Image_tracker.py

import cv2
import numpy as np

cap = cv2.VideoCapture(0)
imgTarget=cv2.imread("wheel.jpg")
advtImg = cv2.imread("wheeladvt.jpg")
hT,wT,cT = imgTarget.shape
advtImg = cv2.resize(advtImg,(wT,hT))

orb = cv2.ORB_create(nfeatures=1000)
kp1,desc1 = orb.detectAndCompute(imgTarget,None)

while True:
    success,imgWebcam = cap.read()
    imgAug = imgWebcam.copy()
    kp2,desc2 = orb.detectAndCompute(imgWebcam,None)

    bf = cv2.BFMatcher()
    matches=bf.knnMatch(desc1,desc2,k=2)

    good=[]

    for m,n in matches:
        if(m.distance < 0.75 *n.distance):
            good.append(m)

#     imgFeatchers = cv2.drawMatches(imgTarget,kp1,imgWebcam,kp2,good,None,flags=2)
    detected = False

    if len(good)>20:
        detected=True
        srcPoints = np.float32([kp1[m.queryIdx].pt for m in good]).reshape(-1,1,2)
        dstPoints = np.float32([kp2[m.trainIdx].pt for m in good]).reshape(-1,1,2)

        matrix,mask = cv2.findHomography(srcPoints,dstPoints,cv2.RANSAC,5)

        pts = np.float32([[0,0],[0,hT],[wT,hT],[wT,0]]).reshape(-1,1,2)
        dst = cv2.perspectiveTransform(pts,matrix)

        img2 = cv2.polylines(imgWebcam,[np.int32(dst)],True,(255,0,255),3)
        imgWarp= cv2.warpPerspective(advtImg,matrix,(imgWebcam.shape[1],imgWebcam.shape[0]))

        maskNew=np.zeros((imgWebcam.shape[0],imgWebcam.shape[1]),np.uint8)
        cv2.fillPoly(maskNew,[np.int32(dst)],(255,255,255))

        maskInv = cv2.bitwise_not(maskNew)
        imgAug = cv2.bitwise_and(imgAug,imgAug,mask=maskInv)
        imgAug = cv2.bitwise_or(imgWarp,imgAug)
        cv2.imshow('Aurgumented',imgAug)
    if detected:
         cv2.imshow('Aurgumented',imgAug)
    else:
        cv2.imshow('origianal',imgWebcam)
    cv2.waitKey(1)