OpenCV | 霍夫变换检测直线

上次写的不好，这次重写一个霍夫变化的框架，里面包括灰度转换、滤波

canny边缘检测、霍夫变换等......

原始图像

import cv2
import numpy as np
import matplotlib.pyplot as plt#Matplotlib是RGB
%matplotlib inline 

def detect_parking_lines(image_path):
    # 读取图像
    img = cv2.imread(image_path)

    # 灰度转换
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # 高斯滤波
    gray = cv2.GaussianBlur(gray, (5, 5), 0)

    # Canny 边缘检测
    edges = cv2.Canny(gray, 50, 150)

    # Hough 变换检测直线
    lines = cv2.HoughLines(edges, 1, np.pi / 180, 130)

    # 绘制检测到的直线
    if lines is not None:
        for line in lines:
            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))
            cv2.line(img, (x1, y1), (x2, y2), (0, 255, 0), 2)

    # 显示结果
    cv2.imshow('Detected Parking Lines', img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

# 调用函数进行车位线检测
detect_parking_lines('chessboard.jpg')

识别后图像：