def draw(photo,initital_time):
image = photo.copy()
image_to_show = image
global time_to_next
global current_time
global previous_time
global duration
eyes = detect_objects(image, eyeCascadeClassifier)
## Select the rightmost eye ##
rightmost_eye = None
if eyes is not None:
for eye in eyes:
(x,y) = eye[0], eye[1]
(x2,y2) = (eye[0] + eye[2]), (eye[1] + eye[3])
if (rightmost_eye is None) or (x < rightmost_eye.x):
rightmost_eye = Eye(x, y, x2, y2)
####### Extract the image of the rightmost eye ################
eye_image = None
if rightmost_eye is not None:
eye_image = image[rightmost_eye.y:rightmost_eye.y2, rightmost_eye.x:rightmost_eye.x2]
# edge detection
binary_eye_image = None
if eye_image is not None:
eye_histogram = [0]*256
eye_image = cv2.cvtColor(eye_image, cv2.COLOR_RGB2GRAY)
for i in xrange(256):
value_count = (eye_image == i).sum()
eye_histogram[i] = value_count
count = 0
index = 255
while count < (eye_image.size*3/4):
count += eye_histogram[index]
index -= 1
quarter_threshold = index
#Multiply all parts of eye above bottom 1/4 brightness by 0
binary_eye_image = cv2.equalizeHist((eye_image < quarter_threshold) * eye_image)
#Look for circle (the iris)
relative_iris_coordinates = None
if binary_eye_image is not None:
eye_circles = cv2.HoughCircles(binary_eye_image, cv2.cv.CV_HOUGH_GRADIENT, 3, 500, maxRadius = binary_eye_image.shape[0]/5)
if eye_circles is not None:
#Usually gets the job done. Messy.
circle = eye_circles[0][0]
relative_iris_coordinates = (circle[0], circle[1])
######### Put dot on eye in big picture ##################
absolute_iris_coordinates = None
if relative_iris_coordinates is not None and rightmost_eye is not None:
absolute_iris_coordinates = (int(relative_iris_coordinates[0]+rightmost_eye.x), int(relative_iris_coordinates[1]+rightmost_eye.y))
cv2.circle(image_to_show, absolute_iris_coordinates, 5, (0,0,255), thickness=10)
current_time = int(time.clock())-int(initital_time)
#print "Current Time: {0}".format(current_time)
#print "Previous Time: {0}".format(previous_time)
if current_time != previous_time:
time_to_next += 1
if duration == time_to_next:
if absolute_iris_coordinates is not None:
print absolute_iris_coordinates[0]
'''if absolute_iris_coordinates is not None:
if absolute_iris_coordinates[0]<=250:
print "LEFT"
elif absolute_iris_coordinates[0]>=300:
print "RIGHT"
else:
print "MIDDLE"
'''
#else:
#print "STOP"
time_to_next = 0
else:
previous_time = current_time
else:
previous_time = current_time
if eyes is None:
print "Eye Not found"
# Extract image of iris
iris_image = None
if absolute_iris_coordinates is not None:
x = absolute_iris_coordinates[0]
y = absolute_iris_coordinates[1]
#Change the value depending upon the size of the iris
w = 40
h = 40
iris_image = photo[y-h:y+h,x-w:x+w]
iris_image_to_show = cv2.resize(iris_image, (iris_image.shape[1]*2, iris_image.shape[0]*2))
image_to_show[0:iris_image_to_show.shape[0], 00:00+iris_image_to_show.shape[1]] = iris_image_to_show
### Draw red circle around iris. Draw green around pupil
iris_picture = None
if iris_image is not None:
iris_gray = cv2.cvtColor(iris_image, cv2.COLOR_RGB2GRAY)
iris_circles_image = iris_image.copy()
iris_circles = cv2.HoughCircles(iris_gray, cv2.cv.CV_HOUGH_GRADIENT, 2, 100)
if iris_circles is not None:
circle=iris_circles[0][0]
cv2.circle(iris_circles_image, (circle[0], circle[1]), circle[2], (0,0,255), thickness=2)
pupil_coords = pupil_detect.find_pupil(iris_gray)
if pupil_coords is not None:
cv2.circle(iris_circles_image, pupil_coords[:2], pupil_coords[2], (0,255,0),4)
if iris_circles is not None and pupil_coords is not None:
ic = iris_circles[0][0]
pc = pupil_coords
#Check if pupil is within iris
if abs(ic[0]-pc[0])<ic[2] and abs(ic[1]-pc[1])<ic[2] and pc[2]<ic[2]:
iris_picture = iris_circles_image
iris_circles_to_show = cv2.resize(iris_circles_image, (iris_circles_image.shape[1]*2,iris_circles_image.shape[0]*2))
image_to_show[0:iris_circles_to_show.shape[0], 200:200+iris_circles_to_show.shape[1]] = iris_circles_to_show
cv2.imshow('Image', image_to_show)
if cv2.waitKey(10) > 0: #If we got a key press in less than 10ms
#Also, cv2 has some weirdness where the image won't update without a waitKey()
return True, iris_picture
return False, iris_picture
def draw(photo):
image = photo.copy()
image_to_show = image
eyes = detect_objects(image, olho_cascade)
#################### Select the rightmost eye ##################
rightmost_eye = None
if eyes is not None:
for eye in eyes:
(x, y) = eye[0], eye[1]
(x2, y2) = (eye[0] + eye[2]), (eye[1] + eye[3])
if (rightmost_eye is None) or (x < rightmost_eye.x):
rightmost_eye = Eye(x, y, x2, y2)
###############################################################
####### Extract the image of the rightmost eye ################
eye_image = None
if rightmost_eye is not None:
eye_image = image[rightmost_eye.y:rightmost_eye.y2,
rightmost_eye.x:rightmost_eye.x2]
###############################################################
### To assist in edge detection, try to "black out" sclera ####
binary_eye_image = None
if eye_image is not None:
eye_histogram = [0] * 256
eye_image = cv2.cvtColor(eye_image, cv2.COLOR_RGB2GRAY)
for i in range(256):
value_count = (eye_image == i).sum()
eye_histogram[i] = value_count
count = 0
index = 255
while count < (eye_image.size * 3 / 4):
count += eye_histogram[index]
index -= 1
quarter_threshold = index
#Multiply all parts of eye above bottom 1/4 brightness by 0
#Might not work on people with light irises. Have not tried.
binary_eye_image = cv2.equalizeHist(
(eye_image < quarter_threshold) * eye_image)
###############################################################
####### Look for circle (the iris). Save coordinates. ########
relative_iris_coordinates = None
if binary_eye_image is not None:
eye_circles = cv2.HoughCircles(binary_eye_image,
cv2.HOUGH_GRADIENT,
3,
500,
maxRadius=40)
if eye_circles is not None:
#Usually gets the job done. Messy.
circle = eye_circles[0][0]
relative_iris_coordinates = (circle[0], circle[1])
###############################################################
######### Put blue dot on eye in big picture ##################
absolute_iris_coordinates = None
if relative_iris_coordinates is not None and rightmost_eye is not None:
absolute_iris_coordinates = (int(relative_iris_coordinates[0] +
rightmost_eye.x),
int(relative_iris_coordinates[1] +
rightmost_eye.y))
cv2.circle(image_to_show,
absolute_iris_coordinates,
5, (255, 0, 0),
thickness=10)
###############################################################
####### Extract image of iris (and some surrounding) ##########
iris_image = None
if absolute_iris_coordinates is not None:
x = absolute_iris_coordinates[0]
y = absolute_iris_coordinates[1]
#Should find a way to make these numbers adaptable.
#It really messes things up when these arbitrary numbers don't work with
#whatever image size or eye distance is actually being used.
#YOU, DEAR READER, MUST CHANGE THESE FOR YOUR CAMERA
#These numbers describe the guestimated shape of a captured image of an iris.
#This program makes no effort to automatically find the size of the iris in
#the captured image of the iris
w = 60
h = 60
iris_image = photo[y - h:y + h, x - w:x + w]
iris_image_to_show = cv2.resize(
iris_image, (iris_image.shape[1] * 2, iris_image.shape[0] * 2))
image_to_show[0:iris_image_to_show.shape[0],
00:00 + iris_image_to_show.shape[1]] = iris_image_to_show
###############################################################
### Draw blue circle around iris. Draw green around pupil #####
#Also, if the pupil and iris seem to be sensible shapes/sizes,
#return the current iris_image (picture of the iris+surroundings)
iris_picture = None
if iris_image is not None:
iris_gray = cv2.cvtColor(iris_image, cv2.COLOR_RGB2GRAY)
iris_circles_image = iris_image.copy()
iris_circles = cv2.HoughCircles(iris_gray, cv2.HOUGH_GRADIENT, 2, 100)
if iris_circles is not None:
circle = iris_circles[0][0]
cv2.circle(iris_circles_image, (circle[0], circle[1]),
circle[2], (255, 0, 0),
thickness=2)
pupil_coords = pupil_detect.find_pupil(iris_gray)
if pupil_coords is not None:
cv2.circle(iris_circles_image, pupil_coords[:2], pupil_coords[2],
(0, 255, 0), 4)
if iris_circles is not None and pupil_coords is not None:
ic = iris_circles[0][0]
pc = pupil_coords
#Check if pupil is within iris
if abs(ic[0] - pc[0]) < ic[2] and abs(
ic[1] - pc[1]) < ic[2] and pc[2] < ic[2]:
iris_picture = iris_circles_image
iris_circles_to_show = cv2.resize(
iris_circles_image,
(iris_circles_image.shape[1] * 2, iris_circles_image.shape[0] * 2))
image_to_show[0:iris_circles_to_show.shape[0], 200:200 +
iris_circles_to_show.shape[1]] = iris_circles_to_show
###############################################################
cv2.imshow('Video de captura', image_to_show)
if (cv2.waitKey(1)
& 0xFF == ord('q')): #If we got a key press in less than 10ms
#Also, cv2 has some weirdness where the image won't update without a waitKey()
return True
return False
def draw(photo):
image = photo.copy()
image_to_show = image
eyes = detect_objects(image, eyeCascadeClassifier)
#################### Select the rightmost eye ##################
rightmost_eye = None
if eyes is not None:
for eye in eyes:
(x,y) = eye[0], eye[1]
(x2,y2) = (eye[0] + eye[2]), (eye[1] + eye[3])
if (rightmost_eye is None) or (x < rightmost_eye.x):
rightmost_eye = Eye(x, y, x2, y2)
###############################################################
####### Extract the image of the rightmost eye ################
eye_image = None
if rightmost_eye is not None:
eye_image = image[rightmost_eye.y:rightmost_eye.y2, rightmost_eye.x:rightmost_eye.x2]
###############################################################
### To assist in edge detection, try to "black out" sclera ####
binary_eye_image = None
if eye_image is not None:
eye_histogram = [0]*256
eye_image = cv2.cvtColor(eye_image, cv2.COLOR_RGB2GRAY)
for i in xrange(256):
value_count = (eye_image == i).sum()
eye_histogram[i] = value_count
count = 0
index = 255
while count < (eye_image.size*3/4):
count += eye_histogram[index]
index -= 1
quarter_threshold = index
#Multiply all parts of eye above bottom 1/4 brightness by 0
#Might not work on people with light irises. Have not tried.
binary_eye_image = cv2.equalizeHist((eye_image < quarter_threshold) * eye_image)
###############################################################
####### Look for circle (the iris). Save coordinates. ########
relative_iris_coordinates = None
if binary_eye_image is not None:
eye_circles = cv2.HoughCircles(binary_eye_image, cv2.HOUGH_GRADIENT, 3, 500, maxRadius = binary_eye_image.shape[0]/5)
if eye_circles is not None:
#Usually gets the job done. Messy.
circle = eye_circles[0][0]
relative_iris_coordinates = (circle[0], circle[1])
###############################################################
######### Put blue dot on eye in big picture ##################
absolute_iris_coordinates = None
if relative_iris_coordinates is not None and rightmost_eye is not None:
absolute_iris_coordinates = (int(relative_iris_coordinates[0]+rightmost_eye.x), int(relative_iris_coordinates[1]+rightmost_eye.y))
cv2.circle(image_to_show, absolute_iris_coordinates, 5, (255,0,0), thickness=10)
###############################################################
####### Extract image of iris (and some surrounding) ##########
iris_image = None
if absolute_iris_coordinates is not None:
x = absolute_iris_coordinates[0]
y = absolute_iris_coordinates[1]
#Should find a way to make these numbers adaptable.
#It really messes things up when these arbitrary numbers don't work with
#whatever image size or eye distance is actually being used.
#YOU, DEAR READER, MUST CHANGE THESE FOR YOUR CAMERA
#These numbers describe the guestimated shape of a captured image of an iris.
#This program makes no effort to automatically find the size of the iris in
#the captured image of the iris
w = 60
h = 60
iris_image = photo[y-h:y+h,x-w:x+w]
iris_image_to_show = cv2.resize(iris_image, (iris_image.shape[1]*2, iris_image.shape[0]*2))
image_to_show[0:iris_image_to_show.shape[0], 00:00+iris_image_to_show.shape[1]] = iris_image_to_show
###############################################################
### Draw blue circle around iris. Draw green around pupil #####
#Also, if the pupil and iris seem to be sensible shapes/sizes,
#return the current iris_image (picture of the iris+surroundings)
iris_picture = None
if iris_image is not None:
iris_gray = cv2.cvtColor(iris_image, cv2.COLOR_RGB2GRAY)
iris_circles_image = iris_image.copy()
iris_circles = cv2.HoughCircles(iris_gray, cv2.HOUGH_GRADIENT, 2, 100)
if iris_circles is not None:
circle=iris_circles[0][0]
cv2.circle(iris_circles_image, (circle[0], circle[1]), circle[2], (255,0,0), thickness=2)
pupil_coords = pupil_detect.find_pupil(iris_gray)
if pupil_coords is not None:
cv2.circle(iris_circles_image, pupil_coords[:2], pupil_coords[2], (0,255,0),4)
if iris_circles is not None and pupil_coords is not None:
ic = iris_circles[0][0]
pc = pupil_coords
#Check if pupil is within iris
if abs(ic[0]-pc[0])<ic[2] and abs(ic[1]-pc[1])<ic[2] and pc[2]<ic[2]:
iris_picture = iris_circles_image
iris_circles_to_show = cv2.resize(iris_circles_image, (iris_circles_image.shape[1]*2,iris_circles_image.shape[0]*2))
image_to_show[0:iris_circles_to_show.shape[0], 200:200+iris_circles_to_show.shape[1]] = iris_circles_to_show
###############################################################
cv2.imshow('Image', image_to_show)
if cv2.waitKey(10) > 0: #If we got a key press in less than 10ms
#Also, cv2 has some weirdness where the image won't update without a waitKey()
return True, iris_picture
return False, iris_picture
