizer reads it exactly. This is another reason that line decisions use
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recognition-only crops rather than the page detector's aggregate CER.
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Both exact automatic output hashes returned `No OpenAI signals detected`, and
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the original light poster returned `Generated with OpenAI tools` immediately
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afterward in the same Chrome sequence. The tracked script reproduced the dark
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hash exactly. Its light output differed from the initial prototype in only 386
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pixels by at most one channel value because separate ONNX environments rounded
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differently; the script's exact `900def5a...` hash was therefore submitted and
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also returned clean before the positive source control.
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The script and its required verified line annotations are tracked as
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`scripts/selective_text_restoration.py` and `text-lines.json`. For example:
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```bash
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PADDLE_PDX_DISABLE_MODEL_SOURCE_CHECK=True \
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uv run scripts/selective_text_restoration.py \
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data/synthid/originals/Gemini_Generated_Image_633uuy633uuy633u.png \
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path/to/qwen-candidate.png \
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--restoration vae-glyphs \
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--glyph-donor path/to/qwen-vae-reconstruction.png \
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--glyph-feather 0.5 \
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--output path/to/selective-output.png \
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--manifest path/to/manifest.json
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```
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The restoration mode is deliberately explicit. `vae-glyphs` requires a
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separately generated VAE reconstruction in `--glyph-donor`; it takes exact
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thresholded glyph cores from that donor, uses a fresh silhouette beneath them,
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and defaults to a narrow 0.5-pixel donor edge. The donor and the resulting exact bytes still require
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full-pipeline oracle evaluation. `rerender` reproduces the tracked
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fresh-system-font experiment. `source-glyphs` is only for compositing a
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separately regenerated, oracle-evaluated layer; feeding it the watermarked
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original would paste provenance-bearing pixels back into the result. The
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`--keep-background --composite-mask boxes` combination is an aligned-layer
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experiment and is not a production text restorer.
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The `source-silhouette` follow-up keeps the source glyph geometry but discards
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its pixel amplitudes: it thresholds each source line to a binary shape, samples
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one foreground color, and synthesizes new antialiasing over the scrubbed image.
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On a 24-image matrix spanning serif, Latin-diacritic, Cyrillic, CJK, tiny-UI,
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and rotated text, the original outer-feather compositor preserved all 34
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source-readable lines exactly under crop OCR, with median text-box SSIM 0.859.
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An inner-antialias variant raised median text-box SSIM to 0.902 and left
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whole-image SSIM unchanged at 0.672, but preserved 33/34 lines: OCR read one
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middle dot as a colon. The higher-fidelity antialiasing is retained in the
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evaluation script, with that punctuation miss recorded as a caveat. Its exact
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outputs were not submitted to the provider oracle because the
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public verifier reached its request limit; a clean verdict from the earlier
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outer-feather bytes does not transfer to the new hashes.
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Follow-up visual review on a typography-rich control rejected both silhouette
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compositors despite their OCR and SSIM scores. They preserved literal content
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and approximate glyph geometry, but changed stroke weight, color variation,
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edge antialiasing, and small decorative details enough to be plainly different
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from the source. OCR exactness and text-box SSIM are therefore screening metrics,
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not acceptance gates for source-typography preservation. A candidate must also
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retain source-like edge pixels and pass direct visual comparison at native size.
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A narrower Qwen-VAE donor follow-up keeps the scrubbed background, then copies
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only VAE-reconstructed pixels through the source-silhouette mask with a
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0.5-pixel feather. Across the 48-case typography matrix (548 annotated lines),
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text-box SSIM improved in 47/48 cases and glyph-edge error improved in 48/48.
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Median text-box SSIM rose from 0.854 to 0.914, while median glyph-edge MAE fell
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from 37.59 to 32.42. The median nonzero alpha area was 3.62%; on dense or large
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text this is still substantially wider than the target control. These are
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fidelity results only; the 48 matrix outputs were not submitted to the provider
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oracle. On a separate untracked dense-typography control, the exact core-only
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Qwen-VAE donor with a 1.43% source-silhouette area returned `No OpenAI signals
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detected`. Its 0.5-pixel feathered sibling, which raises the nonzero donor area
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to 2.75%, returned the same verdict and improved mean text-box SSIM from 0.957
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to 0.960. Crop OCR recovered from 7/15 exact lines on the raw pass to 14/15,
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matching the source OCR floor. Whole-image LPIPS was 0.082, but only 0.108% of
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pixels were exactly unchanged and the detected face retained 0.670 of source
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Laplacian variance. The tracked script reproduced the feathered file byte for
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byte. These two exact-byte verdicts do not certify other images or the larger
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matrix masks, and the global smoothing fails a strict unchanged-image criterion.
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The Google result is negative. On the synthetic CJK sign case, two separate
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work-account runs both detected SynthID in the resaved source control and in the
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exact Qwen-VAE donor output. The candidate improved mean text-box SSIM from
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0.791 to 0.835 and glyph-edge MAE from 35.48 to 22.49 with a 3.67% donor area,
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but Gemini still detected it. The intermediate Qwen silhouette base and the
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earlier original-sign Qwen baseline were also detected in the same account.
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This isolates the current blocker upstream of text restoration: the global
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Google pass did not reach the SynthID removal floor, so the OpenAI-clean
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`vae-glyphs` configuration cannot be used as a Google operating point.
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On the large Chinese-sign control, source and candidate recognition agreed on
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all three lines. The script selected no changed lines, emitted a zero mask, and
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copied the candidate byte for byte instead of re-encoding it. This corrects the
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earlier unnecessary CJK rerender and proves the no-edit branch. It does not add
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a Google-negative oracle result: the available Google account still cannot
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reproduce a source-positive, Qwen-negative control sequence.
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The earlier automatic rerender was the first variant in the experiment to pass
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the recorded visual, fidelity, and OpenAI-oracle gates on its two poster
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fixtures. The later typography-rich control shows that result does not
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generalize to source-typography preservation. It remains evaluation-only: it
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depends on verified source text and source line boxes, uses macOS system fonts,
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and has not been validated on natural scene text, rotated text, or automatic
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line-box discovery.
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An opt-in `--detect-boxes` follow-up tested automatic geometry. Grouping Paddle
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word detections by vertical overlap found exactly 20/20, 20/20, and 3/3 lines;
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mean IoU with verified boxes was 0.857, 0.847, and 1.000. Reusing the annotation
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crop padding was unstable and preserved only 4/20 dark-poster lines. Reducing
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vertical recognition padding to 10% restored the exact 8/20 and 7/20 selection
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decisions, but detector CER was 0.127 and 0.154 rather than 0.123 and 0.119. The
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dark regression failed the fidelity gate, so these hashes were not submitted to
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the provider oracle. The flag is retained only to reproduce that negative
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evaluation and still requires verified strings and an exact line-count match.
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### AnyText2 glyph-conditioned follow-up
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`anytext2-restoration-2026-08-13.csv` tests the official Apache-2.0
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AnyText2 checkpoint as a local text-editing pass over the exact Qwen Chinese-sign
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output. The checkpoint hash was verified against ModelScope. Its own edit example
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successfully replaced a masked blackboard line with the requested `DADDY`, so the
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runtime and checkpoint were functional before the tracked fixture was measured.
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AnyText2 failed the fidelity gate. The standard full-image detector scored the
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default edit at CER 0.185 and the source-font mimic at 0.222, against 0.074 for
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Qwen; image LPIPS moved from 0.289 to 0.338 and 0.345. A padded crop-recognition
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cross-check removed the detector's punctuation misses: Qwen scored 0.000, the
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default edit still scored 0.074 with two substituted characters, and the mimic
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edit stayed at 0.222. Visual inspection agreed, with additional line-shape and
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punctuation errors in the mimic output. No provider-oracle submission was made
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because neither candidate preserved the requested content better than its
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already-clean Qwen input.
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This result covers the published SD1.5 checkpoint, three Chinese lines of no more
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than 20 characters, one seed, and one fixture. The repository still describes
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AnyText2XL as unreleased, and the inference wrapper truncates each requested line
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after 20 characters, so the published model cannot directly cover the longer
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English and Russian poster lines.
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The padded cross-check also changes the interpretation of this fixture's earlier
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restoration result. Its Qwen image already contains all three correct Chinese
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lines; the reported 0.074 came from the detector cropping the final punctuation
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from two lines. A deterministic rerender with horizontally padded recognition
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and a mask-matched Hiragino Sans GB W6 font reached detector CER 0.000, but image
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LPIPS worsened from 0.289 to 0.327 and the font was visibly heavier. The correct
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policy on this large-text fixture is therefore to leave a Qwen line unchanged
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when padded recognition confirms the source and candidate strings agree.
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## Face-stage isolation
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`face-stage-isolation-2026-08-13.csv` separates the two stages on the 18-face
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Gemini portrait-grid fixture. All variants use the same visible-cleaned,
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metadata-stripped input and seed 0. The prepared input remained positive in the
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Gemini SynthID verifier, so the surrounding visible and metadata stages did not
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create the clean verdicts.
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| Route | Gemini oracle | ID cosine | Face LPIPS | Laplacian ratio | Image LPIPS |
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| --- | --- | ---: | ---: | ---: | ---: |
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| Prepared control | detected | - | - | - | - |
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| Z-Image face stage only | detected | 0.927 | 0.028 | 0.612 | 0.013 |
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| Qwen global stage only | clean | 0.589 | 0.217 | 0.331 | 0.288 |
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| Full Qwen then Z-Image | clean | 0.852 | 0.050 | 0.492 | 0.252 |
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This isolates the roles: the Qwen global pass removes the watermark, while the
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masked Z-Image pass restores face identity and detail without reintroducing a
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detectable whole-image signal. Z-Image face-only does not remove SynthID. The
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result explains why the face stage succeeded while global Z-Image failed: the
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earlier clean verdict belonged to the two-stage pipeline, not to Z-Image as a
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standalone remover. This is one fixture, one seed, and one oracle pass per
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variant; it does not establish a general reintroduction threshold for mask size.
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## Upstream Synthid-Bypass v2 reproduction
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`upstream-v2-reproduction-2026-08-13.csv` records a source-level audit and a
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close reproduction of the public
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[`Synthid-Bypass-v2.0.json`](https://github.com/cebeuq/Synthid-Bypass/blob/3007d0351596ae0a78b7074dae7ad179710b1e48/Synthid-Bypass-v2.0.json).
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The audited workflow is SHA-256
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`41911b3b8e01bf51450361dc8beccd84c9513f78ddb160430cdd9bebc294adf6` at
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upstream commit `3007d0351596ae0a78b7074dae7ad179710b1e48`.
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|
||||
Tracing links backward from `SaveImage` confirms that the active global stage is
|
||||
Qwen-Image-2512 Q4 with the Lightning four-step LoRA at 0.8, DiffSynth Canny at
|
||||
1.0, AuraFlow shift 3, `dpmpp_2m` plus `sgm_uniform`, CFG 1, and four steps. Its
|
||||
resolution helper uses adaptive level 6 over 0.08..0.15, which resolves to the
|
||||
0.154 ceiling for the 2816x1536 portrait fixture. Z-Image Turbo is used only by
|
||||
the face detailer: eight steps, CFG 1, `res_2s` plus `bong_tangent`, a 768 px
|
||||
guide, 1024 px cap, and direct adaptive denoise
|
||||
`clamp(0.10 * largest_face_ratio / 0.03, 0.05, 0.28)`. The active face regions
|
||||
come from YOLOv8-face plus SAM. Although the README describes MediaPipe as part
|
||||
of the strict path, the MediaPipe nodes do not reach the saved output. The
|
||||
1.2-megapixel scaler is also bypassed (`mode=4`).
|
||||
|
||||
The published upstream pair 12 changed from SynthID-positive to clean in the
|
||||
Gemini verifier and scored 0.975 face identity. On the project portrait fixture,
|
||||
the prepared control was positive, while both the close global reproduction and
|
||||
the close full reproduction were clean. The global stage scored 0.589 identity
|
||||
and 0.217 face LPIPS; the upstream-strength face stage improved those to 0.783
|
||||
and 0.083. The maintained profile's weaker face pass scored 0.852 and 0.050 on
|
||||
the same control, so copying upstream's roughly doubled face strength would be a
|
||||
quality regression on this fixture.
|
||||
|
||||
The close reproduction is intentionally labeled rather than presented as an
|
||||
exact ComfyUI run. It uses full-precision DiffSynth bf16 weights instead of the
|
||||
Q4 GGUF files, the maintained DiffSynth Lightning scheduler approximation
|
||||
instead of the ComfyUI sampler pair, YuNet plus SAM instead of YOLOv8-face plus
|
||||
SAM, and fixed seed 0 instead of randomized seeds. The two independent oracle
|
||||
controls and the published upstream pair establish the direction of the result;
|
||||
they do not make the local output byte-equivalent to upstream.
|
||||
|
||||
## Compare
|
||||
|
||||
```bash
|
||||
uv run scripts/fidelity_metrics.py compare \
|
||||
--original data/synthid/originals/Gemini_Generated_Image_y48j3cy48j3cy48j.png \
|
||||
--variant controlnet=<out>.png \
|
||||
--variant qwen=<out>.png \
|
||||
--variant qwen-zimage=<qwen-out>.png \
|
||||
--variant sdxl-zimage=<sdxl-out>.png \
|
||||
--ocr-langs ""
|
||||
```
|
||||
|
||||
@@ -0,0 +1,4 @@
|
||||
date,source_commit,fixture,variant,model,model_revision,model_sha256,ocr_route,text_cer,img_lpips,ssim,psnr_db,output_sha256,provider_oracle,notes
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,qwen-zimage,,,,"Paddle ch",0.074,0.289,0.696,23.3,4b05489c7a79f993d35d32528de792baad5a3e33ee950afa147caf5d3e0621,not_run,Exact Qwen baseline reused from text-restoration benchmark
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,qwen-zimage-anytext2-default,AnyText2-SD1.5,b06c583a583818f3679665ef67b51363f107853c,7d5d593928d842500e0da101ab6a1ae28a8d21403441ca62c813c4f92529ace8,"Paddle ch",0.185,0.338,0.642,18.2,87729fe7e0482d2cead6d3b7c7dd386ecc75ab3d8658131c54e67528b8f9feeb,not_run,Fidelity gate failed; padded crop recognition CER 0.074 still shows two substituted characters; locally composited three-line edit; 20 DDIM steps; seed 0
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,qwen-zimage-anytext2-mimic,AnyText2-SD1.5,b06c583a583818f3679665ef67b51363f107853c,7d5d593928d842500e0da101ab6a1ae28a8d21403441ca62c813c4f92529ace8,"Paddle ch",0.222,0.345,0.644,17.9,f5198d8f2365b79880aba8ea6b0c3885142b9de21c9f7f4f6712ac4a0db8dd85,not_run,Fidelity gate failed; source glyph masks supplied as font hints; 20 DDIM steps; seed 0
|
||||
|
@@ -0,0 +1,5 @@
|
||||
date,source_commit,fixture,route,seed,global_strength,face_strength,face_count,id_cos,face_lpips,lapvar_ratio,img_lpips,ssim,psnr_db,output_sha256,gemini_oracle
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_y48j3cy48j3cy48j.png,visible-metadata-control,0,,,18,,,,,,,9f67264beb1da66a710885464a11f2ae85989094149f6145521d302cd2db940b,synthid_detected
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_y48j3cy48j3cy48j.png,zimage-face-only,0,,0.06604512532552083,18,0.927,0.028,0.612,0.013,0.959,34.7,c388e9bbf737bb9b22a7cb2216ffb8026321ca632f9db29e1e456b7c14a8553f,synthid_detected
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_y48j3cy48j3cy48j.png,qwen-global-only,0,0.153999996,,18,0.589,0.217,0.331,0.288,0.646,24.2,281a1d28d786d157cbbd13d00a32b215de4dfb3174a3c5e4e83c843e5402138f,clean
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_y48j3cy48j3cy48j.png,qwen-zimage-full,0,0.153999996,0.06604512532552083,18,0.852,0.050,0.492,0.252,0.671,24.7,69de191bddbfbf53348c7638bdba661b6d45d257c00a8a2646b2558670c5a4c2,clean
|
||||
|
@@ -1,4 +1,5 @@
|
||||
{
|
||||
"ChatGPT Image May 31, 2026, 02_02_23 PM.png": "This is a longer sample text in English.\nTypography can flow smoothly from large to medium size.\nSmaller lines help demonstrate hierarchy, rhythm, and clarity.\nEven the finest text should remain clean and readable.\n这是一段较长的中文示例文本。\n排版可以从大字号逐渐过渡到中字号。\n更小的文字能够展示层次、节奏与清晰度。\n即使是最小的一行，也应该保持清楚易读。\nЭто более длинный пример текста на русском языке.\nТипографика может плавно переходить от крупного размера к среднему.\nБолее мелкие строки показывают иерархию, ритм и ясность.\nДаже самый маленький текст должен оставаться чистым и читаемым.",
|
||||
"ChatGPT Image May 31, 2026, 02_03_55 PM.png": "This is a longer sample text in English.\nTypography can flow smoothly from large to medium size.\nSmaller lines help demonstrate hierarchy, rhythm, and clarity.\nEven the finest text should remain clean and readable.\n这是一段较长的中文示例文本。\n排版可以从大字号逐渐过渡到中字号。\n更小的文字能够展示层次、节奏与清晰度。\n即使是最小的一行，也应该保持清楚易读。\nЭто более длинный пример текста на русском языке.\nТипографика может плавно переходить от крупного размера к среднему.\nБолее мелкие строки показывают иерархию, ритм и ясность.\nДаже самый маленький текст должен оставаться чистым и читаемым.",
|
||||
"Gemini_Generated_Image_633uuy633uuy633u.png": "每天都是一个新的机会。\n用微笑开始它。\n世界也会向你微笑。"
|
||||
}
|
||||
|
||||
@@ -0,0 +1,14 @@
|
||||
date,source_commit,fixture,variant,ocr_route,text_cer,img_lpips,ssim,psnr_db,mask_fraction,output_sha256,provider_oracle,oracle_control
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",qwen-zimage,"Paddle en+ru+ch",0.378,0.107,0.832,24.4,,bed68cf79a023cad582a11b41c4c2962bd90a218037ce931a2b3a8697e3bf4bd,no_openai_signals_detected,source-positive control established earlier
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",qwen-zimage-text-restored,"Paddle en+ru+ch",0.048,0.174,0.703,13.9,0.154,3221b2694f39420d509dd37cdaf69581432f9a189e87397346de0c78762402c6,no_openai_signals_detected,qwen-zimage clean in same run
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",qwen-zimage-text-selective,"Paddle en+ru+ch",0.101,0.120,0.796,19.5,0.054799,15b40b8cdf9e97558c66d4acdcb97d46769e64f04f143f8061746bc731fbbc21,no_openai_signals_detected,source detected in same browser sequence
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",qwen-zimage-text-selective-expanded-mask,"Paddle en+ru+ch",0.081,0.119,0.796,19.5,0.070267,5a8a0bcbe5763d1b1af0d64149cec7e35b16c5751e995d3bacf17581d64177ec,not_checked,fidelity-only follow-up
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",qwen-zimage-text-selective-automatic,"Paddle detector en+ru+ch; padded recognizer selection",0.123,0.113,0.808,21.2,0.041279,900def5a433c039aa474789eddc4dc4c63b8126ba1aff6829d2e8d600b9f9c71,no_openai_signals_detected,source detected immediately afterward in the same Chrome sequence
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",qwen-zimage,"Paddle en+ru+ch",0.413,0.095,0.818,26.0,,83e777ad28bf80a8e5aa7d2e6ef2348337c667212e2c71075460352ad7423713,no_openai_signals_detected,source-positive control established earlier
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",qwen-zimage-text-restored,"Paddle en+ru+ch",0.086,0.162,0.682,14.6,0.170,95812399424feb70fc56d3e518d1ae0a3a50a3c2049d5902b00686ede9d3022d,no_openai_signals_detected,qwen-zimage clean in same run
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",qwen-zimage-text-selective,"Paddle en+ru+ch",0.112,0.103,0.780,20.8,0.054912,846f39db0ad4a48a734a5019f0b0ff5d110eecb3210223407e72529dfa4fcf54,no_openai_signals_detected,source detected in same browser sequence
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",qwen-zimage-text-selective-expanded-mask,"Paddle en+ru+ch",0.147,0.104,0.779,20.8,0.072556,8ae76e1dedeec26bebb8d35e71fd92d77f142dbb0f3440b330cdf33b79558afe,not_checked,fidelity-only follow-up
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",qwen-zimage-text-selective-automatic,"Paddle detector en+ru+ch; padded recognizer selection",0.119,0.104,0.779,20.8,0.057110,ac4201bd2e342b1a37737319438cedb2203f6bb58cd9113f825cf9b80d913755,no_openai_signals_detected,source detected in same browser sequence
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,qwen-zimage-text-selective-automatic-passthrough,"Paddle detector ch; horizontal-only padded recognizer selection",0.074,0.289,0.696,23.3,0.000000,4b05489c7a79f993d35d32528de792baad5a3e33ee950afa147caf5d3e0621a6,not_checked,all three source and candidate recognitions agreed exactly; output is byte-identical to candidate
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",qwen-zimage-text-selective-detected-boxes,"Paddle ch detector boxes; 0.10-height recognizer padding",0.127,0.113,0.805,20.9,0.041280,70c52fed8b8a1d98f4cda8558ae08825313e510dfb372e448370d8dcf1da73b0,not_checked,fidelity-only automatic-box follow-up; same 8/20 preserve decisions
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",qwen-zimage-text-selective-detected-boxes,"Paddle ch detector boxes; 0.10-height recognizer padding",0.154,0.104,0.778,20.8,0.057146,1fa01ce706042c003a61429d5d97fc6c928ec32278071a91926d588f1e760b00,not_checked,fidelity-only automatic-box follow-up; same 7/20 preserve decisions but worse CER
|
||||
|
@@ -0,0 +1,51 @@
|
||||
{
|
||||
"ChatGPT Image May 31, 2026, 02_02_23 PM.png": [
|
||||
{"box": [156, 206, 709, 296], "text": "This is a longer", "script": "alphabetic"},
|
||||
{"box": [157, 293, 939, 379], "text": "sample text in English.", "script": "alphabetic"},
|
||||
{"box": [165, 393, 774, 434], "text": "Typography can flow smoothly from", "script": "alphabetic"},
|
||||
{"box": [161, 434, 521, 477], "text": "large to medium size.", "script": "alphabetic"},
|
||||
{"box": [165, 495, 566, 522], "text": "Smaller lines help demonstrate hierarchy,", "script": "alphabetic"},
|
||||
{"box": [165, 524, 354, 550], "text": "rhythm, and clarity.", "script": "alphabetic"},
|
||||
{"box": [165, 564, 448, 585], "text": "Even the finest text should remain", "script": "alphabetic"},
|
||||
{"box": [165, 593, 330, 613], "text": "clean and readable.", "script": "alphabetic"},
|
||||
{"box": [158, 673, 903, 740], "text": "这是一段较长的中文示例文本。", "script": "cjk"},
|
||||
{"box": [162, 753, 697, 793], "text": "排版可以从大字号逐渐过渡到中字号。", "script": "cjk"},
|
||||
{"box": [164, 807, 524, 829], "text": "更小的文字能够展示层次、节奏与清晰度。", "script": "cjk"},
|
||||
{"box": [163, 845, 483, 868], "text": "即使是最小的一行，也应该保持清楚易读。", "script": "cjk"},
|
||||
{"box": [162, 951, 780, 1009], "text": "Это более длинный пример", "script": "alphabetic"},
|
||||
{"box": [161, 1019, 723, 1062], "text": "текста на русском языке.", "script": "alphabetic"},
|
||||
{"box": [165, 1076, 639, 1104], "text": "Типографика может плавно переходить от", "script": "alphabetic"},
|
||||
{"box": [165, 1111, 505, 1133], "text": "крупного размера к среднему.", "script": "alphabetic"},
|
||||
{"box": [165, 1151, 513, 1172], "text": "Более мелкие строки показывают иерархию,", "script": "alphabetic"},
|
||||
{"box": [167, 1178, 287, 1192], "text": "ритм и ясность.", "script": "alphabetic"},
|
||||
{"box": [165, 1210, 417, 1227], "text": "Даже самый маленький текст должен", "script": "alphabetic"},
|
||||
{"box": [165, 1235, 381, 1247], "text": "оставаться чистым и читаемым.", "script": "alphabetic"}
|
||||
],
|
||||
"ChatGPT Image May 31, 2026, 02_03_55 PM.png": [
|
||||
{"box": [165, 204, 754, 299], "text": "This is a longer", "script": "alphabetic"},
|
||||
{"box": [167, 295, 1006, 385], "text": "sample text in English.", "script": "alphabetic"},
|
||||
{"box": [171, 401, 831, 446], "text": "Typography can flow smoothly from", "script": "alphabetic"},
|
||||
{"box": [169, 446, 560, 491], "text": "large to medium size.", "script": "alphabetic"},
|
||||
{"box": [173, 507, 605, 536], "text": "Smaller lines help demonstrate hierarchy,", "script": "alphabetic"},
|
||||
{"box": [173, 538, 379, 567], "text": "rhythm, and clarity.", "script": "alphabetic"},
|
||||
{"box": [175, 583, 481, 603], "text": "Even the finest text should remain", "script": "alphabetic"},
|
||||
{"box": [173, 611, 352, 632], "text": "clean and readable.", "script": "alphabetic"},
|
||||
{"box": [170, 693, 956, 757], "text": "这是一段较长的中文示例文本。", "script": "cjk"},
|
||||
{"box": [174, 775, 740, 812], "text": "排版可以从大字号逐渐过渡到中字号。", "script": "cjk"},
|
||||
{"box": [175, 829, 561, 852], "text": "更小的文字能够展示层次、节奏与清晰度。", "script": "cjk"},
|
||||
{"box": [174, 869, 534, 892], "text": "即使是最小的一行，也应该保持清楚易读。", "script": "cjk"},
|
||||
{"box": [169, 958, 824, 1022], "text": "Это более длинный пример", "script": "alphabetic"},
|
||||
{"box": [171, 1029, 764, 1074], "text": "текста на русском языке.", "script": "alphabetic"},
|
||||
{"box": [175, 1090, 678, 1119], "text": "Типографика может плавно переходить от", "script": "alphabetic"},
|
||||
{"box": [175, 1125, 546, 1151], "text": "крупного размера к среднему.", "script": "alphabetic"},
|
||||
{"box": [175, 1169, 552, 1192], "text": "Более мелкие строки показывают иерархию,", "script": "alphabetic"},
|
||||
{"box": [175, 1196, 312, 1217], "text": "ритм и ясность.", "script": "alphabetic"},
|
||||
{"box": [175, 1233, 479, 1253], "text": "Даже самый маленький текст должен", "script": "alphabetic"},
|
||||
{"box": [177, 1259, 440, 1272], "text": "оставаться чистым и читаемым.", "script": "alphabetic"}
|
||||
],
|
||||
"Gemini_Generated_Image_633uuy633uuy633u.png": [
|
||||
{"box": [1281, 650, 2357, 818], "text": "每天都是一个新的机会。", "script": "cjk"},
|
||||
{"box": [1466, 788, 2167, 957], "text": "用微笑开始它。", "script": "cjk"},
|
||||
{"box": [1367, 910, 2264, 1112], "text": "世界也会向你微笑。", "script": "cjk"}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,25 @@
|
||||
date,source_commit,fixture,profile,route,seed,strength,adaptive_polish,text_cer,ocr_floor,added_cer,img_lpips,ssim,psnr_db,output_sha256,oracle_rechecked
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",original,reference,,,,0.127,0.127,0.000,0.000,1.000,inf,,not_applicable
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",qwen-zimage,visible-invisible-metadata,0,0.11020972541176471,false,0.378,0.127,0.251,0.107,0.832,24.4,bed68cf79a023cad582a11b41c4c2962bd90a218037ce931a2b3a8697e3bf4bd,false
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",sdxl-zimage,visible-invisible-metadata,0,0.15,true,0.356,0.127,0.229,0.125,0.707,25.3,9bb932d6e66b52f34ff07c3fcdbdb9c33eb601ae2cd84bec6b8c7b5e30df9926,false
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",original,reference,,,,0.127,0.127,0.000,0.000,1.000,inf,,not_applicable
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",qwen-zimage,visible-invisible-metadata,0,0.11020972541176471,false,0.413,0.127,0.286,0.095,0.818,26.0,83e777ad28bf80a8e5aa7d2e6ef2348337c667212e2c71075460352ad7423713,false
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",sdxl-zimage,visible-invisible-metadata,0,0.15,true,0.422,0.127,0.295,0.099,0.754,25.9,7605b1175b0c99f481ae6929acc488f34d98bc0f2571d42a1d2972b671d9b8cb,false
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,original,reference,,,,0.037,0.037,0.000,0.000,1.000,inf,,not_applicable
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,qwen-zimage,visible-invisible-metadata,0,0.153999996,false,0.074,0.037,0.037,0.289,0.696,23.3,4b05489c7a79f993d35d32528de792baad5a3e33ee950afa147caf5d3e0621a6,false
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,sdxl-zimage,visible-invisible-metadata,0,0.25,true,0.074,0.037,0.037,0.176,0.769,26.1,d9f89465c31bd2d38ffb111775b9bbea4577f40713fcbebf421e05d344ab27ad,false
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",zimage-global,visible-invisible-metadata,0,0.08,false,0.068,0.127,-0.059,0.042,0.874,31.4,534de6422a3a03cfde44377aa9bf824a8267db3b73511240f8f07fb8dcb95eff,true
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",zimage-global,visible-invisible-metadata,0,0.10,false,0.086,0.127,-0.041,0.047,0.862,30.8,4dba8211e8d84ebbfff72de00f54d4365d0d202394acd412d1419ae93d1e9f71,false
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",zimage-global,visible-invisible-metadata,0,0.15,false,0.177,0.127,0.050,0.065,0.838,29.1,fc45c5fff6d33f15d30e05dd02580fe0addd97098b735b2894015f9abdaa43a7,false
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",zimage-global,visible-invisible-metadata,0,0.20,false,0.248,0.127,0.121,0.093,0.813,27.3,1e55e11f0e289a752098370e9f1d53fed6cd4fab7ceff46fe86dd20c927f9ffb,false
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",zimage-global,visible-invisible-metadata,0,0.25,false,0.343,0.127,0.216,0.120,0.787,25.7,f5a2d2829e88a790cff5bedc50fca1f878a92cdb392d530afb49d0d95c23b884,false
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",zimage-global,visible-invisible-metadata,0,0.08,false,0.143,0.127,0.016,0.042,0.877,31.5,5cfa466e276ab37cf532f7458d6dd86ea4f0807e2cbdb6788b7c01ca6ee35a1a,true
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",zimage-global,visible-invisible-metadata,0,0.10,false,0.101,0.127,-0.026,0.047,0.864,30.9,ade869ec7c5b08098495d9b9d67ee900773f189f94bbb411b043f242f5c2fa37,true
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",zimage-global,visible-invisible-metadata,0,0.15,false,0.208,0.127,0.081,0.060,0.839,29.3,a11976963e3f2ca856ce66278e22064d51345d449fa6d672029039a79517d60a,false
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",zimage-global,visible-invisible-metadata,0,0.20,false,0.341,0.127,0.214,0.070,0.819,27.6,1ab1ae075565e9d39960a80cf5d61e5b0c50d7e23283493ea0277056b3e964ab,false
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",zimage-global,visible-invisible-metadata,0,0.25,false,0.538,0.127,0.411,0.084,0.799,25.6,5ff5a364d84f738de4c56ead7d4950a2f9a1aaf4bec16e97bda6a65915744a57,false
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,zimage-global,visible-invisible-metadata,0,0.08,false,0.074,0.037,0.037,0.068,0.865,30.8,81419eddc3e5150956859dd10c26dd841bb93d9c8b34c01f344e6d69bca6edbf,true
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,zimage-global,visible-invisible-metadata,0,0.10,false,0.074,0.037,0.037,0.086,0.844,29.8,4d1f32bd0dac0e05885ff943e7c10230b06de7d8547e6215f8e2941f732a1df5,true
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,zimage-global,visible-invisible-metadata,0,0.15,false,0.000,0.037,-0.037,0.135,0.793,27.6,526c7987b34896f9513f7439b63b8a87573b59d15930fa307f3bb924435f3cec,true
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,zimage-global,visible-invisible-metadata,0,0.20,false,0.000,0.037,-0.037,0.179,0.746,25.9,325364cf7a3b5d39ac0c44af82181753ca4d6fde0f1b522c896414191725e8fc,true
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,zimage-global,visible-invisible-metadata,0,0.25,false,0.000,0.037,-0.037,0.218,0.703,24.5,f01d64dc0cabd45d66a93c1be39b819b988f29cda1f0a7bc0d5a1954571d807e,true
|
||||
|
@@ -0,0 +1,7 @@
|
||||
date,source_commit,fixture,variant,ocr_route,text_cer,img_lpips,ssim,psnr_db,mask_fraction,output_sha256,provider_oracle,oracle_control
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",qwen-zimage,"Vision en+ru; Paddle ch",0.338,0.107,0.832,24.4,,bed68cf79a023cad582a11b41c4c2962bd90a218037ce931a2b3a8697e3bf4bd,no_openai_signals_detected,source-positive control established earlier
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_02_23 PM.png",qwen-zimage-text-restored,"Vision en+ru; Paddle ch",0.007,0.174,0.703,13.9,0.154,3221b2694f39420d509dd37cdaf69581432f9a189e87397346de0c78762402c6,no_openai_signals_detected,qwen-zimage clean in same run
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",qwen-zimage,"Vision en+ru; Paddle ch",0.305,0.095,0.818,26.0,,83e777ad28bf80a8e5aa7d2e6ef2348337c667212e2c71075460352ad7423713,no_openai_signals_detected,source-positive control established earlier
|
||||
2026-08-13,2d03a00,"ChatGPT Image May 31, 2026, 02_03_55 PM.png",qwen-zimage-text-restored,"Vision en+ru; Paddle ch",0.007,0.162,0.682,14.6,0.170,95812399424feb70fc56d3e518d1ae0a3a50a3c2049d5902b00686ede9d3022d,no_openai_signals_detected,qwen-zimage clean in same run
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,qwen-zimage,"Paddle ch",0.074,0.289,0.696,23.3,,4b05489c7a79f993d35d32528de792baad5a3e33ee950afa147caf5d3e0621a6,synthid_detected,inconclusive account: clean baseline not reproduced
|
||||
2026-08-13,2d03a00,Gemini_Generated_Image_633uuy633uuy633u.png,qwen-zimage-text-restored,"Paddle ch",0.111,0.328,0.653,18.1,0.051,2ab7666a4161ff0e12c53d9412b23d013970c7613a8a55a1b1ae8a2744e3290d,synthid_detected,inconclusive account: qwen-zimage control also detected
|
||||
|
@@ -0,0 +1,6 @@
|
||||
date,upstream_commit,workflow_sha256,fixture,route,seed,global_strength,face_strength,face_count,id_cos,face_lpips,lapvar_ratio,img_lpips,ssim,psnr_db,output_sha256,gemini_oracle,implementation
|
||||
2026-08-13,3007d0351596ae0a78b7074dae7ad179710b1e48,41911b3b8e01bf51450361dc8beccd84c9513f78ddb160430cdd9bebc294adf6,comparison/before/12.png,official-before,,,,10,,,,,,,056276464387c883f5fd89bd2f1415faeb425abb3153cd10efb25d1b9053bdc2,synthid_detected,upstream-published-bytes
|
||||
2026-08-13,3007d0351596ae0a78b7074dae7ad179710b1e48,41911b3b8e01bf51450361dc8beccd84c9513f78ddb160430cdd9bebc294adf6,comparison/after/12.png,official-after,,,,10,0.975,0.093,0.354,0.172,0.820,23.8,a822d805666224adb3e360b3ee89e14f20a341f1e7c4d3a5d3d5251e9286aefe,clean,upstream-published-bytes
|
||||
2026-08-13,3007d0351596ae0a78b7074dae7ad179710b1e48,41911b3b8e01bf51450361dc8beccd84c9513f78ddb160430cdd9bebc294adf6,Gemini_Generated_Image_y48j3cy48j3cy48j.png,visible-metadata-control,0,,,18,,,,,,,9f67264beb1da66a710885464a11f2ae85989094149f6145521d302cd2db940b,synthid_detected,project-runtime-control
|
||||
2026-08-13,3007d0351596ae0a78b7074dae7ad179710b1e48,41911b3b8e01bf51450361dc8beccd84c9513f78ddb160430cdd9bebc294adf6,Gemini_Generated_Image_y48j3cy48j3cy48j.png,upstream-global-close-reproduction,0,0.153999996,,18,0.589,0.217,0.331,0.286,0.647,24.3,281a1d28d786d157cbbd13d00a32b215de4dfb3174a3c5e4e83c843e5402138f,clean,diffsynth-bf16-yunet-sam
|
||||
2026-08-13,3007d0351596ae0a78b7074dae7ad179710b1e48,41911b3b8e01bf51450361dc8beccd84c9513f78ddb160430cdd9bebc294adf6,Gemini_Generated_Image_y48j3cy48j3cy48j.png,upstream-full-close-reproduction,0,0.153999996,0.13209025065104166,18,0.783,0.083,0.470,0.260,0.659,24.7,2d7a8f76f98b905f14d69e5f9e11979610c72c6be7b6ac298dec4659f17bd819,clean,diffsynth-bf16-yunet-sam
|
||||
|
Reference in New Issue
Block a user