32f2237db7
- P2-6 tracking: global greedy IoU matching (all pairs, best overlap first) replaces track-iteration-order greedy, so a crossing worker's box can no longer be stolen by whichever track came first. Any track in a contended match (person overlapping 2 tracks, or track overlapping 2 persons) is reported via tracker.ambiguous(); run_once resets its detector + smoother state so FALLEN/baseline/immobility never ride an id swap onto the wrong person. A genuinely fallen worker re-confirms within prone_confirm_s. - P2-7 fall: STANDING -> FALLING now requires sustained prone (falling_confirm_s, 1.0s). One prone-looking frame (a bend, a bbox glitch) no longer arms the ghost detector's CRITICAL if the person then leaves. FALLEN / no_motion timing is unchanged (keyed off prone_since). - P2-8 app: run_once feeds the engine and smoothers only tracks re-detected this tick; a track coasting inside max_age with a frozen frame is no-data, so prone-confirm / no-motion / immobility timers cannot accrue on stale data. Re-detection still confirms the fall (dropout pauses evidence). TDD: 7 new tests verified failing on the pre-fix code (git stash), then 203 passed / 2 skipped (hardware) with the fixes.
88 lines
3.9 KiB
Python
88 lines
3.9 KiB
Python
from edge.config import Config
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from edge.tracking import IouTracker
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from edge.smoothing import TrackSmootherPool
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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.engine import EventEngine
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from edge.snapshot import RingBuffer, FaceBlurrer, Snapshotter
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from edge.models import BBox
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def _head_boxes(persons: list) -> list:
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# Head region for face anonymization (PIPA). Sized from the PERSON bbox, not a fixed
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# ~40x40 patch — a close worker fills far more than 40px, so a constant box left the face
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# fully identifiable. Centered on the nose when it is confident, else on the bbox's top
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# (the head is the upper part of the person) so a bad keypoint can't move the blur off it.
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boxes = []
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for p in persons:
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bb = p.bbox
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nose = p.keypoints[0]
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half_w = max(8.0, 0.25 * bb.width)
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if nose.conf >= 0.3:
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cx, cy = nose.x, nose.y
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else:
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cx, cy = bb.cx, bb.y1 + 0.12 * bb.height
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boxes.append(BBox(cx - half_w, cy - 0.18 * bb.height,
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cx + half_w, cy + 0.08 * bb.height))
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return boxes
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def run_once(source, pose, tracker, pool, engine, ring, snapshotter, sink, now_fn, wall_fn=None):
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ok, frame = source.read()
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if not ok:
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# No frame this tick. Return None (not []) so the daemon can tell "camera produced no
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# frame" apart from "frame processed, no events" — a dead/unplugged USB camera returns
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# (False, None) forever, and counting it as a healthy frame made a monitoring outage
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# look perfectly green (fps~=target, cameras_erroring=0).
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return None
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now = now_fn()
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persons = pose.infer(frame)
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tracks = tracker.update(persons, now) # RAW keypoints; smoothing happens per-track below
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lost = tracker.lost()
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# A contended (crossing) match may be an id swap — FALLEN state, frozen baseline, or an
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# immobility timer would ride along to the wrong person. Reset that track's safety state;
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# a genuinely fallen worker still prone re-confirms within prone_confirm_s.
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for tid in tracker.ambiguous():
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engine.forget(tid)
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pool.forget(tid)
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# A track not re-detected this tick still sits in the tracker (< max_age) with a frozen
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# latest frame. Feeding it downstream would re-smooth the same frame and let time-based
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# detector timers (prone confirm / no-motion / immobility) accrue on stale data — treat
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# it as no-data until it is re-detected or ages into lost().
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fresh = [tr for tr in tracks if tr.latest.t == now]
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for tr in fresh:
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f = tr.latest
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f.keypoints = pool.smoother_for(tr.track_id).smooth(f.keypoints, now)
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ring.push(now, frame)
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h, w = frame.shape[:2]
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# `now` (monotonic) drives detector timers; wall time stamps the event (occurred_at). Off the
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# daemon (direct callers / tests) wall_fn is None → engine falls back to now, as before.
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wall_now = wall_fn() if wall_fn is not None else None
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events = engine.process(fresh, lost, now, frame_wh=(w, h), wall_now=wall_now)
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for tr in lost:
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pool.forget(tr.track_id)
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if events:
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snaps = snapshotter.capture([frame], [_head_boxes(persons)])
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for e in events:
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sink.try_send(e, snaps)
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return events
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def build_pipeline(config: Config, source, pose) -> dict:
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return {
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"source": source,
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"pose": pose,
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"tracker": IouTracker(),
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"pool": TrackSmootherPool(),
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"engine": EventEngine(
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FallDetector(config.fall),
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ImmobilityWatchdog(config.immobility),
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GhostIncidentDetector(config.ghost),
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ZoneIntrusionDetector([], config.zone),
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config.engine,
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),
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"ring": RingBuffer(),
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"snapshotter": Snapshotter(FaceBlurrer()),
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}
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