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]
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()
觉得不错打赏一下 | |
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