Tracks the color red. Crude and ineffective. LOT of room for improvement

tracker.py

import cv2,math
import time
import numpy as np
from pymouse import PyMouse
class ColourTracker:
    def __init__(self):
        cv2.namedWindow("colourTrackerWindow",cv2.CV_WINDOW_AUTOSIZE)
        cv2.namedWindow("alternateWindow",cv2.CV_WINDOW_AUTOSIZE)
        self.capture=cv2.VideoCapture(1)
        self.scale_down=1
        self.m=PyMouse()
        time.sleep(5)
    def run(self):
        while True:
            f,orig_img=self.capture.read()
            orig_img2=cv2.flip(orig_img,1)
            img=cv2.GaussianBlur(orig_img,(5,5),0)
            #img=cv2.resize(img,(img.shape[0]/self.scale_down,img.shape[1]/self.scale_down))
            img=cv2.cvtColor(img,cv2.COLOR_BGR2HSV)
            red_lower=np.array([0,150,0],np.uint8)
            red_upper=np.array([5,255,255],np.uint8)
            red_binary=cv2.inRange(img,red_lower,red_upper)
            dilation=np.ones((15,15),"uint8")
            red_binary=cv2.dilate(red_binary,dilation)

            #red_binary2=red_binary     Because contours modify the original image
            contours,hierarchy=cv2.findContours(red_binary,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
            max_area=0
            largest_contour=None
            #term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 )
            #track_window=(0,0,100,100)
            #track_box,track_window=cv2.CamShift(red_binary,track_window,term_crit)

            #print track_box
            for idx,contour in enumerate(contours):
                

                area=cv2.contourArea(contour.astype('int'))
                #area=0
                if area>max_area:
                    largest_contour=contour
                if not largest_contour==None:
                    moment=cv2.moments(largest_contour)
                    if moment["m00"]>1000/self.scale_down:
                        (x,y),radius=cv2.minEnclosingCircle(largest_contour)
                        center=(int(x),int(y))
                        center_x=center[0]
                        center_y=center[1]
                        radius=int(radius)

                        cv2.circle(orig_img,(center[0]*self.scale_down,center[1]*self.scale_down),radius*self.scale_down,(0,255,0),2)
                        
                        self.mouse_scale_x=1376/orig_img.shape[0]
                        self.mouse_scale_y=1376/orig_img.shape[1]
                        print orig_img.shape[0],orig_img.shape[1]

                        if center_x<200:
                            self.m.release(1376-center_x*self.mouse_scale_x,center_y*self.mouse_scale_y)
                            center_x=200/self.mouse_scale_x
                        elif center_x>1200:
                            self.m.release(1376-center_x*self.mouse_scale_x,center_y*self.mouse_scale_y)
                            center_x=1200/self.mouse_scale_x
                        if center_y<200:
                            self.m.release(1376-center_x*self.mouse_scale_x,center_y*self.mouse_scale_y)
                            center_y=200/self.mouse_scale_y
                        self.m.press(1376-center_x*self.mouse_scale_x,center_y*self.mouse_scale_y)
                        

            cv2.imshow('colourTrackerWindow',orig_img)
            cv2.imshow('alternateWindow',red_binary)
            
            if cv2.waitKey(2)==27:
                break

colour_tracker=ColourTracker()
colour_tracker.run()