Labeling
Interactive ground truth labeling in lidar point clouds
Use the Lidar Labeler app to interactively label ground truth data in a lidar point cloud or point cloud sequence. You can define cuboid regions of interests (ROIs) and use them to interactively label ground truth data. Use labeled lidar point clouds to train deep learning models. To automate the labeling process, you can use a built-in automation algorithm or develop your own algorithm. The app also provides APIs for categorizing labels and for creating label definitions. To start labeling an object, see Get Started with the Lidar Labeler.

Apps
Lidar Labeler | Label ground truth data in lidar point clouds |
Functions
Topics
Get Started
- Get Started with the Lidar Labeler
Interactively label a point cloud or point cloud sequence. - Keyboard Shortcuts and Mouse Actions for Lidar Labeler
Use keyboard shortcuts and mouse actions to increase productivity while using the Lidar Labeler app. - Use Custom Point Cloud Source Reader for Labeling
Create a reader function to load a custom image data source into the Lidar Labeler. - Connect Image Display to Lidar Labeler
Automate Labeling
- Create Automation Algorithm for Labeling
Create a custom automation algorithm to use in a labeling app. - Temporal Automation Algorithms
Create a time-based custom tracking algorithm to import into a labeling app. - Automate Ground Truth Labeling For Vehicle Detection Using PointPillars
This example shows how to automate vehicle detections in a point cloud using a pretrainedpointPillarsObjectDetector
in the Lidar Labeler. - Automate Ground Truth Labeling for Lidar Point Cloud Semantic Segmentation Using Lidar Labeler
This example shows how to automate semantic labeling in a point cloud using a pretrained semantic segmentation network in the Lidar Labeler app.