feat: add OBB rectangle visualization to 2D Canvas demo - #12
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Design spec for adding OBB estimation results to the 2D Canvas demo: - LocalTracker (Hungarian matching + ExponentialSmoother per track) - _match_clusters_to_estimates (linear_sum_assignment, gate 6.0m) - _obb_to_dict JSON schema (cx, cy, theta, l, w, corners) - Updated frame snapshot schema with clusters + obb fields - Canvas 8-layer drawing order and legend spec - 6 test cases for OBB structure validation https://claude.ai/code/session_013sQREGvTmjgFT8cyRNmPUL
Implements docs/design/rectangle_visualization.md:
- interactive.py:
- LocalTracker: Hungarian-based frame-to-frame ID management with
per-track ExponentialSmoother (gate 5.0m, alpha 0.4)
- _match_clusters_to_estimates(): linear_sum_assignment centroid
matching with 6.0m gate
- _obb_to_dict(): OBBResult → JSON-serializable dict (cx, cy, theta,
l, w, corners)
- run_once() record_frames=True path now includes clusters and obb
in each frame snapshot
- demo.html:
- Cluster-colored point rendering (6-color palette, falls back to
yellow when no cluster data)
- drawOBB() draws fitted OBB as orange rectangle using corner coords
- Updated legend with OBB entry
- test_interactive.py:
- TestOBBFrameSnapshot with 6 tests covering clusters structure,
obb key presence, 4-corner constraint, positive dimensions,
centre proximity, and missed-frame null guarantee
https://claude.ai/code/session_013sQREGvTmjgFT8cyRNmPUL
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実装したもの（設計書 docs/design/rectangle_visualization.md に準拠）:
src/tracking/evaluation/interactive.py
LocalTracker クラス: ハンガリアン法でフレーム間トラック ID を管理し、ExponentialSmoother (alpha=0.4) で OBB をスムージング
_match_clusters_to_estimates(): セントロイド距離の linear_sum_assignment（ゲート 6.0 m）
_obb_to_dict(): OBBResult → {"cx","cy","theta","l","w","corners"} dict
run_once(record_frames=True) パスで clusters・obb をスナップショットに記録
docs/demo.html
クラスタ点群の色分け描画（6色パレット、データなし時は黄色にフォールバック）
drawOBB() で推定 OBB を橙色矩形として描画（コーナー座標を直接使用）
凡例に OBB エントリを追加
tests/tracking/test_interactive.py
TestOBBFrameSnapshot クラスに設計書指定の 6 テストを追加（全 41 件パス）