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https://github.com/wiltodelta/remove-ai-watermarks.git
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Restructure documentation, validate metadata removal, consolidate assets
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@@ -41,8 +41,8 @@ THE MEASUREMENT
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selects -- the script writes a contact sheet for exactly that.
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DATA SAFETY
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Corpus images are user uploads: read-only, local analysis, gitignored output. The
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template is font-rendered synthetic, never cut from a user upload.
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Treat input datasets as sensitive and read-only, and keep output gitignored. The
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template is font-rendered synthetic, never cut from an input image.
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uv run python scripts/cjk_tail_probe.py --n 6000
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"""
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@@ -66,12 +66,12 @@ sys.path.insert(0, str(Path(__file__).parent.parent))
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sys.path.insert(0, str(Path(__file__).parent))
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REPO = Path(__file__).resolve().parents[1]
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CORPUS = REPO / "data" / "spaces" / "originals"
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OUT = REPO / "data" / "spaces" / "_cjk_tail_probe.jsonl"
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CORPUS = REPO / ".local-eval" / "originals"
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OUT = REPO / ".local-eval" / "cjk-tail-probe.jsonl"
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# Cached under the gitignored data dir, not in scripts/: this is a probe artifact, not a
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# product asset. If the tail mark is ever registered, `render_vendor_silhouettes.py` is
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# what writes the committed silhouette into src/.../assets/.
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TAIL_PNG = REPO / "data" / "spaces" / "_cjk_tail_silhouette.png"
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TAIL_PNG = REPO / ".local-eval" / "cjk-tail-silhouette.png"
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# The tail is a fraction of a full vendor mark's width (`豆包AI生成` is ~5 CJK widths,
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# `AI生成` ~3), and the prefix length differs per vendor, so the size is genuinely
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@@ -262,7 +262,7 @@ def contact_sheet(rows: list[dict[str, Any]], thresh: float, limit: int = 30) ->
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if crop.size:
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tiles.append(cv2.resize(crop, (320, 96), interpolation=cv2.INTER_AREA))
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if tiles:
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dest = REPO / "data" / "spaces" / "_cjk_tail_sheet.png"
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dest = REPO / ".local-eval" / "cjk-tail-sheet.png"
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cv2.imwrite(str(dest), np.vstack(tiles))
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print(f"\ncontact sheet ({len(tiles)} crops, score >= {thresh:.3f}) -> {dest}")
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print("scores: " + ", ".join(f"{r['tail_score']:.2f}" for r in picks[: len(tiles)]))
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