Eye Pupil Tracking using Hough Circle Transform - python-2.7

Question

I have a project of Eye Controlled Wheel Chair where I need to detect the pupil of the Eye and according to its motion the Wheel Chair moves. As a test for the code I am writing I performed the script on a static image. The image is exactly where the camera will be put. The camera will be an IR one.
Note: I am using compiled OpenCV 3.1.0-dev and Python2.7 on Windows Platfrom
The detected circle I wanted using Houghcircle transform:
After that I am working on a code to detect the same thing only by using an IR camera.
The results from the static image code is very reliable to me, but the problem is the code with the IR camera.
The code I have wrote so far is:
import cv2
import numpy as np
cap = cv2.VideoCapture(0)
while True:
## Read Image
ret, image = cap.read()
## Convert to 1 channel only grayscale image
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
## CLAHE Equalization
cl1 = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
clahe = cl1.apply(gray)
## medianBlur the image to remove noise
blur = cv2.medianBlur(clahe, 7)
## Detect Circles
circles = cv2.HoughCircles(blur ,cv2.HOUGH_GRADIENT,1,20,
param1=50,param2=30,minRadius=7,maxRadius=21)
if circles != None:
circles = np.round(circles[0,:]).astype("int")
for circle in circles[0,:]:
# draw the outer circle
cv2.circle(image,(circle[0],circle[1]),circle[2],(0,255,0),2)
# draw the center of the circle
cv2.circle(image,(circle[0],circle[1]),2,(0,0,255),3)
if cv2.waitKey(1) in [27, ord('q'), 32]:
break
cap.release()
cv2.destroyAllWindows()
I always get this error:
**if circles != None:
FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.
Traceback (most recent call last):
cv2.circle(image,(circle[0],circle[1]),circle[2],(0,255,0),2)
IndexError: invalid index to scalar variable.**
For any questions about the code for the static image, the code is:
import cv2
import numpy as np
## Read Image
image = cv2.imread('eye.tif')
imageBackup = image.copy()
## Convert to 1 channel only grayscale image
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
## CLAHE Equalization
cl1 = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
clahe = cl1.apply(gray)
## medianBlur the image to remove noise
blur = cv2.medianBlur(clahe, 7)
## Detect Circles
circles = cv2.HoughCircles(blur ,cv2.HOUGH_GRADIENT,1,20,
param1=50,param2=30,minRadius=7,maxRadius=21)
for circle in circles[0,:]:
# draw the outer circle
cv2.circle(image,(circle[0],circle[1]),circle[2],(0,255,0),2)
# draw the center of the circle
cv2.circle(image,(circle[0],circle[1]),2,(0,0,255),3)
cv2.imshow('Final', image)
cv2.imshow('imageBackup', imageBackup)
cv2.waitKey(0)
cv2.destroyAllWindows()

Answer 1

So i tried it out my self and i had the same error. So i modified the code like i already proposed. Here is the snipped:
if circles != None:
for circle in circles[0,:]:
# draw the outer circle
cv2.circle(image,(circle[0],circle[1]),circle[2],(0,255,0),2)
# draw the center of the circle
cv2.circle(image,(circle[0],circle[1]),2,(0,0,255),3)
In addition you can try to use cv2.Canny for better results. Over and out :)