Guide to: LiDAR


The cml:lidar_box tag allows users to create a LiDAR annotation job for bounding box.

The cml:lidar_segmentation tag allows users to create a LiDAR annotation job for point cloud semantics segmentation.

Building a LiDar Job

The following CML contains the possible parameters for a lidar annotation job:

<cml:lidar_box ontology="true" name="annotation" base-url="{{base_url}}" 
validates="required" rotate-mode="yaw" range-indicators="20:0xFFFF00,30:0xFFA500,40:0x00FF00"
color-mode="elevation" project-async="false" project-rect="false" show-grid="false"
<cml:lidar_segmentation ontology="true" name="annotation" base-url="{{base_url}}" 
validates="required" range-indicators="20:0xFFFF00,30:0xFFA500,40:0x00FF00"
color-mode="elevation" />


Below are the parameters available for cml:lidar_box and cml:lidar_segmentation tag. Some are required in the element; some can be left out.

  • name (Required)
    • The results header where the results links will be stored
  • base_url (Required)
    • URL pointing to the base folder containing point cloud data
  • color-mode (Optional)
    • Defines point cloud color mode
    • Options: 'speed', 'elevation', 'reflection', 'elevation:[x, y][z, w]', 'reflection:[x, y][z, w]', where x & y define the elevation/reflection range, z & w define the color ramp proportion range, [z, w] is optional. For example, 'elevation:[0,5]', 'elevation:[0,2][0.25,1]', 'reflection:[0.25,1]', 'reflection:[0.25,1][0.25,1]' are all acceptable
  • color-mode(new) (Optional)
    • Define preset color mode, if color_config is provided will replace color_mode
    • Options: 'Intensity:0:#0000ff,1:#00ffff', 'Elevation:0:#0000ff,1:#00ffff', can get options string by double click the color mode custom label with ALT key down
  • rotate-mode (Optional)
    • Defines tool rotation mode
    • Options: ‘yaw’ - will only allow rotation of the bounding box in the direction parallel to the ground
  • range-indicators (Optional)
    • Defines circle ranges around the point cloud sensor center.
    • Options: 'x, y, z, ...', 'x:colorInHex, y:colorInHex, ...', where x, y, z defines the distance and colorInHex defines the circle color. If colorInHex is not provided, the default color red is used
  • project-async (Optional)
    • United Annotation - Allows 2D annotation to be updated independently
    • Options: true or false
  • project-rect (Optional)
    • United Annotation - Projects 3D annotation into 2D annotation
    • Options: true or false
  • auto_save (Optional)
    • Flag to enable or disable autosave (frame switch, interpolate, delete from all frames)
    • Options: true or false
  • tracking_mode (Optional)
    • Flag to enable or disable tool-tracked events
    • Options: true or false
  • validate_from (Optional)
    • URL pointing to annotation to be used as ground truth for in tool validation.
    • The format must match the output of the lidar annotation tool (JSON in a hosted URL)
  • review_from (Optional)
    • This parameter accepts the column header containing pre-created annotations.
    • The format must match the output of the lidar annotation tool (JSON in a hosted URL)
  • show-grid (Optional)
    • To show grid in 3d space.
  • default-add-mode (Optional)
    • Defines the behavior of Cuboid. If it is DRAG, users can change the size of the Cuboid when they add Cube. If it is Click, the size is fixed.


LiDAR annotation for bounding box and point cloud semantics segmentation share the same ontology structure. The Ontology Manager allows job owners to create and edit the ontology within a LiDAR Annotation job. LiDAR Annotation Jobs require an ontology to launch. When the CML for a text annotation job is saved, the Ontology Manager link will appear at the top of the Design page.

Ontology Manager Best Practices

  • The limit of ontology is 1,000 classes, however, as best practice, we recommend not exceeding 16 classes in a job to ensure contributors can understand and process the different classes. 
  • Choose from 16 colors pre-selected or upload custom colors as hex code via the CSV ontology upload.
  • If you uploaded model predictions as JSONs, the predicted classes should also be added to the ontology.

Upload Data

We need to first convert client data to the schema supported by our platform. Since there is no standard format in the industry, we work with our clients to understand their format and provide conversion scripts for each request.

For more information on secure hosting, check out this article. Below are example files on how to structure source data.


LiDAR bounding box annotation:

LiDAR point cloud semantics segmentation:

Note: This report may take a while to generate and download due to the large nature of all its data files. However, the download will still be much faster compared to running scripts to scrape the results. 

Additional Reference

Training Guide for LiDAR annotators:

Guide to Workflows for project managers:

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