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
  • AWS
  • Granting cross-account access
  • CORS configuration
  • Google Cloud
  • Granting cross-account access
  • CORS configuration
  • Azure

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  1. How to integrate
  2. Import data

Cloud integrations

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Last updated 7 months ago

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AWS

Granting cross-account access

If your data is stored in a private AWS S3 bucket, you can submit your image URLs in virtual-hosted-style format: https://<bucket-name>.s3.<region>.amazonaws.com/<key>.

We will then use the S3 API to access data from your S3 bucket, using AWS account ID 931508227573 (canonical ID a2c85e730d80dcb51a2c0e1a8f852cf6dc8d6e04d9e00f49239c324de3c1e3e1). We generate temporary to serve the images from your S3 bucket in our frontend. These URLs expire after 24 hours.

This setup requires that you give the Segments.ai AWS account read-only access to the data in your bucket. You can do this by granting us through setting an appropriate :

  1. In your AWS account, go to the S3 Management Console.

  2. Go to your bucket.

  3. Go to the Permissions tab.

  4. In the Bucket Policy section, click the Edit button.

  5. Paste the following bucket policy and save your changes. Don't forget to replace YOUR_BUCKET_NAME with the name of your bucket.

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "segments-s3-access",
            "Effect": "Allow",
            "Principal": {
                "AWS": "arn:aws:iam::931508227573:user/segmentsai-prod-user"
            },
            "Action": [
                "s3:GetObject"
            ],
            "Resource": "arn:aws:s3:::YOUR_BUCKET_NAME/*"
        }
    ]
}

CORS configuration

  1. In your AWS account, go to the S3 Management Console.

  2. Go to your bucket.

  3. Go to the Permissions tab.

  4. In the Cross-origin resource sharing (CORS) section, click the Edit button.

  5. Paste the following configuration and save your changes.

[
    {
        "AllowedHeaders": [
            "*"
        ],
        "AllowedMethods": [
            "GET"
        ],
        "AllowedOrigins": [
            "https://*.segments.ai"
        ],
        "ExposeHeaders": []
    }
]

Google Cloud

Granting cross-account access

CORS configuration

[
    {
      "origin": ["https://*.segments.ai"],
      "method": ["GET"],
      "responseHeader": [],
      "maxAgeSeconds": 3600
    }
]

Azure

If you run into any issues when setting up this integration, please .

You also need to configure for your S3 bucket:

Please to help you set this up.

You also need to configure for your Cloud Storage bucket, using this JSON file:

Please to help you set this up.

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CORS
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