shape detection project using python openCV modul

source code 

import cv2
import numpy as np


def stackImages(scale,imgArray):
    rows = len(imgArray)
    cols = len(imgArray[0])
    rowsAvailable = isinstance(imgArray[0], list)
    width = imgArray[0][0].shape[1]
    height = imgArray[0][0].shape[0]
    if rowsAvailable:
        for x in range(0, rows):
            for y in range(0, cols):
                if imgArray[x][y].shape[:2] == imgArray[0][0].shape[:2]:
                    imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)
                else:
                    imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]),
                                                None, scale, scale)
                if len(imgArray[x][y].shape) == 2: imgArray[x][y] = cv2.cvtColor(imgArray[x][y], cv2.COLOR_GRAY2BGR)
        imageBlank = np.zeros((height, width, 3), np.uint8)
        hor = [imageBlank] * rows
        hor_con = [imageBlank] * rows
        for x in range(0, rows):
            hor[x] = np.hstack(imgArray[x])
        ver = np.vstack(hor)
    else:
        for x in range(0, rows):
            if imgArray[x].shape[:2] == imgArray[0].shape[:2]:
                imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)
            else:
                imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None, scale, scale)
            if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)
        hor = np.hstack(imgArray)
        ver = hor
    return ver

def getcounters(img):
    countours,hierarchy=cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
    for cnt in countours:
        area=cv2.contourArea(cnt)
        print (area)
        if area>500:
            cv2.drawContours(imgcountour,cnt,-1,(255,0,0),3)
            peri=cv2.arcLength(cnt,True)
            print(peri)
            approx=cv2.approxPolyDP(cnt ,0.02*peri,True)
            print(approx)
            print(len(approx))
            objcor=len(approx)
            x,y,w,h=cv2.boundingRect(approx)
            if objcor==3:
                objectType=f"triangle {area}"
            elif objcor==4:
                aspectRatio=w/float(h)
                if aspectRatio>0.95 and aspectRatio<1.05 :
                    objectType=f"Square {area}"
                else:
                    objectType=f"Rectangle {area}"
            elif objcor>4:
                objectType=f"circle {area}"
            else:
                objectType="not define"

            cv2.rectangle(imgcountour,(x,y),(x+w,y+h),(0,255,0),2)

            cv2.putText(imgcountour,objectType,(x+(w//2)-10,y+(h//2)-10),cv2.FONT_HERSHEY_COMPLEX,0.5,(0,0,0),2)


#path='shape.jpg'

#img=cv2.imread(path)

cap=cv2.VideoCapture(0)
cap.set(3,1080)      #width  (chanel number,size)
cap.set(4,800)      #height
cap.set(10,100)     #brightness
while True:
    sucess,img=cap.read()


    imgcountour= img.copy()

    imgGray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    imgBlur = cv2.GaussianBlur(imgGray,(7,7),1)
    imgCanny=cv2.Canny(imgBlur,50,50)
    getcounters(imgCanny)

    imgBlank=np.zeros_like(img)

   # stackimg=stackImages(0.8,([img],[imgcountour]))
    cv2.imshow("image ",imgcountour)
    #cv2.imshow("stack image ",stackimg)
    #cv2.waitKey(0)
    #cv2.imshow("video", img)

    if cv2.waitKey(1) & 0xff == ord("q"):
        break

python MCQ