"""Tests for Model Manager (F16)."""

import numpy as np

from gps_denied.core.models import ModelManager


def test_load_and_get_model():
    manager = ModelManager()

    # Should auto-load
    engine = manager.get_inference_engine("SuperPoint")
    assert engine.model_name == "SuperPoint"

    # Check fallback/dummy
    assert manager.fallback_to_onnx("SuperPoint") is True
    assert manager.optimize_to_tensorrt("SuperPoint", "path.onnx") == "path.onnx.trt"


def test_mock_superpoint():
    manager = ModelManager()
    engine = manager.get_inference_engine("SuperPoint")

    dummy_img = np.zeros((480, 640, 3), dtype=np.uint8)
    res = engine.infer(dummy_img)

    assert "keypoints" in res
    assert "descriptors" in res
    assert "scores" in res
    assert len(res["keypoints"]) == 500
    assert res["descriptors"].shape == (500, 256)


def test_mock_lightglue():
    manager = ModelManager()
    engine = manager.get_inference_engine("LightGlue")

    # Need mock features
    class DummyF:
        def __init__(self, keypoints):
            self.keypoints = keypoints

    f1 = DummyF(np.random.rand(120, 2))
    f2 = DummyF(np.random.rand(150, 2))

    res = engine.infer({"features1": f1, "features2": f2})

    assert "matches" in res
    assert len(res["matches"]) == 100  # min(100, 120, 150)
    assert res["keypoints1"].shape == (100, 2)
    assert res["keypoints2"].shape == (100, 2)