Documentation
  • Introduction
  • Tutorials
    • Getting started
    • Python SDK quickstart
    • Model-assisted labeling
  • How to annotate
    • Label images
      • View and navigate in the image interfaces
      • Image interface settings
      • Image segmentation interface
      • Image vector interface
    • Label 3D point clouds
      • View and navigate in the 3D interface
      • Upload, view, and overlay images
      • 3D interface settings
      • 3D point cloud cuboid interface
      • 3D point cloud vector interface
      • 3D point cloud segmentation interface
      • Merged point cloud view (for static objects)
      • Batch mode (for dynamic objects)
      • Smart cuboid propagation
      • 3D to 2D Projection
      • Tips for labeling cuboid sequences
    • Label sequences of data
      • Use track IDs in sequences
      • Use keyframe interpolation
    • Annotate object links (beta)
    • Customize hotkeys
  • How to manage
    • Add collaborators to a dataset
    • Create an organization
    • Configure the label editor
    • Customize label queue
    • Search within a dataset
    • Clone a dataset
    • Work with issues
    • Bulk change label status
    • Manage QA processes
  • How to integrate
    • Import data
      • Cloud integrations
    • Export data
      • Structure of the release file
      • Exporting image annotations to different formats
    • Integrations
      • Hugging Face
      • W&B
      • Databricks
      • SceneBox
    • Create an API key
    • Upload model predictions
    • Set up webhooks
  • Background
    • Main concepts
    • Sequences
    • Label queue mechanics
    • Labeling metrics
    • 3D Tiles
    • Security
  • Reference
    • Python SDK
    • Task types
    • Sample formats
      • Supported file formats
    • Label formats
    • Categories and attributes
    • API
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  1. How to annotate
  2. Label 3D point clouds

3D to 2D Projection

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Last updated 1 year ago

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For multi-sensor labeling, utilizing the ‘Project cuboids to camera sensors’ feature will automatically project 2D bounding boxes on the camera sensor frames from the 3D cuboids in the lidar point cloud. The projected 2D bounding boxes will maintain the object’s track ID throughout all sensors. This will help speed up the labeling for the 2D camera frames.

Click on the 3-dot icon next to lidar sensor, to access ‘Project cuboids to camera sensors’.

Overwrite existing tracks

  • If this option is checked, it will use the 3D cuboids to overwrite existing 2D bounding box objects.

  • If you made adjustments to the 2D bounding boxes and want to project additional objects from 3D to 2D, make sure this option is unchecked.