emnak

#%% Read and resize images
import numpy as np
import cv2 as cv

# Read images
train_img = cv.imread('train.png')
query_img = cv.imread('query.png')

# Resize images
train_img = cv.resize(train_img, dsize=(600, 950))

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# Select good matched keypoints
ref_matched_kpts = np.float32([kp1[m[0].queryIdx].pt for m in good_matches])
sensed_matched_kpts = np.float32([kp2[m[0].trainIdx].pt for m in good_matches])

# Compute homography
H, status = cv.findHomography(sensed_matched_kpts, ref_matched_kpts, cv.RANSAC,5.0)

# Warp image
warped_image = cv.warpPerspective(img2, H, (img2.shape[1], img2.shape[0]))
            

emnak

import numpy as np
import cv2 as cv
import matplotlib.pyplot as plt

img1 = cv.imread('image1.jpg', cv.IMREAD_GRAYSCALE)  # referenceImage
img2 = cv.imread('image2.jpg', cv.IMREAD_GRAYSCALE)  # sensedImage

# Initiate AKAZE detector
akaze = cv.AKAZE_create()
# Find the keypoints and descriptors with SIFT

emnak

import numpy as np
import cv2 as cv

img = cv.imread('image.jpg')
gray= cv.cvtColor(img, cv.COLOR_BGR2GRAY)

akaze = cv.AKAZE_create()
kp, descriptor = akaze.detectAndCompute(gray, None)

img=cv.drawKeypoints(gray, kp, img)