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. Background

Sequences

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Last updated 1 year ago

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A sequence is a sample comprised of multiple frames. Each frame represents a data point you want to label, such as an image or a 3D point cloud. Using sequences can help increase labeling speed and consistency when working with sequential data.

A sequence has a number of unique features:

  • A track ID is assigned to each labeled object in a sequence. This track ID can be used to track an object over multiple frames. Learn how to use track IDs .

  • A sequence is assigned to a single labeler. This can increase the consistency of the labels between the frames in the sequence.

  • The image vector labeling interface and 3D point cloud cuboid interface allow you to use keyframe interpolation. This reduces the number of frames you need to label manually, which can decrease the labeling time significantly. Learn how to use keyframe interpolation .

Keyframes and remove-keyframes

In the context of interpolation, a keyframe is a marker that indicates that at that frame, the state of the object is defined by the user. In other frames (that are not keyframes), the state of the object label is calculated automatically through interpolation.

A remove-keyframe is a visual indication of where an object was removed from the sample. A remove-keyframe means that the object is not present in that frame and all frames before the next normal keyframe.

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An example of keyframes (blue diamonds) and a remove-keyframe (grey circle with cross). The yellow color indicates the frames in which the object is present.