Comments (1)
Thank you for bringing up the issue. This was my fault, I added a line to test the new API and forgot to delete it. This line will force the algorithm to ignore all information provided the marker and performs matching based on ICP only, which caused the misalignment shown above and make the algorithm super slow.
Also please note that register_segmented only work sometimes, if auto meshing fails, you can either run register_Segmented with meshing option turned off, and remove noise and perform meshing in meshlab. Or you can use register_scene and remove all noise manually.
Please pull the latest change and let me know if that helps. Thanks
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Related Issues (20)
- register_segmented.py result is not the same with README.md's result. HOT 2
- compute_gt_poses.py issue HOT 2
- Step 6. create_label_files.py problem HOT 1
- how to get gt.yml for my custom dataset? HOT 2
- 安装pyrealsense时报错 Error when installing pyrealsense
- Transform.npy and pose.npy Question
- Using Larger Aruco Markers
- Pipeline Problem
- my mask is not in the exact position with the object HOT 2
- wrong issue
- Succesful Method for DenseFusion HOT 7
- Issue with step 4: register_segmented.py, TypeError occurs
- Issue with step6
- NameError: name 'registration' is not defined HOT 4
- ValueError: not enough values to unpack (expected 3, got 2) HOT 1
- create_label_files HOT 2
- Question about transform.npy
- Question about compute_gt_poses.py HOT 1
- Issue about the pointcloud created
- depth_scale parameter
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