Python 如何使用OpenCV在路缘上绘制直线？

我用这段代码用canny和hough做线条检测，但是效果不好

我想在路边画一条线。画直线的目的是计算直线在图像中的位置，因为当我自动驾驶时，我希望我的ROS汽车沿着路边行驶。我的国家是右侧驾驶

import cv2
import numpy as np

img = cv2.imread(r"E:\test_opencv\images\testcanny.jpg")
blur_img = cv2.GaussianBlur(img, (3, 3), 0)
edges = cv2.Canny(blur_img, 250, 450, apertureSize=3)
lines = cv2.HoughLines(edges, 1, np.pi / 180, 118)
minLineLength = 800
maxLineGap = 15
threshold=80
lines = cv2.HoughLinesP(edges, 1, np.pi / 180, threshold, minLineLength, maxLineGap)
for i in range(len(lines)):
    for x1, y1, x2, y2 in lines[i]:
        cv2.line(img, (x1, y1), (x2, y2), (0, 255, 0), 4)
cv2.imshow('canny', edges)
cv2.imshow('Result', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

原图：

精明的图片：

结果图片：

结果图片上只有一些短的绿色线条

事实上，我只是希望路缘的红色部分变成绿线。

就这样,

---

如何修复代码？

使用经典Hough变换（

HoughLines

）比概率Hough变换（

HoughLinesP

）的结果更好。我在你的图片上运行了这个代码，得到了这些结果。第一个图像的阈值为100，下一个图像的阈值为200

守则：

import cv2
import numpy as np

img = cv2.imread("D:\\1.jpg")
blur_img = cv2.GaussianBlur(img, (3, 3), 0)
edges = cv2.Canny(blur_img, 250, 450, apertureSize=3)

rho = 1  #Distance resolution of the accumulator in pixels.
theta = np.pi/180 # Angle resolution of the accumulator in radians.
threshold  = 200 #Accumulator threshold parameter. Only those lines are returned that get enough votes ( >\texttt{threshold} ).

lines = cv2.HoughLines(edges, rho, theta, threshold)

for i in range(len(lines)):
    for r,th in lines[i]:
        a = np.cos(th)
        b = np.sin(th)
        x0 = a*r
        y0 = b*r
        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)

cv2.imshow('canny', edges)
cv2.imshow('Result', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

以及关于Hough变换的更多信息：

---

使用经典Hough变换（

HoughLines

）比使用概率Hough变换（

HoughLinesP

）得到更好的结果。我在你的图片上运行了这个代码，得到了这些结果。第一个图像的阈值为100，下一个图像的阈值为200

守则：

import cv2
import numpy as np

img = cv2.imread("D:\\1.jpg")
blur_img = cv2.GaussianBlur(img, (3, 3), 0)
edges = cv2.Canny(blur_img, 250, 450, apertureSize=3)

rho = 1  #Distance resolution of the accumulator in pixels.
theta = np.pi/180 # Angle resolution of the accumulator in radians.
threshold  = 200 #Accumulator threshold parameter. Only those lines are returned that get enough votes ( >\texttt{threshold} ).

lines = cv2.HoughLines(edges, rho, theta, threshold)

for i in range(len(lines)):
    for r,th in lines[i]:
        a = np.cos(th)
        b = np.sin(th)
        x0 = a*r
        y0 = b*r
        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)

cv2.imshow('canny', edges)
cv2.imshow('Result', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

以及关于Hough变换的更多信息：

---

对于这张图片，我使用此代码来获得更好的效果

import cv2
import numpy as np

img = cv2.imread(r"E:\test_opencv\images\testcanny.jpg")
blur_img = cv2.GaussianBlur(img, (3, 3), 0)
gray = cv2.cvtColor(blur_img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray, 250, 350, apertureSize=3)
rho = 1  #Distance resolution of the accumulator in pixels.
theta = np.pi/180 # Angle resolution of the accumulator in radians.
threshold  = 300 #Accumulator threshold parameter. Only those lines are returned that get enough votes ( >\texttt{threshold} ).
lines = cv2.HoughLines(edges, rho, theta, threshold)
if lines is not None:
    for i in range(len(lines)):
        for r,th in lines[i]:
            a = np.cos(th)
            b = np.sin(th)
            x0 = a*r
            y0 = b*r
            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)
cv2.imshow('canny', edges)
cv2.imshow('Result', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

结果图片：

---

对于这张图片，我使用此代码来获得更好的效果

import cv2
import numpy as np

img = cv2.imread(r"E:\test_opencv\images\testcanny.jpg")
blur_img = cv2.GaussianBlur(img, (3, 3), 0)
gray = cv2.cvtColor(blur_img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray, 250, 350, apertureSize=3)
rho = 1  #Distance resolution of the accumulator in pixels.
theta = np.pi/180 # Angle resolution of the accumulator in radians.
threshold  = 300 #Accumulator threshold parameter. Only those lines are returned that get enough votes ( >\texttt{threshold} ).
lines = cv2.HoughLines(edges, rho, theta, threshold)
if lines is not None:
    for i in range(len(lines)):
        for r,th in lines[i]:
            a = np.cos(th)
            b = np.sin(th)
            x0 = a*r
            y0 = b*r
            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)
cv2.imshow('canny', edges)
cv2.imshow('Result', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

结果图片：

---

当我在您的代码中设置

threshold=300

时，路边只有一行，这非常有用。谢谢！当我在你的代码中设置

threshold=300

时，路边只有一行，这非常有用。谢谢！