I was trying to detect circles from a black background with red circular kind objects.
import cv2
import cv2.cv as cv
import numpy as np
img = cv2.imread('extracted.jpg',0)
img = cv2.medianBlur(img,5)
cimg = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
circles = cv2.HoughCircles(img,cv.CV_HOUGH_GRADIENT,1,20,
param1=50,param2=30,minRadius=0,maxRadius=0)
circles = np.uint8(np.around(circles))
for i in circles[0,:]:
# draw the outer circle
cv2.circle(cimg,(i[0],i[1]),i[2],(0,255,0),2)
# draw the center of the circle
cv2.circle(cimg,(i[0],i[1]),2,(0,0,255),3)
cv2.imshow('detected circles',cimg)
cv2.waitKey(0)
cv2.destroyAllWindows()
I have loaded the image in grayscale mode,still it gives me an error
"circles = np.uint8(np.around(circles))
File "/usr/lib/python2.7/dist-packages/numpy/core/fromnumeric.py", line 2277, in around
return _wrapit(a, 'round', decimals, out)
File "/usr/lib/python2.7/dist-packages/numpy/core/fromnumeric.py", line 37, in _wrapit
result = getattr(asarray(obj),method)(*args, **kwds)
AttributeError: rint"
I cannot post the image because of my present reputation.
There is a small correction to be made in your code.
You are loading image in grayscale, and then again converting it to grayscale using cv2.cvtColor
which is invalid operation.
Alternatively, OpenCV provides a sample for circle detection using Hough Circles method. You can try that.
If you are using OpenCV 2.x version, just change the cv2.LINE_AA
to cv2.CV_AA
or any other lineType you prefer.
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