# 需要導入模塊: import cv [as 別名]

# 或者: from cv import CvtColor [as 別名]

def run(self):

while True:

img = cv.QueryFrame( self.capture )

t1 = time.time()

#blur the source image to reduce color noise

cv.Smooth(img, img, cv.CV_BLUR, 3);

#convert the image to hsv(Hue, Saturation, Value) so its

#easier to determine the color to track(hue)

hsv_img = cv.CreateImage(cv.GetSize(img), 8, 3)

cv.CvtColor(img, hsv_img, cv.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

thresholded_img = cv.CreateImage(cv.GetSize(hsv_img), 8, 1)

# White

sensitivity = 10

cv.InRangeS(hsv_img, (0, 0, 255-sensitivity), (255, sensitivity, 255), thresholded_img)

# Red

#cv.InRangeS(hsv_img, (0, 150, 0), (5, 255, 255), thresholded_img)

# Blue

#cv.InRangeS(hsv_img, (100, 50, 50), (140, 255, 255), thresholded_img)

# Green

#cv.InRangeS(hsv_img, (40, 50, 50), (80, 255, 255), thresholded_img)

#determine the objects moments and check that the area is large

#enough to be our object

mat=cv.GetMat(thresholded_img)

moments = cv.Moments(mat, 0)

area = cv.GetCentralMoment(moments, 0, 0)

#there can be noise in the video so ignore objects with small areas

if(area > 10000):

#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 = cv.GetSpatialMoment(moments, 1, 0)/area

y = cv.GetSpatialMoment(moments, 0, 1)/area

x = int(round(x))

y = int(round(y))

#create an overlay to mark the center of the tracked object

overlay = cv.CreateImage(cv.GetSize(img), 8, 3)

cv.Circle(overlay, (x, y), 2, (255, 255, 255), 20)

cv.Add(img, overlay, img)

#add the thresholded image back to the img so we can see what was

#left after it was applied

t2 = time.time()

cv.Merge(thresholded_img, None, None, None, img)

print "detection time = %gs x=%d,y=%d" % ( round(t2-t1,3) , x, y)

#display the image

cv.ShowImage(color_tracker_window, img)

if cv.WaitKey(10) == 27:

break