Configure the label editor

Once you have created a dataset, you can further configure the labeling interface under Settings -> Labeling -> Categories:

Here you can set the color, name, and description for each category.

Working with attributes

Object attributes

You can add one or more object-level attributes or object attributes to a category by expanding its row.

Attributes come in 4 types:

• Select box

• Multi-select box

• Checkbox

• Text

• Number

You can optionally configure following settings for each object attribute:

• Default value: default value of the attribute.

• Mandatory: whether the attribute is mandatory. Mandatory attributes raise a warning when not filled in.

• Synced across frames ("Sequence-level"): Only in sequence datasets. Whether an attribute should remain constant across all frames for an object with a certain track ID. If false, the attribute can change on each frame.

• Synced across sensors ("Across sensors"): Only in multi-sensor datasets. Whether an attribute should remain constant across all sensors for an object with a certain track ID. If false, the attribute can change on each sensor.

• Sensors: Only in multi-sensor datasets. Whether an attribute applies to 2D sensors, 3D sensors, or all sensors.

Scene attributes

You can add scene attributes by clicking the "Edit image attributes" button. Scene attributes are not linked to a specific object, but rather to a frame or the scene as a whole.

In the labeling interface

When labeling, the object and scene attributes will be shown in the sidebar on the right. Scene attributes are always visible, while object attributes are only shown when an object is selected which has a category with object attributes.

Timeline display (sequences only)

For sequence datasets, user-defined attributes also appear in the timeline interface at the bottom of the editor, allowing you to view and edit them directly while navigating through frames.

How attributes appear in the timeline

The timeline displays attributes differently based on whether they have a category:

Track attributes (attributes with a category):

• Visible when you select a track in the viewer

• Display as rows below the track row in the timeline

• Each row shows the attribute values across frames

Scene attributes (attributes without a category):

• Visible when you select "Scene attributes" from the View dropdown (when no track is selected)

• Display as rows at the top of the timeline

Attribute behavior in timeline

Attributes can be configured along two independent dimensions:

Dimension 1: Frame-level vs Sequence-level (Synced across frames setting)

• Frame-level (Synced across frames = disabled): Each frame can have a different value. The timeline displays one cell per frame that you can edit individually.

• Sequence-level (Synced across frames = enabled): One value applies to all frames. The timeline displays a single value that applies to the entire sequence.

Dimension 2: Sensor-specific vs Synced across sensors

• Sensor-specific: Each sensor can have different values. In multi-sensor sequences, each sensor's timeline shows its own attribute values.

• Synced across sensors: The same value applies to all sensors. All sensors share the same attribute value.

Possible combinations:

These two dimensions create four possible configurations:

1. Frame-level + Sensor-specific: Each frame and each sensor has its own value

2. Frame-level + Synced across sensors: Each frame has its own value, but all sensors share the same values

3. Sequence-level + Sensor-specific: One value per sensor for the entire sequence

4. Sequence-level + Synced across sensors: One value for the entire sequence across all sensors

Benefits of timeline editing

• Edit attribute values without switching between panels

• See how attribute values change across frames at a glance

• Quickly identify frames where specific attribute values are set

• For frame-level attributes, easily compare values across multiple frames

For detailed instructions on editing attributes in the timeline, see Track timeline - Edit attributes.

Editing the configuration file directly

If you click on the "Raw" tab, you can see the configuration in JSON format. You can copy-paste this configuration from one dataset to another, or update it programmatically using the Python SDK. The configuration should adhere to the format defined here.