def METHOD_NAME(
    self, mock_load_labels
):
    mock_cputfl = detectors.api_types[DetectorTypeEnum.cpu]
    TEST_DATA = np.zeros((1, 32, 32, 3), np.uint8)
    TEST_DETECT_RAW = [
        [2, 0.9, 5, 4, 3, 2],
        [1, 0.5, 8, 7, 6, 5],
        [0, 0.4, 2, 4, 8, 16],
    ]
    TEST_DETECT_RESULT = [
        ("label-3", 0.9, (5, 4, 3, 2)),
        ("label-2", 0.5, (8, 7, 6, 5)),
    ]
    TEST_LABEL_FILE = "/test_labels.txt"
    mock_load_labels.return_value = [
        "label-1",
        "label-2",
        "label-3",
        "label-4",
        "label-5",
    ]
    test_cfg = parse_obj_as(DetectorConfig, {"type": "cpu", "model": {}})
    test_cfg.model = ModelConfig()
    test_obj_detect = frigate.object_detection.LocalObjectDetector(
        detector_config=test_cfg,
        labels=TEST_LABEL_FILE,
    )
    mock_load_labels.assert_called_once_with(TEST_LABEL_FILE)
    mock_det_api = mock_cputfl.return_value
    mock_det_api.detect_raw.return_value = TEST_DETECT_RAW
    test_result = test_obj_detect.detect(tensor_input=TEST_DATA, threshold=0.5)
    mock_det_api.detect_raw.assert_called_once()
    assert (
        mock_det_api.detect_raw.call_args.kwargs["tensor_input"].shape
        == np.zeros((1, 32, 32, 3)).shape
    )
    assert test_result == TEST_DETECT_RESULT