Optimizer (scripts/optimizer/): replay.py runs the real C++ tracker/matcher/
scene_tracker chain over a dumped-embeddings HDF5 via sae_kpn, so a threshold
sweep never re-decodes video or re-embeds faces. optimize.py drives scipy's
differential_evolution over the knob space, with DE-level parallelism
(multiple population candidates evaluated concurrently via a ThreadPoolExecutor)
on top of per-film replay parallelism. second_score.py is the per-second X-Ray
scoring metric (TPI/FPI/FN, out-of-cast misID weighted 10x, fair recall masked
to gallery-known cast) that superseded an earlier scene-union metric.
dump_error_frames.py / dump_scene_montage.py extract annotated video frames
(bounding boxes, TPI/FPI/FN captions, onscreen-vs-offscreen split) for visual
review of a replay against ground truth. Gallery utilities: cast_restrict.py,
gallery_membership.py, fetch_missing_actors.py, reembed_gallery.py.
scripts/validation/: X-Ray ground-truth loading and provider-agnostic identity
matching (identity.py's keys_for — an actor is the union of every id we can
derive, since pipeline output and ground truth don't share one id space).
scripts/artifacts/: push/pull scripts for the Gitea generic package registry —
galleries, montage frames, and experiment data (manifests/trajectories/results)
are pushed there instead of committed, since none are needed to run the app,
only benchmarks. Versioned by git short-SHA.
scripts/docs/: MkDocs site build (build_site.sh) and the calibration-curve
comparison chart (calibration_chart.py, matplotlib, reads each gallery's
embedded calibration).
Gallery-building scripts (make_jellyfin_gallery.py, make_gallery.py,
filter_gallery.py, run_from_jellyfin.py, movienet_eval.py, movienet_prep.py,
sae_gallery.py) updated to read/write HDF5 galleries exclusively, matching the
engine-side format switch. run_from_jellyfin.py and the optimizer no longer
carry movie source paths in shared manifests (some source filenames include
scene-release tags) — resolved locally via a gitignored file-lut.json instead.
Add two cameo hunters that flag actors recognised in a title but absent from
its cast:
- cameo_jellyfin.py — pure-Jellyfin cast-membership check (no id cross-walk)
- cameo_hunt.py — TMDB filmography check (actor's combined_credits)
run_from_jellyfin.py now stamps the analysed title's Jellyfin item GUID into
the output JSON as top-level 'jellyfin_item_id' (scene_analyze can't know it),
which cameo_jellyfin.py uses to look up the cast in Jellyfin's own id space.
Document that field in the result-sink output schema header.
dtourolle