Operator inspected the rich Docker UI tied to our backend and noticed
the dashboard showed a 17-keypoint skeleton even with no DensePose
model loaded. Tracing it: `derive_pose_from_sensing` synthesized
geometric placeholders, `pose_stats.average_confidence` was hard-coded
0.87, `pose_zones_summary` invented zones 2/3/4 as "clear", and
`/api/v1/info.features.pose_estimation` claimed `true` regardless.
All cosmetic noise that hid the real capability gap.
Changes:
* `derive_pose_from_sensing` is now an inert `Vec::new()` stub.
Heuristic logic kept in `derive_single_person_pose` (dead-code-warned
out by the rustc unused-fn lint) for the day someone wires a real
trained pose model in.
* `pose_current` returns persons only when `model_loaded == true`; the
endpoint always includes `model_loaded` so the UI can decide what
to render.
* `pose_stats` drops the fake `average_confidence: 0.87`.
* `pose_zones_summary` reports `zones_configured: 0` and an empty
`zones {}` instead of fabricating four zones.
* `api_info.features.pose_estimation` now mirrors `s.model_loaded`.
Sensing endpoints (`/api/v1/sensing/latest`, `/ws/sensing`) are
unchanged — they always carried real ESP32-derived data per ADR-101.
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