def METHOD_NAME():
    model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/yolov5s.onnx"
    input_url1 = "https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg"
    result_url1 = "https://bj.bcebos.com/paddlehub/fastdeploy/yolov5_result1.pkl"
    fd.download(model_url, "resources")
    fd.download(input_url1, "resources")
    fd.download(result_url1, "resources")
    model_file = "resources/yolov5s.onnx"
    preprocessor = fd.vision.detection.YOLOv5Preprocessor()
    postprocessor = fd.vision.detection.YOLOv5Postprocessor()
    rc.test_option.set_model_path(model_file, model_format=ModelFormat.ONNX)
    rc.test_option.use_openvino_backend()
    runtime = fd.Runtime(rc.test_option)
    with open("resources/yolov5_result1.pkl", "rb") as f:
        expect1 = pickle.load(f)
    # compare diff
    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_label_1 = np.fabs(
            np.array(result1.label_ids) - np.array(expect1["label_ids"]))
        diff_scores_1 = np.fabs(
            np.array(result1.scores) - np.array(expect1["scores"]))
        assert diff_boxes_1.max(
        ) < 1e-04, "There's difference in detection boxes 1."
        assert diff_label_1.max(
        ) < 1e-06, "There's difference in detection label 1."
        assert diff_scores_1.max(
        ) < 1e-05, "There's difference in detection score 1."