Image registration notebook

#%% 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))
query_img = cv.resize(query_img, dsize=(600, 950))

#%% Detect keypoints

train_img_g = cv.cvtColor(train_img, cv.COLOR_BGR2GRAY)
query_img_g = cv.cvtColor(query_img, cv.COLOR_BGR2GRAY)

# Initiate AKAZE detector
akaze = cv.AKAZE_create()

# find the keypoints and descriptors with AKAZE
train_kp, train_des = akaze.detectAndCompute(train_img_g, None)
train_img_with_kp = cv.drawKeypoints(train_img, train_kp, None)
cv.imwrite('train_kp.jpg', train_img_with_kp)

query_kp, query_des = akaze.detectAndCompute(query_img_g, None)
query_img_with_kp = cv.drawKeypoints(query_img, query_kp, None)
cv.imwrite('query_kp.jpg', query_img_with_kp)

#%% Match keypoints

# BFMatcher with default params
bf = cv.BFMatcher(cv.NORM_HAMMING)
matches = bf.knnMatch(query_des, train_des, k=2)

# Apply ratio test
good_matches = []
for m, n in matches:
    if m.distance < 0.75 * n.distance:
        good_matches.append([m])

img_with_matches = cv.drawMatchesKnn(query_img, query_kp, train_img, train_kp, good_matches, None,
                         flags=cv.DrawMatchesFlags_NOT_DRAW_SINGLE_POINTS)
cv.imwrite('matches.jpg', img_with_matches)

#%% Warping

# Select good matched keypoints
train_matched_pts = np.float32([train_kp[m[0].trainIdx].pt for m in good_matches])
query_matched_pts = np.float32([query_kp[m[0].queryIdx].pt for m in good_matches])

# Compute homography
H, status = cv.findHomography(query_matched_pts, train_matched_pts, cv.RANSAC, 5.0)

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

cv.imwrite('warped_img.jpg', warped_image)

#%% Superposition
gray_warped_img = cv.cvtColor(warped_image, cv.COLOR_BGR2GRAY)
images_superposition = np.dstack((train_img_g, gray_warped_img, train_img_g))

cv.imwrite("superposition.jpg", images_superposition)