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
It seems superpoint+superglue w/ HLOC estimates most camera orientations incorrectly by 90 degrees error about the +z camera axis (roll). I don't see any such issue with vanila COLMAP. I wonder if you could try reproducing or investigating this result?
Thanks again!
The text was updated successfully, but these errors were encountered:
sfm-user-1
changed the title
Superpoint + superglue w/ pycolmap give 90 degree camera orientation error
Superpoint + superglue w/ hloc give 90 degree camera orientation error
Jan 31, 2024
Found the culprit - PR #373 solves this bug. Unfortunately SuperPoint+SuperGlue cannot match 90-degree rotated images, so for now hloc registers only 26/35 images (those in portrait mode). Fixing this is pretty high on our priority list. For now I suggest baking the EXIF rotation into the images by reading+writing them with OpenCV:
import cv2
for p in input_dir.iterdir():
cv2.imwrite(str(output_dir / p.name), cv2.imread(str(p)))
This prevents COLMAP from sharing intrinsics between rotated images but the negative impact should be negligible.
Hi, thanks for making this repo and the notebooks.
I tried out the superpoint+superglue+colmap notebook here
https://github.com/cvg/Hierarchical-Localization/blob/master/pipeline_SfM.ipynb
using the 35-image dataset here: http://vision.maths.lth.se/calledataset/de_guerre/de_guerre.zip
It seems superpoint+superglue w/ HLOC estimates most camera orientations incorrectly by 90 degrees error about the +z camera axis (roll). I don't see any such issue with vanila COLMAP. I wonder if you could try reproducing or investigating this result?
Thanks again!
The text was updated successfully, but these errors were encountered: