56e569fd7a
Markers/badges -> detection -> cross-view triangulation -> track ribbons + follow-a-friend + LED badge hardware kit. Coordinator-merges policy this phase. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2.3 KiB
2.3 KiB
Lane H — Tracker (M19 detection, M20 solving)
You turn wearable markers in the videos into 3D friend tracks. Backend only.
Spec: 30-phase6.md M19/M20 + contracts #1–#5. Branch lane/h-tracker, own worktree.
What foundation3 gives you
- Stubs
tracker_detect.py/tracker_solve.pywith the contracts in their docstrings; API (POST /api/tracks/solveetc.), CLI (track), DB helpers, and the synthetic fixture's two moving markers +data/work/track_truth.jsonground truth — all already wired. - You fill the two stub bodies and write the two test files. Nothing else.
M19 — detection, the parts that bite
- Sample frames with the
frames.pymachinery (~8 fps is plenty; document your rate). - Color mode: convert to HSV, gate on saturation AND value before hue (pitfall #2);
connected components; centroid → normalized cx/cy. Hue buckets from contract #1 +
FESTIVAL4D_MARKER_HUES. - Blink mode: track candidate bright blobs across the sampled window, integrate brightness
per 133 ms bit window using the video's real fps (pitfall #3), correlate against the
preamble, check parity, emit
code:<id>. - Empty/dark/markerless video → valid-empty detections. Never crash.
M20 — solving, the parts that bite
t_video → t_globalthrough the frozen helpers ONLY (pitfall #1).- Triangulation through
geometryprimitives exactly asresolve.pydoes — read it first. - Bucket ≈0.25 s; 2+ cameras → triangulate (record
views,qualityfrom residual); 1 camera → ray ∩ ground plane per contract #5 (views=1,quality ≤ 0.5). - Smooth per track; write through
dbhelpers; re-solve replaces that marker's tracks (idempotent — don't stack duplicates on every run).
Acceptance (evidence in plan/status/lane-H.md)
- Detection: ≥90 % recall on visible synthetic markers, ≤0.008 normalized center error;
blink ID 5 decoded (
test_tracker_detect.py) - Solve: median 3D error < 0.3 vs
track_truth.json, ≥80 % coverage; single-view fallback test; idempotent re-solve; degradations (test_tracker_solve.py) - CLI +
POST /api/tracks/solverun detect→solve end-to-end on the fixture - Suite ≥ foundation3's count + yours, green; stub-era assertions superseded by your landing → CR entry (CR-1/-4/-5 pattern)