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@soruly
Last active June 15, 2023 14:38
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Compare two images using OpenCV and SIFT in python
import cv2
import sys
import os.path
import numpy as np
def drawMatches(img1, kp1, img2, kp2, matches):
rows1 = img1.shape[0]
cols1 = img1.shape[1]
rows2 = img2.shape[0]
cols2 = img2.shape[1]
out = np.zeros((max([rows1,rows2]),cols1+cols2,3), dtype='uint8')
out[:rows1,:cols1] = np.dstack([img1])
out[:rows2,cols1:] = np.dstack([img2])
for mat in matches:
img1_idx = mat.queryIdx
img2_idx = mat.trainIdx
(x1,y1) = kp1[img1_idx].pt
(x2,y2) = kp2[img2_idx].pt
cv2.circle(out, (int(x1),int(y1)), 4, (255, 0, 0, 1), 1)
cv2.circle(out, (int(x2)+cols1,int(y2)), 4, (255, 0, 0, 1), 1)
cv2.line(out, (int(x1),int(y1)), (int(x2)+cols1,int(y2)), (255, 0, 0, 1), 1)
return out
def compare(filename1, filename2):
img1 = cv2.imread(filename1) # queryImage
img2 = cv2.imread(filename2) # trainImage
# Initiate SIFT detector
sift = cv2.SIFT()
# find the keypoints and descriptors with SIFT
kp1, des1 = sift.detectAndCompute(img1,None)
kp2, des2 = sift.detectAndCompute(img2,None)
# BFMatcher with default params
bf = cv2.BFMatcher()
matches = bf.match(des1,des2)
matches = sorted(matches, key=lambda val: val.distance)
img3 = drawMatches(img1,kp1,img2,kp2,matches[:25])
# Show the image
cv2.imshow('Matched Features', img3)
cv2.waitKey(0)
cv2.destroyWindow('Matched Features')
if len(sys.argv) != 3:
sys.stderr.write("usage: compare.py <queryImageFile> <sourceImageFile>\n")
sys.exit(-1)
compare(sys.argv[1], sys.argv[2])
@amrithmmh
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is it possible to check if say a screenshot taken by webcam is same as the sample image/images using SIFT (i amreally new to image processing so i dont really know what is best for what)

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