def METHOD_NAME():
    model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/blazeface_1000e.tgz"
    input_url1 = "https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg"
    result_url1 = "https://bj.bcebos.com/paddlehub/fastdeploy/blazeface_result1.pkl"
    fd.download_and_decompress(model_url, "resources")
    fd.download(input_url1, "resources")
    fd.download(result_url1, "resources")
    model_dir = "resources/blazeface_1000e"
    model_file = os.path.join(model_dir, "model.pdmodel")
    params_file = os.path.join(model_dir, "model.pdiparams")
    config_file = os.path.join(model_dir, "infer_cfg.yml")
    preprocessor = fd.vision.facedet.BlazeFacePreprocessor()
    postprocessor = fd.vision.facedet.BlazeFacePostprocessor()
    rc.test_option.set_model_path(model_file, params_file, config_file, model_format=ModelFormat.PADDLE)
    rc.test_option.use_openvino_backend()
    runtime = fd.Runtime(rc.test_option)
    with open("resources/blazeface_result1.pkl", "rb") as f:
        expect1 = pickle.load(f)
    im1 = cv2.imread("resources/000000014439.jpg")
    for i in range(3):
        # test runtime
        input_tensors, ims_info = preprocessor.run([im1.copy()])
        output_tensors = runtime.infer({"images": input_tensors[0]})
        results = postprocessor.run(output_tensors, ims_info)
        result1 = results[0]
        diff_boxes_1 = np.fabs(
            np.array(result1.boxes) - np.array(expect1["boxes"]))
        diff_scores_1 = np.fabs(
            np.array(result1.scores) - np.array(expect1["scores"]))
        assert diff_boxes_1.max(
        ) < 1e-03, "There's difference in detection boxes 1."
        assert diff_scores_1.max(
        ) < 1e-04, "There's difference in detection score 1."