Python3与OpenCV3.3 图像处理(十九）--直线检测

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这节课能容不多，基本上是遵循规律编写代码即可

import cv2 as cvimport numpy as npdef line_detection(img):    """方法一"""    gray=cv.cvtColor(img,cv.COLOR_RGB2GRAY)    edges=cv.Canny(gray,50,150,apertureSize=3)    lines=cv.HoughLines(edges,1,np.pi/180,200)    #以下为标准做法    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)        cv.line(img,(x1,y1),(x2,y2),(0,0,255),2)    cv.imshow("img lines",img)def line_detect_possible(img):    """方法二"""    gray = cv.cvtColor(img, cv.COLOR_RGB2GRAY)    edges = cv.Canny(gray, 50, 150, apertureSize=3)    #minLineLength：线段最大长度    #maxLineGap:点和线段之间允许的间隔大小    lines = cv.HoughLinesP(edges, 1, np.pi / 180, 200,minLineLength=50,maxLineGap=10)    for line in lines:        x1,y1,x2,y2=line[0]        cv.line(img, (x1, y1), (x2, y2), (0, 0, 255), 2)    cv.imshow("img lines", img)src=cv.imread('lines.jpg')cv.imshow('def',src)line_detect_possible(src)cv.waitKey(0)cv.destroyAllWindows()

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