import sys
from types import SimpleNamespace
from typing import Any

# The detector only needs NumPy for annotations; keep this unit test independent
# from binary packages and real image/model execution.
_inserted_numpy_stub = "numpy" not in sys.modules
if _inserted_numpy_stub:
    sys.modules["numpy"] = SimpleNamespace(
        ndarray=object,
        isscalar=lambda value: isinstance(value, (int, float)),
    )

from src.config_loader import DetectorSettings
from src.detector import PersonDetector

if _inserted_numpy_stub:
    sys.modules.pop("numpy", None)


class FakeModel:
    def __init__(self) -> None:
        self.kwargs: dict[str, Any] = {}

    def predict(self, **kwargs: Any) -> list[Any]:
        self.kwargs = kwargs
        return []


class FakeFrame:
    shape = (10, 10, 3)


def make_settings(half_precision: bool) -> DetectorSettings:
    return DetectorSettings(
        model_path="unused.pt",
        device="auto",
        confidence_threshold=0.4,
        iou_threshold=0.5,
        image_size=640,
        person_class_id=0,
        max_detections=30,
        half_precision=half_precision,
        use_agnostic_nms=False,
    )


def run_detection(half_precision: bool, effective_half: bool) -> dict[str, Any]:
    detector = PersonDetector(make_settings(half_precision))
    model = FakeModel()
    detector._model = model
    detector._device_name = "cuda" if effective_half else "cpu"
    detector._half = effective_half
    detector.detect(FakeFrame())  # type: ignore[arg-type]
    return model.kwargs


def test_cpu_does_not_pass_half_when_disabled() -> None:
    assert "half" not in run_detection(half_precision=False, effective_half=False)


def test_cpu_does_not_pass_half_when_requested_but_unavailable() -> None:
    assert "half" not in run_detection(half_precision=True, effective_half=False)


def test_cuda_passes_half_only_when_effectively_enabled() -> None:
    kwargs = run_detection(half_precision=True, effective_half=True)
    assert kwargs["half"] is True
    assert "quantize" not in kwargs