In [1]:

    

import cv2
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
cv2.ocl.setUseOpenCL(False)


    

In [2]:

    

img1 = cv2.imread('opencv-feature-matching-template.jpg', 0)
img2 = cv2.imread('opencv-feature-matching-image.jpg', 0)


    

In [3]:

    

plt.imshow(img1, cmap='gray')
plt.show()


    

In [4]:

    

plt.imshow(img2, cmap='gray')
plt.show()


    

In [5]:

    

orb = cv2.ORB_create()

kp1, des1 = orb.detectAndCompute(img1, None)
kp2, des2 = orb.detectAndCompute(img2, None)

bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck = True)

matches = bf.match(des1,des2)
matches = sorted(matches, key = lambda x:x.distance)

img3 = cv2.drawMatches(img1,kp1,img2,kp2, matches[:12], None, flags=2)
plt.figure(figsize=(15,15))
plt.imshow(img3)
plt.show()


    

In [6]:

    

img10 = cv2.drawKeypoints(img1, kp1, img1, color=(0,255,0), flags=0)
plt.figure(figsize=(15,15))
plt.imshow(img10)
plt.show()


    

In [7]:

    

img20 = cv2.drawKeypoints(img2, kp2, img2, color=(0,255,0), flags=0)
plt.figure(figsize=(15,15))
plt.imshow(img20)
plt.show()