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Merge pull request #3722 from berak:py_houghlines_sample

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Vadim Pisarevsky 2015-03-03 18:16:25 +00:00
commit c9ea878d10
2 changed files with 24 additions and 22 deletions
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12
doc/py_tutorials/py_imgproc/py_houghlines/py_houghlines.markdown
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@ -59,7 +59,7 @@ denotes they are the parameters of possible lines in the image. (Image courtesy:
![](images/houghlines2.jpg) ![](images/houghlines2.jpg)
Hough Tranform in OpenCV Hough Transform in OpenCV
========================= =========================
Everything explained above is encapsulated in the OpenCV function, \*\*cv2.HoughLines()\*\*. It simply returns an array of :math:(rho, Everything explained above is encapsulated in the OpenCV function, \*\*cv2.HoughLines()\*\*. It simply returns an array of :math:(rho,
@ -78,7 +78,8 @@ gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3) edges = cv2.Canny(gray,50,150,apertureSize = 3)
lines = cv2.HoughLines(edges,1,np.pi/180,200) lines = cv2.HoughLines(edges,1,np.pi/180,200)
for rho,theta in lines[0]: for line in lines:
rho,theta = line[0]
a = np.cos(theta) a = np.cos(theta)
b = np.sin(theta) b = np.sin(theta)
x0 = a*rho x0 = a*rho
@ -123,10 +124,9 @@ import numpy as np
img = cv2.imread('dave.jpg') img = cv2.imread('dave.jpg')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3) edges = cv2.Canny(gray,50,150,apertureSize = 3)
minLineLength = 100 lines = cv2.HoughLinesP(edges,1,np.pi/180,100,minLineLength=100,maxLineGap=10)
maxLineGap = 10 for line in lines:
lines = cv2.HoughLinesP(edges,1,np.pi/180,100,minLineLength,maxLineGap) x1,y1,x2,y2 = line[0]
for x1,y1,x2,y2 in lines[0]:
cv2.line(img,(x1,y1),(x2,y2),(0,255,0),2) cv2.line(img,(x1,y1),(x2,y2),(0,255,0),2)
cv2.imwrite('houghlines5.jpg',img) cv2.imwrite('houghlines5.jpg',img)

34
samples/python2/houghlines.py
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@ -18,23 +18,25 @@ src = cv2.imread(fn)
dst = cv2.Canny(src, 50, 200) dst = cv2.Canny(src, 50, 200)
cdst = cv2.cvtColor(dst, cv2.COLOR_GRAY2BGR) cdst = cv2.cvtColor(dst, cv2.COLOR_GRAY2BGR)
# HoughLines() if True: # HoughLinesP
# lines = cv2.HoughLines(dst, 1, math.pi/180.0, 50, np.array([]), 0, 0) lines = cv2.HoughLinesP(dst, 1, math.pi/180.0, 40, np.array([]), 50, 10)
# a,b,c = lines.shape a,b,c = lines.shape
# for i in range(b): for i in range(a):
# rho = lines[0][i][0] cv2.line(cdst, (lines[i][0][0], lines[i][0][1]), (lines[i][0][2], lines[i][0][3]), (0, 0, 255), 3, cv2.LINE_AA)
# theta = lines[0][i][1]
# a = math.cos(theta) else: # HoughLines
# b = math.sin(theta) lines = cv2.HoughLines(dst, 1, math.pi/180.0, 50, np.array([]), 0, 0)
# x0, y0 = a*rho, b*rho a,b,c = lines.shape
# pt1 = ( int(x0+1000*(-b)), int(y0+1000*(a)) ) for i in range(a):
# pt2 = ( int(x0-1000*(-b)), int(y0-1000*(a)) ) rho = lines[i][0][0]
# cv2.line(cdst, pt1, pt2, (0, 0, 255), 3, cv2.LINE_AA) theta = lines[i][0][1]
a = math.cos(theta)
b = math.sin(theta)
x0, y0 = a*rho, b*rho
pt1 = ( int(x0+1000*(-b)), int(y0+1000*(a)) )
pt2 = ( int(x0-1000*(-b)), int(y0-1000*(a)) )
cv2.line(cdst, pt1, pt2, (0, 0, 255), 3, cv2.LINE_AA)
lines = cv2.HoughLinesP(dst, 1, math.pi/180.0, 50, np.array([]), 50, 10)
a,b,c = lines.shape
for i in range(b):
cv2.line(cdst, (lines[0][i][0], lines[0][i][1]), (lines[0][i][2], lines[0][i][3]), (0, 0, 255), 3, cv2.LINE_AA)
cv2.imshow("source", src) cv2.imshow("source", src)
cv2.imshow("detected lines", cdst) cv2.imshow("detected lines", cdst)