这次我尝试从Solem’s blog开始的另一个例子.它是一个通过使用Hough变换检测图像中的线条和圆圈的模块.
这是代码(houghlines.py)：

import numpy as np
import cv2

"""
Script using OpenCV's Hough transforms for reading images of 
simple dials.
"""

# load grayscale image
im = cv2.imread("house2.jpg")
gray_im = cv2.cvtColor(im, cv2.COLOR_RGB2GRAY)

# create version to draw on and blurred version
draw_im = cv2.cvtColor(gray_im, cv2.COLOR_GRAY2BGR)
blur = cv2.GaussianBlur(gray_im, (0,0), 5)

m,n = gray_im.shape

# Hough transform for circles
circles = cv2.HoughCircles(gray_im, cv2.cv.CV_HOUGH_GRADIENT, 2, 10, np.array([]), 20, 60, m/10)[0]

# Hough transform for lines (regular and probabilistic)
edges = cv2.Canny(blur, 20, 60)
lines = cv2.HoughLines(edges, 2, np.pi/90, 40)[0]
plines = cv2.HoughLinesP(edges, 1, np.pi/180, 20, np.array([]), 10)[0]

# draw 
for c in circles[:3]:
 # green for circles (only draw the 3 strongest)
 cv2.circle(draw_im, (c[0],c[1]), c[2], (0,255,0), 2) 

for (rho, theta) in lines[:5]:
 # blue for infinite lines (only draw the 5 strongest)
 x0 = np.cos(theta)*rho 
 y0 = np.sin(theta)*rho
 pt1 = ( int(x0 + (m+n)*(-np.sin(theta))), int(y0 + (m+n)*np.cos(theta)) )
 pt2 = ( int(x0 - (m+n)*(-np.sin(theta))), int(y0 - (m+n)*np.cos(theta)) )
 cv2.line(draw_im, pt1, pt2, (255,0,0), 2) 

for l in plines:
 # red for line segments
 cv2.line(draw_im, (l[0],l[1]), (l[2],l[3]), (0,0,255), 2)

cv2.imshow("circles",draw_im)
cv2.waitKey()

# save the resulting image
cv2.imwrite("res.jpg",draw_im)

当我在python中执行文件时：

execfile('houghlines.py')

出现以下错误：

File "houghlines.py", line 24, in <module>
    lines = cv2.HoughLines(edges, 2, np.pi/90, 40)[0]
TypeError: 'NoneType' object has no attribute '__getitem__'

你们有任何想法如何解决它？
提前致谢.

解决方法:

有时HoughLines和HoughLinesP没有返回.我认为这意味着“没有台词”.我真的很惊讶文档中的示例没有考虑到它.也许这是一个错误.

在任何情况下,您都可以使用简单的if结果来阻止代码失败！=无：或用默认列表替换None(如HoughLinesP(… args …)或[[]]).这不会解决您的线路未被检测到的事实,但它允许您在该情况下执行某些操作而不是失败.