def METHOD_NAME():
    model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/FastestDet.onnx"
    input_url1 = "https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg"
    input_url2 = "https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000570688.jpg"
    result_url1 = "https://bj.bcebos.com/paddlehub/fastdeploy/fastestdet_result1.pkl"
    fd.download(model_url, "resources")
    fd.download(input_url1, "resources")
    fd.download(input_url2, "resources")
    fd.download(result_url1, "resources")
    model_file = "resources/FastestDet.onnx"
    model = fd.vision.detection.FastestDet(
        model_file, runtime_option=rc.test_option)
    with open("resources/fastestdet_result1.pkl", "rb") as f:
        expect1 = pickle.load(f)
    # compare diff
    im1 = cv2.imread("./resources/000000014439.jpg")
    print(expect1)
    for i in range(3):
        # test single predict
        result1 = model.predict(im1)
        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"]))
        print(diff_boxes_1.max(), diff_boxes_1.mean())
        assert diff_boxes_1.max(
        ) < 1e-04, "There's difference in detection boxes 1."
        assert diff_label_1.max(
        ) < 1e-04, "There's difference in detection label 1."
        assert diff_scores_1.max(
        ) < 1e-05, "There's difference in detection score 1."