Same pose stream, new safety axis: musculoskeletal-load prevention. This is an honest 2D reduction of REBA - band exposure TIME, not a precise REBA score. Edge: - geometry: arm_elevation_deg (shoulder->elbow vs vertical-down, best of both arms) and knee_flexion_deg (hip-knee-ankle interior angle, worst of both legs). Both return None when no confident side exists - "unmeasurable" must never read as "0 deg / straight". - detectors/ergonomics.py: per-frame dt accumulation into bands (trunk 20-60 and 60+ deg via the existing torso angle, arm 90+ deg, knee <110 deg), gated on confident core keypoints; detection gaps are dt-capped (2s) so a dropout never counts as exposure. Hourly per-camera report, skipped when nothing was observed (an empty-workshop report is noise). - Engine: tracks in an incident state (FALLING/FALLEN/NO_MOTION) are excluded - a fallen worker's 90-deg trunk is an incident, not an ergonomic exposure. The report event (ergo_report/INFO) carries no track_id and no spatial: a camera-level anonymous aggregate, per the PIPA-first product stance. - run_once: NO snapshots on ergo_report (a frame would turn a statistic into surveillance imagery); capture is skipped entirely when only ergo fired. Server/UI: ergo_report accepted (validator + chk_events_type, edited in the still-undeployed heatmap migration); detail view now renders event metrics with Korean labels and seconds humanized - the ergo report's whole value IS its metrics. Korean type label in list + detail. Verified: pytest 232 pass (10 new) / PHPUnit 135 pass. NOTE: the detail-view visual check is pending - the Chrome extension disconnected mid-verification; harness is staged under the session scratchpad (events/1/view).
161 lines
9.3 KiB
Python
161 lines
9.3 KiB
Python
from dataclasses import dataclass
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from edge.tracking import Track
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from edge.events import Event, EventType, severity_for
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from edge.detectors.fall import FallDetector
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from edge.detectors.immobility import ImmobilityWatchdog
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from edge.detectors.ghost import GhostIncidentDetector
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from edge.detectors.zone import ZoneIntrusionDetector
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from edge.detectors.occupancy import OccupancyWatchdog, OccupancyConfig
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from edge.detectors.ergonomics import ErgoMonitor, ErgoConfig
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@dataclass
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class EngineConfig:
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camera_id: str = "cam"
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cooldown_s: float = 30.0
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_OCCUPANCY_TYPES = {"lone_worker": EventType.LONE_WORKER,
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"overcapacity": EventType.OVERCAPACITY,
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"overstay": EventType.OVERSTAY}
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class EventEngine:
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def __init__(self, fall: FallDetector, immobility: ImmobilityWatchdog,
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ghost: GhostIncidentDetector, zone: ZoneIntrusionDetector,
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cfg: EngineConfig, occupancy: OccupancyWatchdog | None = None,
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ergonomics: ErgoMonitor | None = None):
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self.fall = fall
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self.immobility = immobility
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self.ghost = ghost
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self.zone = zone
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# Keyword-with-default so the existing 5-arg constructors (runtime, tests) keep working.
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self.occupancy = occupancy if occupancy is not None else OccupancyWatchdog(OccupancyConfig())
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self.ergonomics = ergonomics if ergonomics is not None else ErgoMonitor(ErgoConfig())
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self.cfg = cfg
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self._last_emit: dict[tuple, float] = {}
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def _allow(self, key: tuple, now: float) -> bool:
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last = self._last_emit.get(key)
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if last is not None and now - last < self.cfg.cooldown_s:
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return False
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self._last_emit[key] = now
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return True
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def forget(self, track_id: int) -> None:
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"""트랙 소실 시 하위 감지기 + dedup 캐시의 트랙별 상태를 정리 (24/7 장치 메모리 누수 방지)."""
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self.fall.forget(track_id)
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self.immobility.forget(track_id)
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self.zone.forget(track_id)
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self.occupancy.forget(track_id)
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self._last_emit = {k: v for k, v in self._last_emit.items()
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if not (len(k) >= 2 and k[1] == track_id)}
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def _mk(self, etype: EventType, occurred_at: float, track_id=None, zone_id=None,
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metrics=None, spatial=None) -> Event:
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m = metrics or {}
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duration_s = m.get("immobility_s") or m.get("waited_s") or m.get("dwell_s") \
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or m.get("alone_s") or 0.0
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return Event(etype, severity_for(etype), self.cfg.camera_id, track_id,
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zone_id, occurred_at, duration_s, m, spatial)
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def process(self, active_tracks: list[Track], lost_tracks: list[Track],
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now: float, frame_wh=None, wall_now: float | None = None) -> list[Event]:
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# `now` is a MONOTONIC clock (never jumps): it drives every detector timer, hysteresis,
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# and cooldown, so an NTP step cannot instantly satisfy immobile_s / expire all tracks /
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# reset a genuine immobility countdown. `wall_now` is real wall-clock time, used ONLY to
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# stamp Event.occurred_at (the server correlates and retains by wall time). Defaults to
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# `now` so single-clock callers (unit tests) keep their existing occurred_at behavior.
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occurred_at = wall_now if wall_now is not None else now
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events: list[Event] = []
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self.ghost.on_lost(lost_tracks, now)
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for tr in active_tracks:
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# frame_wh lets the zone detector normalize the foot to the dashboard's 0..1 zone
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# space (see ZoneIntrusionDetector._foot). run_once supplies the live frame size.
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zone_hits = self.zone.update(tr, now, frame_wh)
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in_zone = bool(self.zone.active_zone_ids(tr.track_id))
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# 발 좌표(0..1)를 트랙 이벤트 전부에 부착 — 서버 히트맵의 원료. 존 감지기가 이미
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# 계산하는 좌표계를 그대로 재사용해 존 폴리곤과 같은 공간에 놓인다.
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foot = self.zone._foot(tr, frame_wh)
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sig, meta = self.fall.update(tr, now)
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state = self.fall._states.get(tr.track_id)
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self.ghost.note_state(tr.track_id, state.name if state else "STANDING")
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# 자세 부담 노출은 사고 상태가 아닌 트랙만 — 쓰러진 사람의 90° 몸통은
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# 인체공학 노출이 아니라 이미 사고로 처리 중인 상태다.
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if state is None or state.name == "STANDING":
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self.ergonomics.update(tr, now)
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if sig == "fall" and self._allow((EventType.FALL, tr.track_id), now):
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events.append(self._mk(EventType.FALL, occurred_at, tr.track_id,
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metrics=meta, spatial=foot))
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elif sig == "no_motion" and self._allow((EventType.NO_MOTION, tr.track_id), now):
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events.append(self._mk(EventType.NO_MOTION, occurred_at, tr.track_id,
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metrics=meta, spatial=foot))
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elif sig == "near_fall" and self._allow((EventType.NEAR_FALL, tr.track_id), now):
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# 니어미스(FALLING까지 갔다 확정 전 회복): 알람용이 아니라 히트맵/통계 재료.
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events.append(self._mk(EventType.NEAR_FALL, occurred_at, tr.track_id,
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metrics=meta, spatial=foot))
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fired, imeta = self.immobility.update(tr, now, in_danger_zone=in_zone)
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if fired and self._allow((EventType.IMMOBILITY, tr.track_id), now):
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events.append(self._mk(EventType.IMMOBILITY, occurred_at, tr.track_id,
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metrics=imeta, spatial=foot))
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for hit in zone_hits:
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# 협착(pinch) is the highest-danger zone (machinery entrapment) and must emit
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# PINCH/HIGH — the old `restricted else WARNING` silently downgraded it. The
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# dashboard offers exactly these three levels (see zones.php).
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etype = {"pinch": EventType.PINCH,
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"restricted": EventType.ZONE_RESTRICTED}.get(
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hit["level"], EventType.ZONE_WARNING)
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if self._allow((etype, tr.track_id, hit["zone_id"]), now):
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events.append(self._mk(etype, occurred_at, tr.track_id,
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zone_id=hit["zone_id"], spatial=foot))
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# 존 규칙(2인 1조 · 정원 · 체류): 위 per-track 루프에서 zone.update가 갱신한 멤버십을
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# 존별 인원으로 뒤집어 감시자에 넘긴다. stale 트랙은 run_once가 이미 걸러냈으므로
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# 여기 인원수는 이번 틱에 실제로 검출된 사람만 센다.
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zone_tracks: dict[str, set[int]] = {}
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for tr in active_tracks:
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for zid in self.zone.active_zone_ids(tr.track_id):
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zone_tracks.setdefault(zid, set()).add(tr.track_id)
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for o in self.occupancy.update(self.zone.zones, zone_tracks, now):
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etype = _OCCUPANCY_TYPES[o["kind"]]
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# 쿨다운 키에 zone_id 포함: 존 A의 위반이 존 B의 발보를 막지 않는다. track_id가
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# None인 존 단위 이벤트의 키는 forget()이 지우지 못하지만, 존 수에 비례하는
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# 소량이라 누수로 보지 않는다 (ghost와 달리 키 공간이 유한).
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if self._allow((etype, o["track_id"], o["zone_id"]), now):
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events.append(self._mk(etype, occurred_at, track_id=o["track_id"],
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zone_id=o["zone_id"], metrics=o["metrics"]))
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# 자세 부담 주기 리포트 — 간격이 자체 게이트라 쿨다운(_allow)을 타지 않는다.
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# 카메라 단위 익명 합계: track_id·spatial 없음 (개인 좌표를 남기지 않는다).
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ergo = self.ergonomics.report(now)
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if ergo is not None:
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events.append(self._mk(EventType.ERGO_REPORT, occurred_at, metrics=ergo))
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for g in self.ghost.update(active_tracks, now):
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# No _allow cooldown for GHOST: ghost.update pops each incident from its candidates as it
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# emits, and track ids are never reused, so a given track fires GHOST at most once ever.
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# Routing it through _allow would only insert a permanent (GHOST, track_id) dedup key for
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# a track that was already forgotten reappear_s ago — a slow 24/7 memory leak that
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# forget() can never reclaim (the track never appears in lost_tracks again).
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# Ghost's loss point is camera-native pixels (bbox centre at loss time). Normalize to
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# the same 0..1 space every other event's spatial uses so the heatmap can overlay them;
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# frame_wh=None (unit tests) keeps raw coords, matching the zone detector's convention.
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gs = g["spatial"]
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if frame_wh and gs is not None:
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w, h = frame_wh
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if w > 0 and h > 0:
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gs = (gs[0] / w, gs[1] / h)
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events.append(self._mk(EventType.GHOST, occurred_at, track_id=g["track_id"],
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spatial=gs,
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metrics={"last_state": g["last_state"],
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"waited_s": g["waited_s"]}))
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# ghost.on_lost already consumed lost tracks' state above, so forgetting here is safe.
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for tr in lost_tracks:
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self.forget(tr.track_id)
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return events
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