from collections import deque
from edge.models import Keypoint, BBox
from edge.tracking import Track, TrackFrame
from edge.detectors.zone import point_in_polygon, Zone, ZoneIntrusionDetector, ZoneConfig

SQUARE = [(0, 0), (100, 0), (100, 100), (0, 100)]

def test_point_in_polygon_basic():
    assert point_in_polygon(50, 50, SQUARE) is True
    assert point_in_polygon(150, 50, SQUARE) is False

def _track_with_ankles(ax, ay, t):
    kps = [Keypoint(ax, ay, 0.9) for _ in range(17)]
    kps[15] = Keypoint(ax, ay, 0.9)   # L_ANKLE
    kps[16] = Keypoint(ax, ay, 0.9)   # R_ANKLE
    return Track(1, deque([TrackFrame(t, BBox(ax - 10, ay - 60, ax + 10, ay), kps)], maxlen=90))

def test_intrusion_fires_after_debounce():
    z = Zone("z1", "restricted", SQUARE)
    det = ZoneIntrusionDetector([z], ZoneConfig(debounce_s=0.5))
    tr = _track_with_ankles(50, 50, 0.0)
    assert det.update(tr, now=0.0) == []
    tr = _track_with_ankles(50, 50, 0.6)
    out = det.update(tr, now=0.6)
    assert out == [{"zone_id": "z1", "level": "restricted"}]

def test_leaving_zone_resets():
    z = Zone("z1", "warning", SQUARE)
    det = ZoneIntrusionDetector([z], ZoneConfig(debounce_s=0.5))
    det.update(_track_with_ankles(50, 50, 0.0), now=0.0)
    det.update(_track_with_ankles(200, 200, 0.6), now=0.6)  # 이탈
    out = det.update(_track_with_ankles(50, 50, 1.0), now=1.0)  # 재진입, 디바운스 재시작
    assert out == []


def _track_lowconf_ankles(bbox, t):
    kps = [Keypoint(0, 0, 0.0) for _ in range(17)]  # every keypoint hallucinated at the origin
    return Track(1, deque([TrackFrame(t, bbox, kps)], maxlen=90))

def test_foot_falls_back_to_bbox_when_ankles_low_confidence():
    # Both ankles are hallucinated at (0,0) with conf 0. Averaging them would pin the foot to the
    # image origin — outside any centred zone. The detector must instead use the bbox
    # bottom-centre, where the worker actually stands, so the intrusion still fires.
    z = Zone("z1", "restricted", SQUARE)
    det = ZoneIntrusionDetector([z], ZoneConfig(debounce_s=0.0))
    bbox = BBox(40, 10, 60, 50)  # bottom-centre = (cx=50, y2=50), inside SQUARE
    out = det.update(_track_lowconf_ankles(bbox, 0.0), now=0.0)
    assert out == [{"zone_id": "z1", "level": "restricted"}]


def test_zone_uses_normalized_coordinates_when_frame_size_given():
    # The dashboard stores zones as 0..1 of the image (it stretches the snapshot to a fixed
    # 960x540 canvas). The edge foot is camera-native pixels. Normalizing the foot by the
    # frame size makes the two comparable regardless of camera resolution — without this,
    # every zone is silently misplaced.
    zn = Zone("z1", "restricted", [(0.4, 0.4), (0.6, 0.4), (0.6, 0.6), (0.4, 0.6)])
    det = ZoneIntrusionDetector([zn], ZoneConfig(debounce_s=0.0))
    # foot at the centre of a 1280x720 frame -> (0.5, 0.5) -> inside the 0.4..0.6 zone
    inside = det.update(_track_with_ankles(640, 360, 0.0), now=0.0, frame_wh=(1280, 720))
    assert inside == [{"zone_id": "z1", "level": "restricted"}]
    # foot near the corner -> ~(0.008, 0.014) -> outside
    det2 = ZoneIntrusionDetector([zn], ZoneConfig(debounce_s=0.0))
    assert det2.update(_track_with_ankles(10, 10, 0.0), now=0.0, frame_wh=(1280, 720)) == []