问如何用Python OpenCV和Hough Lines确定箭图中抖动的方向？

EN

import cv2
import numpy as np
from numpy import mean
import matplotlib.pyplot as plt


def get_hough_lines(img, name):
    try:
        inputImageGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        edges = cv2.Canny(inputImageGray, 150, 200, apertureSize=3)
        minLineLength = 30
        maxLineGap = 1
        dtype = [('x1', float), ('y1', float), ('x2', float), ('y2', float)]
        lines = cv2.HoughLinesP(edges, cv2.HOUGH_PROBABILISTIC, np.pi / 180, 30, minLineLength, maxLineGap)
        a = np.array(lines, dtype=dtype)
        np.sort(a, order='x1')
        x_s = []
        y_s = []
        x_flow = [i[0][2] - i[0][0] for i in lines]
        y_flow = [i[0][3] - i[0][1] for i in lines]
        plt.plot([i for i in range(len(x_flow))], x_flow, 'o', color='black')
        plt.savefig("debug.png", bbox_inches='tight', pad_inches=0)
        # [np.sqrt(np.square(i[2] - i[0]) + np.square(i[3] - i[1])) for i in a]
        for x in range(0, len(lines)):
            for x1, y1, x2, y2 in lines[x]:
                # cv2.line(inputImage,(x1,y1),(x2,y2),(0,128,0),2, cv2.LINE_AA)
                pts = np.array([[x1, y1], [x2, y2]], np.int32)
                cv2.polylines(img, [pts], True, (0, 255, 0))
                x_s.append(x2 - x1)
                y_s.append(y2 - y1)

        average_direction = [mean(x_s), mean(y_s)]

        font = cv2.FONT_HERSHEY_SIMPLEX

        cv2.imwrite(f"TEST_{name}_hough_direction_right_{average_direction[0]}_up__{average_direction[1]}.jpg", img)
    except TypeError as e:
        print('could not parse hough lines')
    except Exception as e:
        print('could not parse hough lines')