Deepen AI - Enterprise
Deepen AI
  • Deepen AI Overview
  • FAQ
  • Saas & On Premise
  • Data Management
    • Data Management Overview
    • Creating/Uploading a dataset
    • Create a dataset profile
    • Auto Task Assignments
    • Task Life Cycle
    • Tasks Assignments
    • Creating a group
    • Adding a user
    • Embed labeled dataset
    • Export
    • Export labels
    • Import Labels
    • Import profile
    • Import profile via JSON
    • Access token for APIs
    • Data Streaming
    • Reports
    • Assessments
  • 2D/3D editors
    • Editor Content
    • AI sense (ML-assisted labeling)
    • Assisted 2d Segmentation
    • Scene Labeling
  • 2D Editor
    • 2D Editor Overview
    • 2D Bounding Boxes
    • 2D Polyline/Line
    • 2D Polygon
      • 2D Semantic/Instance Segmentation
        • 2D Segmentation (foreground/background)
    • 2D Points
    • 2D Semantic Painting
      • Segment Anything
      • Propagate Labels in Semantic Segementation
      • 2D Semantic Painting/Segmentation Output Format
    • 3D Bounding boxes on images
    • 2D ML-powered Visual Object Tracking
    • 2D Shortcut Keys
    • 2D Customer Review
  • 3D Editor
    • 3D Editor Overview
    • 3D Bounding Boxes — Single Frame/Individual Frame
    • 3D Bounding Boxes_Sequence
    • 3D Bounding Boxes Features
      • Label View
      • One-Click Bounding Box
      • Sequence Timeline
      • Show Ground Mesh
      • Secondary Views
      • Camera Views
      • Hide/UnHide Points in 3D Lidar
    • 3D Lines
    • 3D Polygons
    • 3D Semantic Segmentation/Painting
    • 3D Instance Segmentation/Painting
    • Fused Cloud
    • 3D Segmentation (Smart Brush)
    • 3D Segmentation (Polygon)
    • 3D Segmentation (Brush)
    • 3D Segmentation (Ground Polygon)
    • 3D Painting (Foreground/Background)
    • 3D Segmentation(3D Brush/Cube)
    • Label Set
    • 3D Shortcut Keys
    • 3D Customer Review
  • 3D input/output
    • JSON input format for uploading a dataset in a point cloud project.
    • How to convert ROS bag into JSON data for annotation
    • Data Output Format - 3D Semantic Segmentation
    • Data Output Format - 3D Instance Segmentation
  • Quality Assurance
    • Issue Creation
    • Automatic QA
  • Calibration
    • Calibration
    • Charuco Dictionary
    • Calibration FAQ
    • Data Collection for Camera intrinsic Calibration
    • Camera Intrinsic calibration
    • Data Collection for Lidar-Camera Calibration (Single Target)
    • Lidar-Camera Calibration (Single target)
    • Data Collection for Lidar-Camera Calibration (Targetless)
    • Lidar-Camera Calibration (Targetless)
    • Data Collection for Multi Target Lidar-Camera Calibration
    • Multi Target Lidar-Camera Calibration
    • Lidar-Camera Calibration(Old)
    • Vehicle-Camera Calibration
      • Data Collection for Vehicle-Camera Calibration
      • Vehicle Camera Targetless Calibration
      • Data collection for lane based targetless vehicle-camera calibration
      • Lane based Targetless Vehicle Camera Calibration
    • Data Collection for Rough Terrain Vehicle-Camera Calibration
    • Rough Terrain Vehicle-Camera Calibration
    • Calibration Toolbar options
    • Calibration Profile
    • Data Collection for Overlapping-Camera Calibration
    • Overlapping-Camera Calibration
    • Data collection guide for Overlapping Camera Calibration (Multiple-Targets)
    • Overlapping Camera Calibration (Multiple-Targets)
    • Data Collection for Vehicle-3D Lidar calibration
    • Data Collection for Vehicle-2D Lidar calibration
    • Vehicle Lidar (3D and 2D) Calibration
    • Data Collection for Vehicle Lidar Targetless Calibration
    • Data Collection for IMU Lidar Targetless Calibration
    • Vehicle Lidar Targetless Calibration
    • Data Collection for Non Overlapping Camera Calibration
    • Non-Overlapping-Camera Calibration
    • Multi Sensor Visualization
    • Data Collection for LiDAR-LiDAR Calibration
    • LiDAR-LiDAR Calibration
    • Data Collection for IMU Intrinsic calibration
    • IMU Intrinsic Calibration
    • Data Collection for Radar-Camera Calibration
    • Radar-Camera Calibration
    • Data Collection for IMU Vehicle calibration
    • Lidar-IMU Calibration
    • IMU Vehicle Calibration
    • Data Collection for vehicle radar calibration
    • Vehicle radar calibration
    • Calibration Optimiser
    • Calibration list page
    • Data collection for rough terrain vehicle-Lidar calibration
    • Rough terrain vehicle Lidar calibration
    • Surround view camera correction calibration
    • Data Collection for Surround view camera correction calibration
    • Data Collection for Lidar-Radar calibration
    • Lidar Radar Calibration
    • Vehicle Lidar Calibration
    • API Documentation
      • Targetless Overlapping Camera Calibration API
      • Target Overlapping Camera Calibration API
      • Lidar Camera Calibration API
      • LiDAR-LiDAR Calibration API
      • Vehicle Lidar Calibration API
      • Global Optimiser
      • Radar Camera Calibration API
      • Target Camera-Vehicle Calibration API
      • Targetless Camera-Vehicle Calibration API
      • Calibration groups
      • Delete Calibrations
      • Access token for APIs
    • Target Generator
  • API Reference
    • Introduction and Quickstart
    • Datasets
      • Create new dataset
      • Delete dataset
    • Issues
    • Tasks
    • Process uploaded data
    • Import 2D labels for a dataset
    • Import 3D labels for a dataset
    • Download labels
    • Labeling profiles
    • Paint labels
    • User groups
    • User / User Group Scopes
    • Download datasets
    • Label sets
    • Resources
    • 2D box pre-labeling model API
    • 3D box pre-labeling model API
    • Output JSON format
Powered by GitBook
On this page
Export as PDF
  1. Data Management

Adding a user

PreviousCreating a groupNextEmbed labeled dataset

Last updated 1 year ago

How to add a user:

  1. When a workspace is opened there is the Users option on the left side panel.

  2. Click on the Users option and at the top right click on Add user.

  3. Enter valid email and select the scope for the user and click on Add User.

Permission rights of each user: Deepen AI annotation tools have different user access levels for different tasks. Different roles and their description are as follows:

  1. Admin: This role can view/add/edit/delete a project, add/delete a dataset, add users, add payment details, sign up for different pricing plans, assign users, add files and add labels.

  2. Reader: This role can view all the labels, reports and profiles but cannot make any changes.

  3. Datasets Admin: This role has access to create and delete datasets. They can assign frames to already added users. They cannot label or add any users.

  4. Datasets Creator: This role has access to add datasets, but cannot delete datasets.

  5. Labels Admin: This role can add and delete labels.

  6. Labeller: This role has access to annotate the allocated frames (Labelling and QA)

  7. Customer: This role has permission to accept or reject labels in the workspace.

Apart from these, we have additional scopes for Access Tokens. They are:

  1. Dataset Labels Admin: This role can add and delete the labels on the dataset level only.

  2. Dataset Labeller: This role has access to annotate the allocated frames(Labelling and QA) on the dataset level.

  3. Dataset Calibration Edit: This role can view, create, manage and delete calibration datasets at the dataset level.

  4. Dataset Calibration Read: This role can view all at the dataset level for calibration dataset.

  5. Dataset Reader: This role can view all the labels, reports and profiles but cannot make any changes at the dataset level.

  6. Dataset Customer: This role can accept labels at the dataset level.