Open cxb1998 opened 4 months ago
Or give some detailed notes
I get result in demo_fundamental.py, kpts1, kpts2:
![Uploading Snipaste_2024-07-17_17-55-51.png…]()
I get result in demo_fundamental.py, kpts1, kpts2:
hello! Your image seems to be damaged, can you upload it again? Also, are the results you get referring to the custom points?
I get result in demo_fundamental.py, kpts1, kpts2:
hello! Your image seems to be damaged, can you upload it again? Also, are the results you get referring to the custom points?
I add this code to demo_fundamental.py, you can try.
img1 = cv2.imread(im1_path)
img2 = cv2.imread(im2_path)
for i,v in enumerate(mask):
if v[0]==1:
m1 = kpts1[i].cpu().numpy().astype('int32')
m2 = kpts2[i].cpu().numpy().astype('int32')
cv2.circle(img1, m1, 5, (0,0,255), -1)
cv2.circle(img2, m2, 5, (0,0,255), -1)
cv2.imwrite('/data/tjh/RoMa/output/sacre-1.png', img1)
cv2.imwrite('/data/tjh/RoMa/output/sacre-2.png', img2)
I am also eager to know how to generate such images using match_keypoints?
Hi, Im away for the summer, will get back with some demos start of september.
Regarding pic above, use the match_keypoint method for your keypoints of choice and use e.g. opencv to visualize.
你好,我今年夏天不在家,九月初会带着一些演示回来。 Special look forward to, excellent algorithm let people worship. I hope to see a detailed explanation then, thank you
I found that the algorithm did not work well for small objects and was not rotation invariant. Is there any solution?
Can you provide a demo for the use of custom point matching? thanks