Comments (2)
Hi @e1339g,
This error occurs when the pose file can not be found. Did you follow the instructions in the Readme and exported the path to the dataset with
export DATA=path/to/dataset/sequences
If yes, please print the pose_path
that is passed to the load_poses
function to see what is going on.
Best regards
Benedikt
from 4dmos.
Thank you for your great work, and sharing the code.
I am trying to train my own dataset from kitti raw data. I have converted raw data to semantickitti data format using this script.
https://github.com/jbehley/point_labeler/blob/master/scripts/kitti_raw2odometry.py
However, when I tried to train the data is gives me an error "Ground truth poses are not available."
and
inv_frame0 = np.linalg.inv(poses[0])
IndexError: index 0 is out of bounds for axis 0 with size 0
My poses.txt is in same folder in velodyne and label files. And in poses.txt file each row has 12 elements. I do not quite understand why it can not read the poses.txt file. Please help me to train the data
Thank you
from 4dmos.
Related Issues (20)
- Custom visualization - mismatch data shape HOT 1
- Does using closed loop poses have a significant impact on recognition results? HOT 4
- Inference problem HOT 2
- evaluate problem HOT 14
- predict confidences when using pose
- Evaluation on 16 channel LiDAR pointcloud HOT 3
- Model adaption for Movable object segmentation HOT 1
- About the gap between testing result and validation result on SemanticKITTI HOT 5
- Docker build issue HOT 2
- Deployment HOT 7
- Does it have scan_cleaner utils like LM-Net? HOT 6
- Deploying 4DMOS on Robots HOT 6
- Results regarding Apollo HOT 2
- Performane on trained weights HOT 13
- 4DMOS in Nuscenes HOT 2
- some questions about MinkowskiEngine HOT 1
- UserWarning: GPUs can't support floating point data HOT 3
- Was able to run everything. All of a sudden, I got this error. TypeError: expected str, bytes or os.PathLike object, not NoneType" HOT 2
- Which sequence is used as the validation sequence for the Apollo dataset HOT 1
- Apollo dataset fine tune loss nan HOT 1
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