Pupil Detection with Python and OpenCV

pupil.py

#Identify pupils. Based on beta 1

import numpy as np
import cv2
import time

cap = cv2.VideoCapture(0) 	#640,480
w = 640
h = 480

while(cap.isOpened()):
    ret, frame = cap.read()
    if ret==True:
	
		#downsample
		#frameD = cv2.pyrDown(cv2.pyrDown(frame))
		#frameDBW = cv2.cvtColor(frameD,cv2.COLOR_RGB2GRAY)
	
		#detect face
		frame = cv2.cvtColor(frame,cv2.COLOR_RGB2GRAY)
		faces = cv2.CascadeClassifier('haarcascade_eye.xml')
		detected = faces.detectMultiScale(frame, 1.3, 5)
	
		#faces = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
		#detected2 = faces.detectMultiScale(frameDBW, 1.3, 5)
		
		pupilFrame = frame
		pupilO = frame
		windowClose = np.ones((5,5),np.uint8)
		windowOpen = np.ones((2,2),np.uint8)
		windowErode = np.ones((2,2),np.uint8)

		#draw square
		for (x,y,w,h) in detected:
			cv2.rectangle(frame, (x,y), ((x+w),(y+h)), (0,0,255),1)	
			cv2.line(frame, (x,y), ((x+w,y+h)), (0,0,255),1)
			cv2.line(frame, (x+w,y), ((x,y+h)), (0,0,255),1)
			pupilFrame = cv2.equalizeHist(frame[y+(h*.25):(y+h), x:(x+w)])
			pupilO = pupilFrame
			ret, pupilFrame = cv2.threshold(pupilFrame,55,255,cv2.THRESH_BINARY)		#50 ..nothin 70 is better
			pupilFrame = cv2.morphologyEx(pupilFrame, cv2.MORPH_CLOSE, windowClose)
			pupilFrame = cv2.morphologyEx(pupilFrame, cv2.MORPH_ERODE, windowErode)
			pupilFrame = cv2.morphologyEx(pupilFrame, cv2.MORPH_OPEN, windowOpen)

			#so above we do image processing to get the pupil..
			#now we find the biggest blob and get the centriod
			
			threshold = cv2.inRange(pupilFrame,250,255)		#get the blobs
			contours, hierarchy = cv2.findContours(threshold,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
			
			#if there are 3 or more blobs, delete the biggest and delete the left most for the right eye
			#if there are 2 blob, take the second largest
			#if there are 1 or less blobs, do nothing
			
			if len(contours) >= 2:
				#find biggest blob
				maxArea = 0
				MAindex = 0			#to get the unwanted frame 
				distanceX = []		#delete the left most (for right eye)
				currentIndex = 0 
				for cnt in contours:
					area = cv2.contourArea(cnt)
					center = cv2.moments(cnt)
					cx,cy = int(center['m10']/center['m00']), int(center['m01']/center['m00'])
					distanceX.append(cx)	
					if area > maxArea:
						maxArea = area
						MAindex = currentIndex
					currentIndex = currentIndex + 1
		
				del contours[MAindex]		#remove the picture frame contour
				del distanceX[MAindex]
			
			eye = 'right'

			if len(contours) >= 2:		#delete the left most blob for right eye
				if eye == 'right':
					edgeOfEye = distanceX.index(min(distanceX))
				else:
					edgeOfEye = distanceX.index(max(distanceX))	
				del contours[edgeOfEye]
				del distanceX[edgeOfEye]

			if len(contours) >= 1:		#get largest blob
				maxArea = 0
				for cnt in contours:
					area = cv2.contourArea(cnt)
					if area > maxArea:
						maxArea = area
						largeBlob = cnt
					
			if len(largeBlob) > 0:	
				center = cv2.moments(largeBlob)
				cx,cy = int(center['m10']/center['m00']), int(center['m01']/center['m00'])
				cv2.circle(pupilO,(cx,cy),5,255,-1)

	
		#show picture
		cv2.imshow('frame',pupilO)
		cv2.imshow('frame2',pupilFrame)
		if cv2.waitKey(1) & 0xFF == ord('q'):
			break
	
	#else:
		#break

# Release everything if job is finished
cap.release()
cv2.destroyAllWindows()

To -->- bma131 commented on Mar 21

Your codes did not work for me. It was giving the following error. 

After changing the following line, it worked...... (removed "_,")
_,contours, hierarchy = cv2.findContours(threshold,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)

 changed to 

contours, hierarchy = cv2.findContours(threshold,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)

However the issue with blank paper or id cards(with or without picture) shows the pupil on the screen.

It worked for me correctly thanks for the effort!
I have one question though, what does maxArea contains in each iteration ? Blob size for right eye ?

1. It worked for me correctly thanks for the effort!
   Which one worked for you ?.
   The program itself or the spoofing(id card, blank paper etc......)

2. Are you referring this maxArea = 0
   I think it is sort of flag to find the biggest area.
   Please see the following line in the code.
   if area > maxArea:
   maxArea = area
   From the above code, area moving to maxarea, if it is bigger than the previous. This way can find the biggest one.

1. It worked for me correctly thanks for the effort!
   Which one worked for you ?. -- pupil.py file itself worked for me!
   The program itself or the spoofing(id card, blank paper etc......) -- the program itself in this case
2. Are you referring this maxArea = 0
   I think it is sort of flag to find the biggest area.
   Please see the following line in the code.
   if area > maxArea:
   maxArea = area
   From the above code, area moving to maxarea, if it is bigger than the previous. This way can find the biggest one.

What I wonder here is, sorry for the late answer I've been offline due to self-isolation and I had no access to my laptop anyways. What does maxArea corresponds in here ? As far as I understood, it is the area of the biggest contour in eye and it actually indicates the pupil. But I'm not sure about it.

hi friends, thank for your source code. But I have a trouble like
", line 70, in
del contours[MAindex] # remove the picture frame contour
~~~~~~~~^^^^^^^^^
TypeError: 'tuple' object doesn't support item deletion

if I set cap is a image in 5th line, it's work. But not working with videocapture.
Please, help me if you can.

With the help of github copilot I am working through the issues. My setup is win 11 py 3.12.0. I have added comment with my name. I hopes this helps others.

I'm at troubleshooting this error
File "D:\py\pupil\measure.py", line 100, in
del contours[MAindex]
~~~~~~~~^^^^^^^^^
IndexError: list assignment index out of range

#Identify pupils. Based on beta 1

import numpy as np
import cv2
import time

cap = cv2.VideoCapture(0) #640,480
w = 640
h = 480

while(cap.isOpened()):
ret, frame = cap.read()
if ret==True:

	#downsample
	#frameD = cv2.pyrDown(cv2.pyrDown(frame))
	#frameDBW = cv2.cvtColor(frameD,cv2.COLOR_RGB2GRAY)

	#detect face
	frame = cv2.cvtColor(frame,cv2.COLOR_RGB2GRAY)
	#warprdiv added to resolve file location issue
	#faces = cv2.CascadeClassifier('haarcascade_eye.xml')
	faces = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_eye.xml')
	
	detected = faces.detectMultiScale(frame, 1.3, 5)

	#faces = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
	#detected2 = faces.detectMultiScale(frameDBW, 1.3, 5)
	
	pupilFrame = frame
	pupilO = frame
	windowClose = np.ones((5,5),np.uint8)
	windowOpen = np.ones((2,2),np.uint8)
	windowErode = np.ones((2,2),np.uint8)

	#draw square
	for (x,y,w,h) in detected:
		cv2.rectangle(frame, (x,y), ((x+w),(y+h)), (0,0,255),1)	
		cv2.line(frame, (x,y), ((x+w,y+h)), (0,0,255),1)
		cv2.line(frame, (x+w,y), ((x,y+h)), (0,0,255),1)
		#pupilFrame = cv2.equalizeHist(frame[y+(h*.25):(y+h), x:(x+w)])
		pupilFrame = cv2.equalizeHist(frame[int(y+(h*.25)):int(y+h), int(x):int(x+w)])
		pupilO = pupilFrame
		ret, pupilFrame = cv2.threshold(pupilFrame,55,255,cv2.THRESH_BINARY)		#50 ..nothin 70 is better
		pupilFrame = cv2.morphologyEx(pupilFrame, cv2.MORPH_CLOSE, windowClose)
		pupilFrame = cv2.morphologyEx(pupilFrame, cv2.MORPH_ERODE, windowErode)
		pupilFrame = cv2.morphologyEx(pupilFrame, cv2.MORPH_OPEN, windowOpen)

		#so above we do image processing to get the pupil..
		#now we find the biggest blob and get the centriod
		
		threshold = cv2.inRange(pupilFrame,250,255)		#get the blobs
		contours, hierarchy = cv2.findContours(threshold,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
		
		#if there are 3 or more blobs, delete the biggest and delete the left most for the right eye
		#if there are 2 blob, take the second largest
		#if there are 1 or less blobs, do nothing
		
		if len(contours) >= 2:
			#find biggest blob
			maxArea = 0
			MAindex = 0			#to get the unwanted frame 
			distanceX = []		#delete the left most (for right eye)
			currentIndex = 0 
			for cnt in contours:
				area = cv2.contourArea(cnt)
				center = cv2.moments(cnt)
				#warpdriv added take care of divide by zero error
				if center['m00'] != 0:	
					cx,cy = int(center['m10']/center['m00']), int(center['m01']/center['m00'])
				distanceX.append(cx)	
				if area > maxArea:
					maxArea = area
					MAindex = currentIndex
				currentIndex = currentIndex + 1
	
			#del contours[MAindex]		#remove the picture frame contour
			#warpdriv added
			contours = list(contours)
			del contours[MAindex]
			contours = tuple(contours)

			#del distanceX[MAindex]
			#warpdriv added
			distanceX = list(distanceX)
			del distanceX[MAindex]
			distanceX = tuple(distanceX)
		
		eye = 'right'

		if len(contours) >= 2:		#delete the left most blob for right eye
			if eye == 'right':
				edgeOfEye = distanceX.index(min(distanceX))
			else:
				edgeOfEye = distanceX.index(max(distanceX))	

			#warpdriv added
			#del contours[MAindex]		#remove the picture frame contour
			contours = list(contours)
			del contours[MAindex]
			contours = tuple(contours)

			#warpdriv added
			#del distanceX[MAindex]
			distanceX = list(distanceX)
			del distanceX[MAindex]
			distanceX = tuple(distanceX)

		if len(contours) >= 1:		#get largest blob
			maxArea = 0
			for cnt in contours:
				area = cv2.contourArea(cnt)
				if area > maxArea:
					maxArea = area
					largeBlob = cnt
				
		if len(largeBlob) > 0:	
			center = cv2.moments(largeBlob)
			cx,cy = int(center['m10']/center['m00']), int(center['m01']/center['m00'])
			cv2.circle(pupilO,(cx,cy),5,255,-1)


	#show picture
	cv2.imshow('frame',pupilO)
	cv2.imshow('frame2',pupilFrame)
	if cv2.waitKey(1) & 0xFF == ord('q'):
		break

#else:
	#break

Release everything if job is finished

cap.release()
cv2.destroyAllWindows()