from __future__ import annotations

import pytest

from yovision_brain.decode import DecodedFrame
from yovision_brain.vision import (
    BoundingBox,
    Detection,
    LumaBlobDetector,
    SingleStreamTracker,
    TorchLumaBlobDetector,
)


def frame(payload: bytes, *, sequence: int = 0, width: int = 4, height: int = 3) -> DecodedFrame:
    return DecodedFrame(sequence, sequence * 40_000_000, "camera", "main", width, height, "rgb24", payload)


def rgb(values: list[int]) -> bytes:
    return b"".join(bytes((value, value, value)) for value in values)


def detection(left: int, top: int, right: int, bottom: int) -> Detection:
    return Detection(BoundingBox(left, top, right, bottom), "anonymous_target", 0.9)


def test_detector_emits_only_anonymous_observations() -> None:
    payload = rgb([0, 255, 255, 0, 0, 255, 255, 0, 0, 0, 0, 0])
    result = LumaBlobDetector(minimum_area=2).detect(frame(payload))
    assert result == (Detection(BoundingBox(1, 0, 3, 2), "anonymous_target", 1.0),)
    assert LumaBlobDetector.metadata.weights == "none"
    assert "external model license" in LumaBlobDetector.metadata.license


def test_empty_frame_has_no_detection() -> None:
    assert LumaBlobDetector().detect(frame(rgb([0] * 12))) == ()


def test_tracker_keeps_session_id_across_motion_and_short_occlusion() -> None:
    tracker = SingleStreamTracker(iou_threshold=0.1, max_missed=2)
    first = tracker.update((detection(0, 0, 3, 3),), frame_sequence=0, timestamp_ns=0)
    assert first[0].track_id == "track-000001"
    assert tracker.update((), frame_sequence=1, timestamp_ns=1) == ()
    resumed = tracker.update((detection(1, 0, 4, 3),), frame_sequence=2, timestamp_ns=2)
    assert resumed[0].track_id == "track-000001"
    assert tracker.finish() == ("track-000001",)


def test_disappeared_track_ends_and_new_target_gets_new_id() -> None:
    tracker = SingleStreamTracker(max_missed=1)
    first = tracker.update((detection(0, 0, 2, 2),), frame_sequence=0, timestamp_ns=0)
    tracker.update((), frame_sequence=1, timestamp_ns=1)
    tracker.update((), frame_sequence=2, timestamp_ns=2)
    second = tracker.update((detection(0, 0, 2, 2),), frame_sequence=3, timestamp_ns=3)
    assert first[0].track_id == "track-000001"
    assert second[0].track_id == "track-000002"


def test_track_ids_are_session_local() -> None:
    one = SingleStreamTracker().update((detection(0, 0, 1, 1),), frame_sequence=0, timestamp_ns=0)
    two = SingleStreamTracker().update((detection(0, 0, 1, 1),), frame_sequence=0, timestamp_ns=0)
    assert one[0].track_id == two[0].track_id == "track-000001"


def test_torch_backend_cpu_smoke_uses_no_external_weights() -> None:
    pytest.importorskip("torch")
    result = TorchLumaBlobDetector().detect(frame(rgb([0, 255] + [0] * 10)))
    assert result[0].category == "anonymous_target"
    assert TorchLumaBlobDetector.metadata.weights == "none"