detect_doubao_frame reuses the image engine's synthetic doubao alpha as its
video template, so the glyph cannot drift between registries. The policy is
seedance-style single-floor, calibrated by sequential decode over 39
TC260-confirmed Doubao corpus videos and 25 negatives: a 12-frame stable run
at 0.35 accepts 33/39 positives and 0/25 negatives (0.30 already accepted a
negative), and through the shipped arbiter identify_video selects 32/39 with
no false selection. Also documents the measured impossibility of a bare-pill
removal arm with the current detector (68 OCR-confirmed pills max 0.317 vs
clean negatives max 0.353 -- no separating threshold exists).
One committed example per registered mark: 12 PNG (image registry) and 6 MP4
clips (video registry), generated by scripts/render_visible_examples.py from
the committed silhouettes and detector templates -- never from user uploads.
The generator self-verifies (exit 1 when a mark misses its own example) and
tests/test_visible_examples.py holds both sides to it: registry completeness
both ways, per-engine detection on the canonical example, and the shipped
temporal selection accepting each clip.
Second tranche of measured-but-unregistered candidates parked under
scripts/assets/visible-mark-candidates/ with a README recording why none
ships yet (positives do not separate from clean negatives): samsung_en,
gemini_text, notebooklm, dola, mindvideo, higgsfield, jianying, capcut, zsky,
chromastudio, digenai, gendo.
Victor Kuznetsov