help in shape and color detection in python opencv

edit

Hi i am a beginner.. For the pyrhon code below it does colour and object detection.. how do i add shape detection to it?? i mean i want to detect color and shape of the object and get the centroid.. My aim.. Plz help.. thanks in advance..

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import cv2, math
import numpy as np
class ColourTracker:
      def __init__(self):
          cv2.namedWindow("ColourTrackerWindow", cv2.CV_WINDOW_AUTOSIZE)
          self.capture = cv2.VideoCapture(0)
          self.scale_down = 4
      def run(self):
          while True:
              f, orig_img = self.capture.read()
              #orig_img = cv2.flip(orig_img, 1)
              img = cv2.GaussianBlur(orig_img, (5,5), 0)
              #laplacian = cv2.Laplacian(orig_img,cv2.CV_64F)
              sobelx = cv2.Sobel(orig_img,cv2.CV_64F,1,0,ksize=5)
              sobely = cv2.Sobel(orig_img,cv2.CV_64F,0,1,ksize=5)
              img = cv2.cvtColor(orig_img, cv2.COLOR_BGR2HSV)
              img = cv2.resize(img, (len(orig_img[0]) / self.scale_down, len(orig_img) / self.scale_down))
          boundaries = [([0, 150, 150], [5, 255, 255]),
                            ([40, 80, 10], [255, 255, 255]),
                            ([190, 150, 100], [255, 255, 255])]
              for (lower, upper) in boundaries:
                              lower = np.array(lower,np.uint8)
                              upper = np.array(upper,np.uint8)
                              binary = cv2.inRange(img, lower, upper)
                              dilation = np.ones((15, 15), "uint8")
                              binary = cv2.dilate(binary, dilation)
                              #edge = cv2.Canny(red_binary,200,300,apertureSize = 3)
                              contours, hierarchy = cv2.findContours(binary, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
                              max_area = 0
                              largest_contour = None
                              for idx, contour in enumerate(contours):
                                  area = cv2.contourArea(contour)
                                  if area > max_area:
                                      max_area = area
                                      largest_contour = contour
                                      if not largest_contour == None:
                                          moment = cv2.moments(largest_contour)
                                          if moment["m00"] > 1000 / self.scale_down:
                                              rect = cv2.minAreaRect(largest_contour)
                                              rect = ((rect[0][0] * self.scale_down, rect[0][1] * self.scale_down), (rect[1][0] * self.scale_down, rect[1][1] * self.scale_down), rect[2])
                                              box = cv2.cv.BoxPoints(rect)
                                              box = np.int0(box)
                                              cv2.drawContours(orig_img,[box], 0, (0, 0, 255), 2)
                                              cv2.imshow("ColourTrackerWindow", orig_img)
                                              if cv2.waitKey(20) == 27:
                                                  cv2.destroyWindow("ColourTrackerWindow")
                                                  self.capture.release()
                                                  break
if __name__ == "__main__":
   colour_tracker = ColourTracker()
   colour_tracker.run()