python|python实现opencv学习十七（hough变换检测直线）图像处理|opencv

HoughLines
代码：

# -*- coding=GBK -*- import cv2 as cv import numpy as np# hough变换检测直线与圆：https://blog.csdn.net/on2way/article/details/47028969 def line_image(image): gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY) edges = cv.Canny(gray, 50, 150, apertureSize=3) # 第四个输入参数是Sobel算子的大小，3的话就是3*3 cv.imshow("edges", edges) lines = cv.HoughLines(edges, 1, np.pi / 180, 200) # 霍夫变换进行形状检测 # cv.HoughLines(edges, rho, theta, threshold) # img 为输入的图像，Canny提取后的边界数据; rho/ρ为距离精确度（理解为距离单位）; theta/θ为角度精确度（理解为角度单位单位）; threshold 为累加器阈值,当累加器中的值高于threshold时才认为是一条直线 # 返回值每段直线(ρ,θ)的的二维矩阵 for line in lines: rho, theta = line[0] a = np.cos(theta) # np.cos是便于计算数组所有theta的cos值，sin同理，而且三角函数是np库里面的 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) # 输入参数： img，起始点，终，颜色，宽度 cv.imshow("line", image)src = https://www.it610.com/article/cv.imread("Line.png") cv.imshow("before", src) line_image(src) cv.waitKey(0) cv.destroyAllWindows()

结果：

文章图片

备注：

文章图片

hough变换检测直线与圆参考资料：https://blog.csdn.net/on2way/article/details/47028969

HoughLinesP
代码：

# -*- coding=GBK -*- import cv2 as cv import numpy as npdef line_image(image): gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY) # 灰度图像 edges = cv.Canny(gray, 50, 200) lines = cv.HoughLinesP(edges, 1, np.pi/180, 30, minLineLength=60, maxLineGap=10) lines1 = lines[:, 0, :]# 提取为二维for x1, y1, x2, y2 in lines1[:]: cv.line(image, (x1, y1), (x2, y2), (255, 0, 0), 1) cv.imshow("line", image)src = https://www.it610.com/article/cv.imread("Line.png") cv.imshow("before", src) line_image(src) cv.waitKey(0) cv.destroyAllWindows()

结果：