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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  • Permissions
  • Adding collaborators programmatically

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  1. How to manage

Add collaborators to a dataset

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Last updated 1 year ago

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Go to Settings -> Collaborators to add collaborators to your dataset.

Permissions

Collaborators can have one of 4 roles: labeler, reviewer, manager and administrator. Each role has a different set of permissions:

Labeler
Reviewer
Manager
Administrator

Label samples

Review samples

Manage samples and issues (view, add, update, delete)

Manage collaborators (add, update, delete)

Manage releases (view, add, delete)

Manage settings

Manage labelsets

Labelers and reviewers can only see the "Overview" tab of a dataset, where they can click the "Start labeling" and "Start reviewing" buttons depending on their role. Note that they cannot browse the samples on the Samples tab.

Managers and administrators can add collaborators to a dataset. Note that a manager cannot add a collaborator with an administrator role.

Adding collaborators programmatically

You can also .

add collaborators to a dataset using the Python SDK