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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  • Label
  • Label set

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  1. How to integrate
  2. Export data

Structure of the release file

The general structure of the release file is as follows:

{
    "name": "first release",
    "description": "This is a first release of Segments.ai playground dataset",
    "created_at": "2020-07-09 10:20:19.888887+00:00",
    "dataset": {
        "name": "flowers",
        "task_type": "segmentation-bitmap",
        "task_attributes": {...} // the categories etc.
        "labelsets": [
            /** list of labelsets **/
        ],
        "samples": {
            /** list of samples **/
        }
    }
    
}

Sample

Each sample entry contains information about the sample (name, image URL, ...) and a list of labels.

{
    "name": "donuts.jpg",
    "attributes": {
        "image": {
            "url": "https://segmentsai-prod.s3.eu-west-2.amazonaws.com/assets/segments/3b8b3da2-f09a-494b-999e-37250dfbf5b6.jpg"
        }
    },
    "labels": {
        /** list of labels, indexed by labelset **/    
    }
}

Label

The attributes field of a label contains all the info about the labeled objects. Its contents depend on the type of the label (image segmentation, cuboid,...). See Label formats for an overview of the attributes per label type. Each label also contains basic information such as the time it was created, the user who created it, its status (e.g. LABELED).

{
    "label_status": "LABELED",
    "attributes": {
        "format_version": "0.1",
        "annotations": [
            {
                "id": 1,
                "category_id": 1
            },
            {
                "id": 2,
                "category_id": 1
            },
            {
                "id": 3,
                "category_id": 1
            },
            {
                "id": 4,
                "category_id": 1
            }
        ],
        "segmentation_bitmap": {
            "url": "https://segmentsai-prod.s3.eu-west-2.amazonaws.com/assets/segments/504e7633-ef51-49c3-8b0e-d4eb9100532d.png"
        }
    }
}

Label set

Each labelset entry contains the labelset's name and description:

{
    "name": "ground-truth",
    "description": ""
}
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