直线检测

霍夫直线变换

百度百科
前提条件：边缘检测已经完成
平面空间→极坐标

相关代码

import cv2 as cv
import numpy as np


def line_detection(image):
    """ 自己写 :param image: :return: """
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    # apertureSize 梯度窗口大小
    edges = cv.Canny(gray, 50, 150, apertureSize=3)
    # 获取直线 参数: 边缘 半径步长 偏转1° 低值
    lines = cv.HoughLines(edges, 1, np.pi / 180, 200)
    for line in lines:
        # print(type(lines)) 查看类型
        rho, theta = line[0]
        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)
        # 参数:待绘图对象 起点 终点 颜色 灰度宽度
        cv.line(image, (x1, y1), (x2, y2), (0, 0, 255), 2)
    cv.imshow("image-lines", image)


def line_detect_possible_demo(image):
    """ 使用api直接获取 :param image: :return: """
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    edges = cv.Canny(gray, 50, 150, apertureSize=3)
    # minLineLength 最小的线长; maxLineGap 最大的线直接的间隔
    lines = cv.HoughLinesP(edges, 1, np.pi / 180, 100, minLineLength=50, maxLineGap=10)
    for line in lines:
        # print(type(line)) 查看类型
        # 获取起点和终点
        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("main.png")
cv.namedWindow("input image", cv.WINDOW_AUTOSIZE)
cv.imshow("input image", src)
line_detection(src)
line_detect_possible_demo(src)
cv.waitKey(0)

cv.destroyAllWindows()

效果展示