Python3与OpenCV3.3 图像处理(十九）--直线检测

 

这节课能容不多，基本上是遵循规律编写代码即可

 

 

import cv2 as cv
import numpy as np

def 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]