if not args.diameter == None:
bound = cv2.minAreaRect(cnts[0])
bound = cv2.boxPoints(bound)
bound = numpy.array(bound, dtype="int")
bound = perspective.order_points(bound)
cv2.drawContours(frame2, [bound.astype("int")], -1, RED, 2)
(tl, tr, br, bl) = bound
tltrX = int((tl[0] + tr[0]) * 0.5)
tltrY = int((tl[1] + tr[1]) * 0.5)
blbrX = int((bl[0] + br[0]) * 0.5)
blbrY = int((bl[1] + br[1]) * 0.5)
cv2.line(frame2, (tltrX, tltrY), (blbrX, blbrY), BLUE, 2)
distance = numpy.sqrt(((tltrX - blbrX)**2) +
((tltrY - blbrY)**2))
ratio = args.diameter / distance
tracker.diameter_ratio = ratio
diameter_unit = "mm"
if args.debug:
cv2.imwrite("test.bmp", frame2)
# process background substraction
blur = cv2.medianBlur(frame, 7) # median blur to remove noise
foreground = cv2.absdiff(blur, background) # subtract background
foreground = cv2.cvtColor(
foreground,
cv2.COLOR_BGR2GRAY) # turn into grayscale channel cv_8uc1
result = cv2.threshold(foreground, args.threshold, 255,
cv2.THRESH_BINARY)[1] # threshold
# contour tracking
contours, hierachy = cv2.findContours(result, cv2.RETR_LIST,
