def ovalChange(self, i):
if i > 0:
prevOval = ovalList[i - 1]
self.canvas.itemconfigure(prevOval, fill="black")
if i < (len(ovalList)):
currentOval = ovalList[i]
self.canvas.itemconfigure(currentOval, fill="red")
self.canvas.update()
time.sleep(3)
if i < (len(ovalList)):
#Call Edge Detection of binary frame
ret, frame = cam.read()
threshPupil, threshGlint = imgThreshold.imgThreshold(frame)
cpX,cpY,cp,ccX,ccY,cc,successfullyDetected = edgeDet.edgeDetectionAlgorithm(threshPupil,threshGlint)
calIteration = 0
while not successfullyDetected:
ret, frame = cam.read()
threshPupil, threshGlint = imgThreshold.imgThreshold(frame)
cpX,cpY,cp,ccX,ccY,cc,successfullyDetected = edgeDet.edgeDetectionAlgorithm(threshPupil,threshGlint)
calIteration += 1
#print calIteration
if calIteration > 100:
self.canvas.itemconfigure(currentOval, fill="orange")
self.canvas.update()
threshPupil, threshGlint = imgThreshold.imgThreshold(frame)
cv2.imshow('feed',threshPupil)
if successfullyDetected:
cv2.imwrite('pic{:>05}.png'.format(i), frame)
calIteration = 0
pupilX.append(cpX)
pupilY.append(cpY)
glintX.append(ccX)
glintY.append(ccY)
print 'pupilX current'
print pupilX
if i < (len(ovalList)):
j = i + 1
self.ovalChange(j)
if i == (len(ovalList)-1):
print 'Pupil x'
print pupilX
print 'Pupil y'
print pupilY
print 'glint x'
print glintX
print 'glint y'
print glintY
print 'ScreenCoordsX'
print screenCoordinatesX
print 'ScreenCoordsY'
print screenCoordinatesY
aOriginal, bOriginal = GCU.calibration(pupilX, pupilY, glintX, glintY, screenCoordinatesX, screenCoordinatesY)
print aOriginal
print "Here's a gap"
print bOriginal
print 'Calibration done'
return aOriginal, bOriginal
def show_frame(self):
#Read the input feed, flip it, resize it and show it in the corresponding label
ret, frame = cap.read()
flipFrame = cv2.flip(frame, 1)
cv2image = cv2.resize(flipFrame, (vidWidth, vidHeight));
img1 = Image.fromarray(cv2image)
imgtk1 = ImageTk.PhotoImage(image=img1)
videoStream1.imgtk1 = imgtk1
videoStream1.configure(image=imgtk1)
#Call the threholding function
threshPupil, threshGlint = imgThreshold.imgThreshold(frame)
#Call Edge Detection of binary frame
cpX,cpY,cp,ccX,ccY,cc,successfullyDetected = edgeDet.edgeDetectionAlgorithm(threshPupil,threshGlint)
#Draw around the pupil and glint
print('cpX: ', cpX, ' cpY: ', cpY, ' ccX: ', ccX, ' ccY: ', ccY)
#print successfullyDetected
if cpX is None or cpY is None or ccX is None or ccY is None:
print('pupil or corneal not detected, skipping...')
else:
# Ellipse Fitting
frameCopy = frame.copy()
#draw pupil centre
cv2.circle(frameCopy, (cpX,cpY),3,(0,255,0),-1)
#draw pupil circumference
cv2.drawContours(frameCopy,cp,-1,(0,0,255),3)
#draw corneal centre
cv2.circle(frameCopy, (ccX,ccY),3,(0,255,0),-1)
#draw corneal circumference
cv2.drawContours(frameCopy,cc,-1,(0,0,255),3)
#Show detected pupil
if(frameCopy != None):
frameC_resized = cv2.resize(frameCopy, (vidWidth, vidHeight), interpolation = cv2.INTER_AREA)
frameC_resized = cv2.flip(frameC_resized, 1)
img1 = Image.fromarray(frameC_resized)
imgtk1 = ImageTk.PhotoImage(image=img1)
videoStream1.imgtk1 = imgtk1
videoStream1.configure(image=imgtk1)
#If mouseToggle is true implement the cursor control code
#Allows user to interact with computer wiht their eyes
if mouseToggle:
if 'aOriginal' in globals() and 'bOriginal' in globals():
# Centre points of glint and pupil pass to vector
gazeX, gazeY = GGP.getGazePoint(aOriginal, bOriginal, cpX, cpY, ccX, ccY)
ATE.move_mouse(gazeX, gazeY)
infoLabel.configure(text = "Now tracking your eye!")
else:
infoLabel.configure(text = "You have not calibrated yet, please do so")
videoStream1.after(5, self.show_frame)
def show_frameInit(self):
#Read the input feed, flip it, resize it and show it in the corresponding label
if cap.isOpened():
ret, frame = cap.read()
flipFrame = cv2.flip(frame, 1)
cv2image = cv2.resize(flipFrame, (vidWidth, vidHeight))
img1 = Image.fromarray(cv2image)
imgtk1 = ImageTk.PhotoImage(image=img1)
videoStreamInit.imgtk1 = imgtk1
videoStreamInit.configure(image=imgtk1)
#Call the threholding function
threshPupil, threshGlint = imgThreshold.imgThreshold(frame)
#Call Edge Detection of binary frame
cpX,cpY,cp,ccX,ccY,cc,successfullyDetected = edgeDet.edgeDetectionAlgorithm(threshPupil,threshGlint)
#Draw around the pupil and glint, if they are detected
print('cpX: ', cpX, ' cpY: ', cpY, ' ccX: ', ccX, ' ccY: ', ccY)
if cpX is None or cpY is None or ccX is None or ccY is None:
print('pupil or corneal not detected, skipping...')
else:
# Ellipse Fitting
frameCopy = frame.copy()
#draw pupil centre
cv2.circle(frameCopy, (cpX,cpY),3,(0,255,0),-1)
#draw pupil circumference
cv2.drawContours(frameCopy,cp,-1,(0,0,255),3)
#draw corneal centre
cv2.circle(frameCopy, (ccX,ccY),3,(0,255,0),-1)
#draw corneal circumference
cv2.drawContours(frameCopy,cc,-1,(0,0,255),3)
#Code that will show the detected pupil, if it is detected
if(frameCopy != None):
frameC_resized = cv2.resize(frameCopy, (vidWidth, vidHeight), interpolation = cv2.INTER_AREA)
frameC_resized = cv2.flip(frameC_resized, 1)
img1 = Image.fromarray(frameC_resized)
imgtk1 = ImageTk.PhotoImage(image=img1)
videoStreamInit.imgtk1 = imgtk1
videoStreamInit.configure(image=imgtk1)
else:
#Alerts the suer if the camera is not plugged in, attempts to open camera feed
videoStreamInit.configure(text = "You have not plugged in the camera")
global cap
cap = cv2.VideoCapture(capVal)
#Continue showing feed until calibration button is pressed.
if (not calButton):
videoStreamInit.after(5, self.show_frameInit)
def show_frame(self):
#Read the input feed, flip it, resize it and show it in the corresponding label
ret, frame = cap.read()
flipFrame = cv2.flip(frame, 1)
cv2image = cv2.cvtColor(flipFrame, cv2.COLOR_BGR2GRAY)
cv2image = cv2.resize(flipFrame, (vidWidth, vidHeight));
img1 = Image.fromarray(cv2image)
imgtk1 = ImageTk.PhotoImage(image=img1)
videoStream1.imgtk1 = imgtk1
videoStream1.configure(image=imgtk1)
#Call the threholding function
threshPupil, threshGlint = imgThreshold.imgThreshold(frame)
#Call Edge Detection of binary frame
cpX,cpY,cp,ccX,ccY,cc,successfullyDetected = edgeDet.edgeDetectionAlgorithm(threshPupil,threshGlint)
#Draw around the pupil and glint
print('cpX: ', cpX, ' cpY: ', cpY, ' ccX: ', ccX, ' ccY: ', ccY)
if cpX is None or cpY is None or ccX is None or ccY is None:
print('pupil or corneal not detected, skipping...')
else:
# Ellipse Fitting
frameCopy = frame.copy()
#draw pupil centre
cv2.circle(frameCopy, (cpX,cpY),3,(0,255,0),-1)
#draw pupil circumference
cv2.drawContours(frameCopy,cp,-1,(0,0,255),3)
#draw corneal centre
cv2.circle(frameCopy, (ccX,ccY),3,(0,255,0),-1)
#draw corneal circumference
cv2.drawContours(frameCopy,cc,-1,(0,0,255),3)
#Show the detected pupil
if(frameCopy != None):
frameC_resized = cv2.resize(frameCopy, (vidWidth, vidHeight), interpolation = cv2.INTER_AREA)
frameC_resized = cv2.flip(frameC_resized, 1)
img1 = Image.fromarray(frameC_resized)
imgtk1 = ImageTk.PhotoImage(image=img1)
videoStream1.imgtk1 = imgtk1
videoStream1.configure(image=imgtk1)
videoStream1.after(5, self.show_frame)
calibrationY = [133, 133, 133, 399, 399, 399, 665, 665, 665]
aOriginal, bOriginal = GCU.calibration(pupilX, pupilY, glintX, glintY, calibrationX, calibrationY)
# Open video capture
cap = cv2.VideoCapture(1)
i = 0
print(cap)
print(cap.isOpened())
while(cap.isOpened()):
# Read a frame from feed
ret, frame = cap.read()
threshPupil, threshGlint = imgThreshold.imgThreshold(frame)
# Edge Detection of binary frame
cpX,cpY,cp,ccX,ccY,cc,successfullyDetected = edgeDet.edgeDetectionAlgorithm(threshPupil, threshGlint)
# print('cpX: ', cpX, ' cpY: ', cpY, ' ccX: ', ccX, ' ccY: ', ccY)
if cpX is None or cpY is None or ccX is None or ccY is None:
print('pupil or corneal not detected, skipping...')
else:
# Ellipse Fitting
frameCopy = frame.copy()
#draw pupil centre
cv2.circle(frameCopy, (cpX,cpY),3,(0,255,0),-1)
#draw pupil circumference
cv2.drawContours(frameCopy,cp,-1,(0,0,255),3)
def ovalChange(self):
global iteration
global quitButtonClick
print "clicked start calibration %d" % iteration
#As long as the quit button hasnt been pressed
#Colour the previous dot black, if there is a previous dot
#Colour the current dot red
if (not quitButtonClick):
if iteration > 0:
prevOval = ovalList[iteration - 1]
self.canvas.itemconfigure(prevOval, fill="black")
if iteration < (len(ovalList)):
currentOval = ovalList[iteration]
self.canvas.itemconfigure(currentOval, fill="red")
self.canvas.update()
time.sleep(3)
if iteration < (len(ovalList)):
if iteration > 0:
prevOval = ovalList[iteration - 1]
self.canvas.itemconfigure(prevOval, fill="black")
currentOval = ovalList[iteration]
self.canvas.itemconfigure(currentOval, fill="red")
self.canvas.update()
#Cause a delay between dots, so the user has time to move gaze
count = 0
while(count < 12):
count+=1
ret, frame = cap.read()
gazeCount = 0
curPupilX = []
curPupilY = []
curGlintX = []
curGlintY = []
#Collect 3 sets of gaze points for each dot
while (gazeCount < 3):
countGap = 0
#Cause delay between collection of data sets
while(countGap < 4):
countGap+=1
ret, frame = cap.read()
#Read frame, threshold, edge detect
ret, frame = cap.read()
threshPupil, threshGlint = imgThreshold.imgThreshold(frame)
cpX,cpY,cp,ccX,ccY,cc,successfullyDetected = edgeDet.edgeDetectionAlgorithm(threshPupil,threshGlint)
calIteration = 0
#If edges have not been detected, try again
#If edges are not detected for a prolonged perios, turn calibration dot orange
#and show the camera feed
while not successfullyDetected:
ret, frame = cap.read()
threshPupil, threshGlint = imgThreshold.imgThreshold(frame)
cpX,cpY,cp,ccX,ccY,cc,successfullyDetected = edgeDet.edgeDetectionAlgorithm(threshPupil,threshGlint)
calIteration += 1
if calIteration > 100:
self.canvas.itemconfigure(currentOval, fill="orange")
self.canvas.update()
threshPupil, threshGlint = imgThreshold.imgThreshold(frame)
self.checkFeedFrame()
#If the edges have been successfully detected, store the pupil and glint data
if successfullyDetected:
self.removewindow()
cv2.imwrite('pic{:>05}{}.png'.format(iteration, gazeCount), frame)
print ("saved image %d " % iteration)
calIteration = 0
curPupilX.append(cpX)
curPupilY.append(cpY)
curGlintX.append(ccX)
curGlintY.append(ccY)
# self.canvas.itemconfigure(currentOval, fill="green")
# self.canvas.update()
gazeCount += 1
#Once there are three sets of gaze data for each dot
#find the average values of each bit of data and store the average
#in the corresponding list
countPupilX = 0
for e in curPupilX:
countPupilX += e
avgPupilX = countPupilX/len(curPupilX)
countPupilY = 0
for e in curPupilY:
countPupilY += e
avgPupilY = countPupilY/len(curPupilY)
countGlintX = 0
for e in curGlintX:
countGlintX += e
avgGlintX = countGlintX/len(curGlintX)
countGlintY = 0
for e in curGlintY:
countGlintY += e
avgGlintY = countGlintY/len(curGlintY)
pupilX.append(avgPupilX)
pupilY.append(avgPupilY)
glintX.append(avgGlintX)
glintY.append(avgGlintY)
iteration += 1
#If all the dots have been visited pass the data collected to the
#calibraiton equations and open the user frame
if iteration == (len(ovalList)):
global aOriginal
global bOriginal
aOriginal, bOriginal = GCU.calibration(pupilX, pupilY, glintX, glintY,screenCoordinatesX, screenCoordinatesY)
self.canvas.itemconfigure(currentOval, fill="black")
iteration += 1
self.openUserFrame()
else:
self.ovalChange()
