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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On this page
  • 1. Upload data to Segments.ai's asset storage service
  • Via the web interface
  • Via the Python SDK
  • 2. Keep the data in your cloud bucket
  • Public but unguessable URLs
  • Customer-secured URLs
  • Cross-account access

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  1. How to integrate

Import data

PreviousManage QA processesNextCloud integrations

Last updated 10 months ago

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There are two ways to import the data you want to label:

  1. Upload the data to Segments.ai's asset storage service via the web interface or Python SDK.

  2. Keep the data in your own cloud bucket and submit the URLs to Segments.ai via the Python SDK.

1. Upload data to Segments.ai's asset storage service

The maximum file size for our asset storage service is 100MB.

Via the web interface

Within a dataset, click the "Add samples" button or drag and drop files to the page. The uploaded assets (e.g. image or point cloud files) are stored in the Segments AWS S3 bucket. The asset URLs are public but unguessable, making them only accessible to dataset collaborators.

Via the Python SDK

See the .

2. Keep the data in your cloud bucket

If you want to keep the data in your own cloud bucket or on your own file server, you can use the to Segments.ai. In this case, no data is copied to our own storage system, only a reference (URL) to the data is stored in our database. This can be done in three ways:

Public but unguessable URLs

Keep the data in a cloud bucket whose content can be publicly accessed but not listed. You store the assets in this bucket with unguessable file names (containing a random uuid) such that they can only be accessed by third parties who you've shared the URLs with.

Customer-secured URLs

Keep the data in a private cloud bucket or server, and generate proxied or pre-signed URLs on your end to retain full control of the access permissions. These URLs can have custom restrictions: expiry time, maximum number of accesses, IP whitelisting, rate limits, etc.

Cross-account access

Keep the data in a private cloud bucket or server, and grant us cross-account access. In this case, we generate temporary pre-signed URLs whenever the images need to be displayed in the frontend. For setting this up, see .

Python SDK reference
Python SDK to submit the URLs
Cloud integrations