text: import imutils
  import cv2
  # redlower(HueLower,SaturationLower,ValueLower)
  redlower = (157, 93,203)# low scale of red color value
  redupper = (179,255,255)# high scale of red color value
  camera=cv2.VideoCapture(0)
  while True:
      (grabbed, frame)=camera.read()
      frame=imutils.resize(frame,width=600)
      blur=cv2.GaussianBlur(frame,(11,11),0)
      hsv = cv2.cvtColor(blur,cv2.COLOR_BGR2HSV)#converting image color to hsv and storing the value
      mask=cv2.inRange(hsv,redlower,redupper)#comaprng hsv value of image with the other parameters
      mask=cv2.erode(mask,None,iterations=2)# this filter is used to remove noise in the image
      mask=cv2.dilate(mask,None,iterations=2)#this filter is used to remove noise in the image
      cnts=cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)[-2]
      center=None
      if len(cnts) > 0:
          c=max(cnts, key=cv2.contourArea)# find maximum contour area
          ((x,y),radius)=cv2.minEnclosingCircle(c)# used to create an minimum enclosing circle around the object absed on the coordinates ,radius
          M=cv2.moments(c)
          center=(int(M["m10"]/M["m00"]),int(M["m01"]/M["m00"]))# finding the center of the minimum enclosing circle(x,y)
          if radius > 10:
              cv2.circle(frame,(int(x),int(y)),int(radius),(0,255,255),2)# this functions specifier the coloe ,thickness boundary of minimum circle
              cv2.circle(frame,center,5,(0,0,255),-1)# this function specifies the center within the minimum circle along with its coordinates
              print(center[0],radius)
              if radius >250:
                  print("stop")
              else:
                  if(center[0]<150):
                      print("left")
                  elif(center[0]>450):
                      print("right")
                  elif(radius<250):
                      print("front")
                  else:
                      print("stop")
      cv2.imshow("Frame",frame)
      key=cv2.waitKey(1) & 0xFF
      if key == ord("q"):
          break
  cam.release()
  cv2.destroyAllWindows()
  