hough空間(離散極座標)的表示
原因：
影象中直線的表示，由斜率和截距表示，而極座標中用(r, theta)表示.
r = cos(theta)*x + sin(theta)*y

##測直線cv.HoughLines演算法不夠完善需要程式碼補充  ，cv.HoughLinesP則演算法補充
import cv2 as cv
import numpy as np

def line_detection(image):
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    edges = cv.Canny(gray, 50, 150, apertureSize=3)
    lines = cv.HoughLines(edges, 1, np.pi/180, 200)
    for line in lines:
        print(type(lines))
        rho, theta = line[0]            #rho極徑引數的距離解析度    theta極角引數的角度解析度
        a = np.cos(theta)
        b = np.sin(theta)
        x0 = a * rho
        y0 = b * rho
        x1 = int(x0+1000*(-b))
        y1 = int(y0+1000*(a))
        x2 = int(x0-1000*(-b))
        y2 = int(y0-1000*(a))
        cv.line(image, (x1, y1), (x2, y2), (0, 0, 255), 2)
    cv.imshow("image-lines", image)

def line_detect_possible_demo(image):
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    edges = cv.Canny(gray, 50, 150, apertureSize=3)
    lines = cv.HoughLinesP(edges, 1, np.pi/180, 100, minLineLength=50, maxLineGap=10)
    for line in lines:
        print(type(line))
        x1, y1, x2, y2 = line[0]
        cv.line(image, (x1, y1), (x2, y2), (0, 0, 255), 2)
    cv.imshow("line_detect_possible_demo", image)

src = cv.imread("C:/Users/weiqiangwen/Desktop/sest/morph01.png")
# cv.namedWindow("input contours",cv.WINDOW_AUTOSIZE)
cv.imshow("contours", src)
line_detection(src)
line_detect_possible_demo(src)
cv.waitKey(0)

cv.destroyAllWindows()
print("--------- Python OpenCV Tutorial ---------")