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The July report (4-model ArcFace/LVFace bake-off, pre-opencv5 framework, 3-film training + held-out validation) is superseded by the opencv5 build: single-model LVFace-B, a 6-knob DE sweep over all 9 films, flood-fill presence, and the registry/decode fixes. Rather than overwrite it, archive it date-suffixed and start the current report fresh. - Rename the six July result pages to *-2026-07.md, rewrite their intra-archive cross-links, and add an "Archived (July 2026)" banner to each. - mkdocs nav: current report at top, the July set under an Archive section. - New docs/methodology.md for the opencv5 run: corrects the withdrawn anneal_sec/extinction_sec presence bridging (windows are now [first_seen, last_seen], AR-012/013), documents the two presence modes (track_extent / flood), and records that every eval scores all 9 films. The current experiment log (model-bakeoff.md) and Home rewrite land once the DE sweep converges and the final optimum is known.
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Archived (July 2026). This report covers the pre-opencv5 framework and the 4-model ArcFace/LVFace bake-off. It is superseded by the current experiment log for the opencv5 build. Kept for provenance; the numbers here are historical.
Whole gallery vs. cast-restricted gallery
Two ways to run the matcher. Full mode scores every detected face against the entire 2418-actor gallery. Restricted mode pre-filters each film's gallery down to just its Jellyfin-credited cast (typically around 15 top-billed actors) before the matcher runs.
Result
Averaged across the 3 compared models (r50 excluded, see the full experiment log) and both expansion settings, on the 4 training films:
| scope | F1 | P | R | total misID |
|---|---|---|---|---|
| full | 71.1% | 89.6% | 59.6% | 1121 |
| restricted | 75.9% | 90.4% | 65.6% | 299 |
Restriction improves every metric at once, not a precision/recall trade: +4.8pp F1, +6.0pp recall, roughly a quarter the total misIDs. Fewer candidates in the matcher's search space means fewer opportunities for a lookalike false match, and the recall gain shows this does not cost real detections.
Every model's best-scoring combo in the training matrix uses the restricted gallery:
See the full experiment log for the complete table. One
combo reaches zero true out-of-cast misidentifications,
arcface_w600k_mbf_restricted_exp (F1 76.2%), and it is a restricted one,
consistent with restriction, not expansion, being what suppresses cross-film
confusions.
The restriction effect (+4.8pp averaged across models) is larger than the model-choice effect: LVFace beats r18 by 6.2pp in full mode but beats mbf by 3.3pp. Restriction is the single strongest lever in the matrix.
Why this is not the shipped default
Cast restriction is implemented today only as an offline optimizer
technique
(scripts/optimizer/cast_restrict.py):
it pre-builds a filtered gallery file per film using Jellyfin's cast list
before the benchmark calls the matcher. There is no runtime "restrict to
this title's credited cast" switch in the shipped application;
scene_analyze always matches against whatever single gallery file it is
given.
Building this as a real feature requires:
- A live Jellyfin cast lookup at analysis time. The title is already known,
and
scripts/run_from_jellyfin.pyalready performs this lookup for its ownfilter_gallery-based restriction path; it is not wired intoscene_analyzeas a first-class option. - A decision on the fallback case: what happens to a real, uncredited cameo (see the Germar Terrell Gardner and Talia Balsam cases in the LVFace deep dive) if the restricted gallery never includes them at all.
- Regenerating the restricted-gallery cache whenever a title's Jellyfin cast list changes.
The shipped src/config.hpp defaults use
the full-mode winner (LVFace-B_Glint360K_full_exp, F1 75.3% training,
67.4% held-out macro) rather than the higher-scoring restricted_exp
(78.3%), because 78.3% describes a capability the application does not
have yet.