import numpy as np
import cv2
import time
ESC=27
camera = cv2.VideoCapture(0)
orb = cv2.ORB_create()
bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)

imgTrainColor=cv2.imread('/home/shar/q11.jpg')
imgTrainGray = cv2.cvtColor(imgTrainColor, cv2.COLOR_BGR2GRAY)

kpTrain = orb.detect(imgTrainGray,None)
kpTrain, desTrain = orb.compute(imgTrainGray, kpTrain)

firsttime=True

while True:

    ret, imgCamColor = camera.read()
    imgCamGray = cv2.cvtColor(imgCamColor, cv2.COLOR_BGR2GRAY)
    kpCam = orb.detect(imgCamGray,None)
    kpCam, desCam = orb.compute(imgCamGray, kpCam)
    matches = bf.match(desCam,desTrain)
    good = []
    for m,n in matches:
        if m.distance < 0.5*n.distance:
            good.append(m)

    if firsttime==True:
        h1, w1 = imgCamColor.shape[:2]
        h2, w2 = imgTrainColor.shape[:2]
        nWidth = w1+w2
        nHeight = max(h1, h2)
        hdif = (h1-h2)/2
        firsttime=False

    result = np.zeros((nHeight+1, nWidth+1, 3), np.uint8)
    result[hdif:hdif+h2, :w2] = imgTrainColor
    result[:h1, w2:w1+w2] = imgCamColor

    for i in range(len(matches)):
        pt_a=(int(kpTrain[matches[i].trainIdx].pt[0]), int(kpTrain[matches[i].trainIdx].pt[1]+hdif))
        pt_b=(int(kpCam[matches[i].queryIdx].pt[0]+w2), int(kpCam[matches[i].queryIdx].pt[1]))
        cv2.line(result, pt_a, pt_b, (255, 0, 0))

    cv2.imshow('Camara', result)

    key = cv2.waitKey(20)
    if key == ESC:
        break

cv2.destroyAllWindows()
camera.release()