move_detect/edge/engine.py
유창욱 b358822247 feat(ergo): posture-load exposure scoring (REBA bands) with anonymous reports
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).
2026-08-06 21:46:39 +09:00

161 lines
9.3 KiB
Python

from dataclasses import dataclass
from edge.tracking import Track
from edge.events import Event, EventType, severity_for
from edge.detectors.fall import FallDetector
from edge.detectors.immobility import ImmobilityWatchdog
from edge.detectors.ghost import GhostIncidentDetector
from edge.detectors.zone import ZoneIntrusionDetector
from edge.detectors.occupancy import OccupancyWatchdog, OccupancyConfig
from edge.detectors.ergonomics import ErgoMonitor, ErgoConfig
@dataclass
class EngineConfig:
camera_id: str = "cam"
cooldown_s: float = 30.0
_OCCUPANCY_TYPES = {"lone_worker": EventType.LONE_WORKER,
"overcapacity": EventType.OVERCAPACITY,
"overstay": EventType.OVERSTAY}
class EventEngine:
def __init__(self, fall: FallDetector, immobility: ImmobilityWatchdog,
ghost: GhostIncidentDetector, zone: ZoneIntrusionDetector,
cfg: EngineConfig, occupancy: OccupancyWatchdog | None = None,
ergonomics: ErgoMonitor | None = None):
self.fall = fall
self.immobility = immobility
self.ghost = ghost
self.zone = zone
# Keyword-with-default so the existing 5-arg constructors (runtime, tests) keep working.
self.occupancy = occupancy if occupancy is not None else OccupancyWatchdog(OccupancyConfig())
self.ergonomics = ergonomics if ergonomics is not None else ErgoMonitor(ErgoConfig())
self.cfg = cfg
self._last_emit: dict[tuple, float] = {}
def _allow(self, key: tuple, now: float) -> bool:
last = self._last_emit.get(key)
if last is not None and now - last < self.cfg.cooldown_s:
return False
self._last_emit[key] = now
return True
def forget(self, track_id: int) -> None:
"""트랙 소실 시 하위 감지기 + dedup 캐시의 트랙별 상태를 정리 (24/7 장치 메모리 누수 방지)."""
self.fall.forget(track_id)
self.immobility.forget(track_id)
self.zone.forget(track_id)
self.occupancy.forget(track_id)
self._last_emit = {k: v for k, v in self._last_emit.items()
if not (len(k) >= 2 and k[1] == track_id)}
def _mk(self, etype: EventType, occurred_at: float, track_id=None, zone_id=None,
metrics=None, spatial=None) -> Event:
m = metrics or {}
duration_s = m.get("immobility_s") or m.get("waited_s") or m.get("dwell_s") \
or m.get("alone_s") or 0.0
return Event(etype, severity_for(etype), self.cfg.camera_id, track_id,
zone_id, occurred_at, duration_s, m, spatial)
def process(self, active_tracks: list[Track], lost_tracks: list[Track],
now: float, frame_wh=None, wall_now: float | None = None) -> list[Event]:
# `now` is a MONOTONIC clock (never jumps): it drives every detector timer, hysteresis,
# and cooldown, so an NTP step cannot instantly satisfy immobile_s / expire all tracks /
# reset a genuine immobility countdown. `wall_now` is real wall-clock time, used ONLY to
# stamp Event.occurred_at (the server correlates and retains by wall time). Defaults to
# `now` so single-clock callers (unit tests) keep their existing occurred_at behavior.
occurred_at = wall_now if wall_now is not None else now
events: list[Event] = []
self.ghost.on_lost(lost_tracks, now)
for tr in active_tracks:
# frame_wh lets the zone detector normalize the foot to the dashboard's 0..1 zone
# space (see ZoneIntrusionDetector._foot). run_once supplies the live frame size.
zone_hits = self.zone.update(tr, now, frame_wh)
in_zone = bool(self.zone.active_zone_ids(tr.track_id))
# 발 좌표(0..1)를 트랙 이벤트 전부에 부착 — 서버 히트맵의 원료. 존 감지기가 이미
# 계산하는 좌표계를 그대로 재사용해 존 폴리곤과 같은 공간에 놓인다.
foot = self.zone._foot(tr, frame_wh)
sig, meta = self.fall.update(tr, now)
state = self.fall._states.get(tr.track_id)
self.ghost.note_state(tr.track_id, state.name if state else "STANDING")
# 자세 부담 노출은 사고 상태가 아닌 트랙만 — 쓰러진 사람의 90° 몸통은
# 인체공학 노출이 아니라 이미 사고로 처리 중인 상태다.
if state is None or state.name == "STANDING":
self.ergonomics.update(tr, now)
if sig == "fall" and self._allow((EventType.FALL, tr.track_id), now):
events.append(self._mk(EventType.FALL, occurred_at, tr.track_id,
metrics=meta, spatial=foot))
elif sig == "no_motion" and self._allow((EventType.NO_MOTION, tr.track_id), now):
events.append(self._mk(EventType.NO_MOTION, occurred_at, tr.track_id,
metrics=meta, spatial=foot))
elif sig == "near_fall" and self._allow((EventType.NEAR_FALL, tr.track_id), now):
# 니어미스(FALLING까지 갔다 확정 전 회복): 알람용이 아니라 히트맵/통계 재료.
events.append(self._mk(EventType.NEAR_FALL, occurred_at, tr.track_id,
metrics=meta, spatial=foot))
fired, imeta = self.immobility.update(tr, now, in_danger_zone=in_zone)
if fired and self._allow((EventType.IMMOBILITY, tr.track_id), now):
events.append(self._mk(EventType.IMMOBILITY, occurred_at, tr.track_id,
metrics=imeta, spatial=foot))
for hit in zone_hits:
# 협착(pinch) is the highest-danger zone (machinery entrapment) and must emit
# PINCH/HIGH — the old `restricted else WARNING` silently downgraded it. The
# dashboard offers exactly these three levels (see zones.php).
etype = {"pinch": EventType.PINCH,
"restricted": EventType.ZONE_RESTRICTED}.get(
hit["level"], EventType.ZONE_WARNING)
if self._allow((etype, tr.track_id, hit["zone_id"]), now):
events.append(self._mk(etype, occurred_at, tr.track_id,
zone_id=hit["zone_id"], spatial=foot))
# 존 규칙(2인 1조 · 정원 · 체류): 위 per-track 루프에서 zone.update가 갱신한 멤버십을
# 존별 인원으로 뒤집어 감시자에 넘긴다. stale 트랙은 run_once가 이미 걸러냈으므로
# 여기 인원수는 이번 틱에 실제로 검출된 사람만 센다.
zone_tracks: dict[str, set[int]] = {}
for tr in active_tracks:
for zid in self.zone.active_zone_ids(tr.track_id):
zone_tracks.setdefault(zid, set()).add(tr.track_id)
for o in self.occupancy.update(self.zone.zones, zone_tracks, now):
etype = _OCCUPANCY_TYPES[o["kind"]]
# 쿨다운 키에 zone_id 포함: 존 A의 위반이 존 B의 발보를 막지 않는다. track_id가
# None인 존 단위 이벤트의 키는 forget()이 지우지 못하지만, 존 수에 비례하는
# 소량이라 누수로 보지 않는다 (ghost와 달리 키 공간이 유한).
if self._allow((etype, o["track_id"], o["zone_id"]), now):
events.append(self._mk(etype, occurred_at, track_id=o["track_id"],
zone_id=o["zone_id"], metrics=o["metrics"]))
# 자세 부담 주기 리포트 — 간격이 자체 게이트라 쿨다운(_allow)을 타지 않는다.
# 카메라 단위 익명 합계: track_id·spatial 없음 (개인 좌표를 남기지 않는다).
ergo = self.ergonomics.report(now)
if ergo is not None:
events.append(self._mk(EventType.ERGO_REPORT, occurred_at, metrics=ergo))
for g in self.ghost.update(active_tracks, now):
# No _allow cooldown for GHOST: ghost.update pops each incident from its candidates as it
# emits, and track ids are never reused, so a given track fires GHOST at most once ever.
# Routing it through _allow would only insert a permanent (GHOST, track_id) dedup key for
# a track that was already forgotten reappear_s ago — a slow 24/7 memory leak that
# forget() can never reclaim (the track never appears in lost_tracks again).
# Ghost's loss point is camera-native pixels (bbox centre at loss time). Normalize to
# the same 0..1 space every other event's spatial uses so the heatmap can overlay them;
# frame_wh=None (unit tests) keeps raw coords, matching the zone detector's convention.
gs = g["spatial"]
if frame_wh and gs is not None:
w, h = frame_wh
if w > 0 and h > 0:
gs = (gs[0] / w, gs[1] / h)
events.append(self._mk(EventType.GHOST, occurred_at, track_id=g["track_id"],
spatial=gs,
metrics={"last_state": g["last_state"],
"waited_s": g["waited_s"]}))
# ghost.on_lost already consumed lost tracks' state above, so forgetting here is safe.
for tr in lost_tracks:
self.forget(tr.track_id)
return events