move_detect/edge/detectors/zone.py
유창욱 f1ee7f0a36 fix(edge): confidence-gate foot/nose keypoints, warn on MoveNet single-person (P2-9/10/11)
Three keypoint-trust hardening fixes that reuse the codebase's existing
"visible" confidence convention (no new tuning knobs):

- P2-9 zone.py: _foot averaged both ankles unconditionally, so a
  hallucinated ankle (conf~0, often pinned to (0,0)) dragged the foot
  point into or out of a zone. Now averages only ankles with conf >= 0.2
  and falls back to the bbox bottom-centre when neither is trustworthy.

- P2-11 geometry.py: head_below_hips used the NOSE regardless of
  confidence. Now returns False when the nose is below the visibility
  threshold, so an unconfident/hallucinated nose can't fire the
  head-below-hips fall cue. The confident-nose path is unchanged
  (test_fall.py stays green).

- P2-10 movenet_pose.py: the CPU MoveNet fallback is single-person, so at
  a multi-worker site every worker but one is silently invisible to
  fall/zone/ghost detection. Construction now logs a loud startup WARNING
  pointing to the Hailo backend.

Tests: test_zone (bbox fallback), test_geometry (low-conf nose), and
test_movenet_pose (caplog warning). Full python suite: 157 passed, 2
skipped.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019Xmn8KZWqiQUguEMRtn6rW
2026-07-17 10:25:04 +09:00

87 lines
3.4 KiB
Python

from dataclasses import dataclass
from edge.tracking import Track
from edge.models import L_ANKLE, R_ANKLE
# Below this an ankle keypoint is treated as unusable (typically hallucinated at conf~0).
MIN_ANKLE_CONF = 0.2
def point_in_polygon(x: float, y: float, poly: list[tuple[float, float]]) -> bool:
inside = False
n = len(poly)
j = n - 1
for i in range(n):
xi, yi = poly[i]
xj, yj = poly[j]
if ((yi > y) != (yj > y)) and (x < (xj - xi) * (y - yi) / ((yj - yi) or 1e-9) + xi):
inside = not inside
j = i
return inside
@dataclass(frozen=True)
class Zone:
zone_id: str
level: str # "warning" | "restricted"
polygon: list # list[tuple[float,float]]
@dataclass
class ZoneConfig:
debounce_s: float = 0.75
class ZoneIntrusionDetector:
def __init__(self, zones: list[Zone], cfg: ZoneConfig):
self.zones = zones
self.cfg = cfg
self._inside_since: dict[tuple[int, str], float] = {}
self._fired: set[tuple[int, str]] = set()
def forget(self, track_id: int) -> None:
self._inside_since = {k: v for k, v in self._inside_since.items() if k[0] != track_id}
self._fired = {k for k in self._fired if k[0] != track_id}
def _foot(self, track: Track, frame_wh=None) -> tuple[float, float]:
p = track.latest
a, b = p.keypoints[L_ANKLE], p.keypoints[R_ANKLE]
# Average only the ankles the model is confident about. A hallucinated ankle (conf~0,
# often pinned to (0,0) or a frame corner) would otherwise drag the foot point into or
# out of a zone. With neither ankle trustworthy, fall back to the bbox bottom-centre — a
# robust standing-foot proxy (same bbox-fallback discipline as fall.py's cues).
good = [k for k in (a, b) if k.conf >= MIN_ANKLE_CONF]
if good:
fx = sum(k.x for k in good) / len(good)
fy = sum(k.y for k in good) / len(good)
else:
fx, fy = p.bbox.cx, p.bbox.y2
# Zones are stored NORMALIZED (0..1 of the image) by the dashboard, which stretches the
# camera snapshot to a fixed canvas. The foot is camera-native pixels, so normalize it
# by the frame size to compare in the same space — otherwise every zone is misplaced
# (a zone drawn at image-centre would be checked against a raw pixel like 480, matching
# nothing on a 1280-wide frame). frame_wh=None keeps raw coords for unit tests that
# supply their own matching space.
if frame_wh:
w, h = frame_wh
if w > 0 and h > 0:
fx, fy = fx / w, fy / h
return (fx, fy)
def active_zone_ids(self, track_id: int) -> set:
return {z for (tid, z) in self._inside_since if tid == track_id}
def update(self, track: Track, now: float, frame_wh=None) -> list[dict]:
fx, fy = self._foot(track, frame_wh)
out = []
for zone in self.zones:
key = (track.track_id, zone.zone_id)
if point_in_polygon(fx, fy, zone.polygon):
start = self._inside_since.setdefault(key, now)
if now - start >= self.cfg.debounce_s and key not in self._fired:
self._fired.add(key)
out.append({"zone_id": zone.zone_id, "level": zone.level})
else:
self._inside_since.pop(key, None)
self._fired.discard(key)
return out