在处理了网上找到的一些代码后,(http://www.davidhampgonsalves.com/2011/05/OpenCV-Python-Color-Based-Object-Tracking)我正在尝试跟踪彩色对象。在运行代码时,我已将输入从相机更改为 AVI 文件。代码运行时,没有视频,第40行的代码,
moments = cv.Moments(thresholded_img, 0)
在参数上返回 TypeError:'ܤ'。(它基本上是一串我不明白的符号)。任何帮助将不胜感激,我将在下面完整发布源代码。非常感谢
约翰
import cv
color_tracker_window = "Color Tracker"
class ColorTracker:
def __init__(self):
cv.NamedWindow( color_tracker_window, 1 )
f = 'video.avi'
self.capture = cv.CaptureFromFile(f)
def run(self):
while True:
img = cv.QueryFrame( self.capture )
#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)
cv.InRangeS(hsv_img, (120, 80, 80), (140, 255, 255), thresholded_img)
#determine the objects moments and check that the area is large
#enough to be our object
moments = cv.Moments(thresholded_img, 0)
area = cv.GetCentralMoment(moments, 0, 0)
data = []
#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 = cv.GetSpatialMoment(moments, 1, 0)/area
y = cv.GetSpatialMoment(moments, 0, 1)/area
print 'x: ' + str(x) + ' y: ' + str(y) + ' area: ' + str(area)
data.append(x, y, area)
#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
cv.Merge(thresholded_img, None, None, None, img)
#display the image
cv.ShowImage(color_tracker_window, img)
if cv.WaitKey(10) == 27:
break
if __name__=="__main__":
color_tracker = ColorTracker()
color_tracker.run()