siftFeatureMatching.py

import cv2 
import matplotlib.pyplot as plt
import time

#sift
sift = cv2.SIFT_create()

#feature matching
bf = cv2.BFMatcher(cv2.NORM_L2, crossCheck=True)


cap = cv2.VideoCapture(0)

while cap.isOpened():
    # read images

    suc, img1 = cap.read()
    img2 = img1
    #img1 = cv2.imread('pencil3.jpg')  
    #img2 = cv2.imread('pencil3.jpg') 

    start = time.time()

    img1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
    img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)

    keypoints_1, descriptors_1 = sift.detectAndCompute(img1,None)
    keypoints_2, descriptors_2 = sift.detectAndCompute(img2,None)

    matches = bf.match(descriptors_1,descriptors_2)
    matches = sorted(matches, key = lambda x:x.distance)

    end = time.time()
    totalTime = end - start

    fps = 1 / totalTime
    #print("FPS: ", fps)
    

    img3 = cv2.drawMatches(img1, keypoints_1, img2, keypoints_2, matches[:300], img2, flags=2)
    #plt.imshow(img3),plt.show()
    cv2.putText(img3, f'FPS: {int(fps)}', (20,450), cv2.FONT_HERSHEY_SIMPLEX, 1.5, (0,255,0), 2)
    cv2.imshow('SIFT', img3)

    if cv2.waitKey(5) & 0xFF == 27:
        break


cap.release()