def run(self):
while True:
img = self.capture.read()
#blur the source image to reduce color noise
cv2.blur(img, img, 3)
#convert the image to hsv(Hue, Saturation, Value) so its
#easier to determine the color to track(hue)
hsv_img = cv2.CreateImage(cv2.GetSize(img), 8, 3)
cv2.CvtColor(img, hsv_img, cv2.CV_BGR2HSV)
#limit all pixels that don't match our criteria, in this case we are
#looking for purple but if you want you can adjust the first value in
#both turples which is the hue range(120,140). OpenCV uses 0-180 as
#a hue range for the HSV color model
greenLower = (20, 190, 165)
greenUpper = (30, 225, 220)
thresholded_img = cv2.CreateImage(cv2.GetSize(hsv_img), 8, 1)
cv2.InRangeS(hsv_img, greenLower, greenUpper, thresholded_img)
#determine the objects moments and check that the area is large
#enough to be our object
moments = cv2.Moments(thresholded_img, 0)
area = cv2.GetCentralMoment(moments, 0, 0)
#there can be noise in the video so ignore objects with small areas
if (area > 100000):
#determine the x and y coordinates of the center of the object
#we are tracking by dividing the 1, 0 and 0, 1 moments by the area
x = cv2.GetSpatialMoment(moments, 1, 0) / area
y = cv2.GetSpatialMoment(moments, 0, 1) / area
#print 'x: ' + str(x) + ' y: ' + str(y) + ' area: ' + str(area)
#create an overlay to mark the center of the tracked object
overlay = cv2.CreateImage(cv2.GetSize(img), 8, 3)
cv2.Circle(overlay, (x, y), 2, (255, 255, 255), 20)
cv2.Add(img, overlay, img)
#add the thresholded image back to the img so we can see what was
#left after it was applied
cv2.Merge(thresholded_img, None, None, None, img)
#display the image
cv2.ShowImage(color_tracker_window, img)
if cv2.WaitKey(10) == 27:
break
def getPupil(frame): pupilImg = cv.CreateImage(cv.GetSize(frame), 8, 1) cv.InRangeS(frame, (30,30,30), (80,80,80), pupilImg) contours = cv.FindContours(pupilImg, cv.CreateMemStorage(0), mode = cv.CV_RETR_EXTERNAL) del pupilImg pupilImg = cv.CloneImage(frame) while contours: moments = cv.Moments(contours) area = cv.GetCentralMoment(moments,0,0) if (area > 50): pupilArea = area x = cv.GetSpatialMoment(moments,1,0)/area y = cv.GetSpatialMoment(moments,0,1)/area pupil = contours global centroid centroid = (int(x),int(y)) cv.DrawContours(pupilImg, pupil, (0,0,0), (0,0,0), 2, cv.CV_FILLED) break contours = contours.h_next() return (pupilImg)
def run(self):
#initiate font
font = cv.InitFont(cv.CV_FONT_HERSHEY_SIMPLEX, 1, 1, 0, 3, 8)
# instantiate images
hsv_img = cv.CreateImage(cv.GetSize(cv.QueryFrame(self.capture)), 8, 3)
threshold_img1 = cv.CreateImage(cv.GetSize(hsv_img), 8, 1)
threshold_img1a = cv.CreateImage(cv.GetSize(hsv_img), 8, 1)
threshold_img2 = cv.CreateImage(cv.GetSize(hsv_img), 8, 1)
i = 0
writer = cv.CreateVideoWriter('angle_tracking.avi', cv.CV_FOURCC('M', 'J', 'P', 'G'), 30, cv.GetSize(hsv_img), 1)
while True:
# capture the image from the cam
img = cv.QueryFrame(self.capture)
# convert the image to HSV
cv.CvtColor(img, hsv_img, cv.CV_BGR2HSV)
# threshold the image to isolate two colors
cv.InRangeS(hsv_img, (165, 145, 100), (250, 210, 160), threshold_img1) # red
cv.InRangeS(hsv_img, (0, 145, 100), (10, 210, 160), threshold_img1a) # red again
cv.Add(threshold_img1, threshold_img1a, threshold_img1) # this is combining the two limits for red
cv.InRangeS(hsv_img, (105, 180, 40), (120, 260, 100), threshold_img2) # blue
# determine the moments of the two objects
threshold_img1 = cv.GetMat(threshold_img1)
threshold_img2 = cv.GetMat(threshold_img2)
moments1 = cv.Moments(threshold_img1, 0)
moments2 = cv.Moments(threshold_img2, 0)
area1 = cv.GetCentralMoment(moments1, 0, 0)
area2 = cv.GetCentralMoment(moments2, 0, 0)
# initialize x and y
x1, y1, x2, y2 = (1, 2, 3, 4)
coord_list = [x1, y1, x2, y2]
for x in coord_list:
x = 0
# there can be noise in the video so ignore objects with small areas
if (area1 > 200000):
# x and y coordinates of the center of the object is found by dividing the 1,0 and 0,1 moments by the area
x1 = int(cv.GetSpatialMoment(moments1, 1, 0) / area1)
y1 = int(cv.GetSpatialMoment(moments1, 0, 1) / area1)
# draw circle
cv.Circle(img, (x1, y1), 2, (0, 255, 0), 20)
# write x and y position
cv.PutText(img, str(x1) +', '+str(y1), (x1, y1 + 20), font, 255) # Draw the text
if (area2 > 100000):
# x and y coordinates of the center of the object is found by dividing the 1,0 and 0,1 moments by the area
x2 = int(cv.GetSpatialMoment(moments2, 1, 0) / area2)
y2 = int(cv.GetSpatialMoment(moments2, 0, 1) / area2)
# draw circle
cv.Circle(img, (x2, y2), 2, (0, 255, 0), 20)
cv.PutText(img, str(x2) +', '+str(y2), (x2, y2 + 20), font, 255) # Draw the text
cv.Line(img, (x1, y1), (x2, y2), (0, 255, 0), 4, cv.CV_AA)
# draw line and angle
cv.Line(img, (x1, y1), (cv.GetSize(img)[0], y1), (100, 100, 100, 100), 4, cv.CV_AA)
x1 = float(x1)
y1 = float(y1)
x2 = float(x2)
y2 = float(y2)
angle = int(math.atan((y1 - y2) / (x2 - x1)) * 180 / math.pi)
cv.PutText(img, str(angle), (int(x1) + 50, (int(y2) + int(y1)) / 2), font, 255)
# cv.WriteFrame(writer,img)
# display frames to users
cv.ShowImage('Target', img)
cv.ShowImage('Threshold1', threshold_img1)
cv.ShowImage('Threshold2', threshold_img2)
cv.ShowImage('hsv', hsv_img)
# Listen for ESC or ENTER key
c = cv.WaitKey(7) % 0x100
if c == 27 or c == 10:
break
cv.DestroyAllWindows()