You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi,
Thanks for great work and it's really useful to remapping scene.
Please allow me simplify the own data process first:
Prepare images of scene
Run hloc to get A. db of sfm, B. matches keras model, C.pairs_info.txt(e.q. pairs-exhaustive.txt, pairs-query-netvlad50.txt)
Run pixloc to localize query image
I check the code in localizer.py, it need get the id from pairs_info.txt and sfm db
self.model3d = Model3D(paths.reference_sfm)
dbs = [self.model3d.name2id[r] for r in self.retrieval[name]]
Is that mean I have to do step 2 every time once new query image added?
The text was updated successfully, but these errors were encountered:
Thanks for your amazing work! I have the same question. Anyone have any thought on this? Is this a real-time 6 DOF pose estimation? What is the minimum inference time we can get from this approach? Thanks in advance.
@Arlen0615 It is not necessary to do all parts of step 2 to localize a new image. You only need to determine which database images are relevant for the new image.
Regarding timings: No, this is not a real-time pose estimation algorithm as it is computationally quite expensive.
Hi,
Thanks for great work and it's really useful to remapping scene.
Please allow me simplify the own data process first:
I check the code in localizer.py, it need get the id from pairs_info.txt and sfm db
self.model3d = Model3D(paths.reference_sfm)
dbs = [self.model3d.name2id[r] for r in self.retrieval[name]]
Is that mean I have to do step 2 every time once new query image added?
The text was updated successfully, but these errors were encountered: