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GrumpyZhou avatar GrumpyZhou commented on July 21, 2024

Hi @miRemid , have you solved the issue? Is it just for COTR or for all of the methods? Have you checked that whether the dataset directories are set correctly?

I would add printing lines:

match_res = matcher(im1_path, im2_path) 
print(im1_path, match_res.shape)

to the following script at L163:

image-matching-toolbox/immatch/utils/hpatches_helper.py

Lines 159 to 169 in aa07c4e

for im_idx in range(2, 7):
im2_path = os.path.join(seq_dir, '{}.ppm'.format(im_idx))
H_gt = np.loadtxt(os.path.join(seq_dir, 'H_1_{}'.format(im_idx)))
scale = np.ones(4)
# Predict matches
try:
t0 = time.time()
match_res = matcher(im1_path, im2_path)
match_time.append(time.time() - t0)
matches, p1s, p2s = match_res[0:3]

from image-matching-toolbox.

miRemid avatar miRemid commented on July 21, 2024

the problem had been solved without any change, i don't know why :)
and i find the cost of time for each item is slower than other methods, which takes 154.14s on 3090
image
anyway, the pipeline is correct

from image-matching-toolbox.

GrumpyZhou avatar GrumpyZhou commented on July 21, 2024

@miRemid That's great to hear! Regarding the runtime of COTR, yes it is slower than most of the other methods. They have reported some numbers about the runtime in the paper as well.

from image-matching-toolbox.

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