Created
January 10, 2019 00:47
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import numpy as np | |
import cv2 | |
#import random | |
if __name__ == '__main__': | |
img1 = cv2.imread('Univ4.jpg') | |
gray1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY) | |
img2 = cv2.imread('Univ3.jpg') | |
gray2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY) | |
dst = gray1 | |
sift = cv2.xfeatures2d.SIFT_create() | |
kp1, desc1 = sift.detectAndCompute(gray1, None) | |
kp2, desc2 = sift.detectAndCompute(gray2, None) | |
bf = cv2.BFMatcher() | |
matches = bf.knnMatch(desc1, desc2, k=2) | |
good_matches = [] | |
# Apply ratio test | |
ratio = 0.5 | |
pt1 = [] | |
pt2 = [] | |
for m, n in matches: | |
if m.distance < ratio * n.distance: | |
good_matches.append([m]) | |
pt1.append(kp1[m.queryIdx].pt) | |
pt2.append(kp2[m.trainIdx].pt) | |
''' | |
for index in range(len(pt1)): | |
b = random.randint(0, 255) | |
g = random.randint(0, 255) | |
r = random.randint(0, 255) | |
cv2.circle(img1, (int(pt1[index][0]), int(pt1[index][1])), 3, (b, g, r), thickness=-1, lineType=cv2.LINE_AA) | |
cv2.circle(img2, (int(pt2[index][0]), int(pt2[index][1])), 3, (b, g, r), thickness=-1, lineType=cv2.LINE_AA) | |
''' | |
draw = cv2.drawMatchesKnn(img1, kp1, img2, kp2, good_matches, None, flags=2) | |
cv2.imshow('draw', draw) | |
cv2.waitKey(0) | |
cv2.destroyAllWindows() |
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