Universal Data Tool
  • Universal Data Tool Docs
  • Installation
  • Running On-Premise
  • Collaborative Labeling
  • Building and Labeling Datasets
    • Image Segmentation
    • Image Classification
    • Text Classification
    • Named Entity Recognition
    • Entity Relations / Part of Speech Tagging
    • Audio Transcription
    • Data Entry
    • Video Segmentation
    • Composite Interfaces
    • Landmark / Pose Annotation
  • Importing Data
    • Upload or Open Directories
    • Import File URLs
    • Import COCO Images
    • Import from Google Drive
    • Import from AWS S3 Bucket
    • Import from CSV or JSON
    • Import using AWS Cognito
    • Import Text Snippets
  • The Format .udt.json
    • What is the .udt.json format?
    • What is the .udt.csv format?
  • Machine Learning
    • Jupyter Notebook Integration
    • Import Datasets into Pandas
    • Fast.ai
      • Fast.ai Image Classification
      • Fast.ai Image Segmentation
  • Integrate with Any Web Page
    • Integrate with the Javascript Library
    • Getting Started with React
  • Train your Workforce
    • Getting Started with UDT Courses
  • Frequently Asked Questions
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  • Run via Docker
  • Independent Collaboration Server

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Running On-Premise

Run the Universal Data Tool on your infrastructure.

PreviousInstallationNextCollaborative Labeling

Last updated 4 years ago

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For small companies or projects, you might want to consider just using the or , which requires less setup!

The Universal Data Tool can be run and customized on your own infrastructure easily. This is best for users who want to keep their version of Universal Data Tool stable, and don't need new features from weekly releases. You may also want to keep your data within your network.

Run via Docker

The Universal Data Tool builds docker containers on every new release. You can run the Universal Data Tool using...

# Starts the Universal Data Tool on port 3000 and a collaborative server on 3001
docker run -d -p 3000:3000 -p 3001:3001 \
             -e UDT_collaborationServer_url=http://localhost:3001 \
             universaldatatool/universaldatatool

You can provide different options to the docker container to control various aspects of Universal Data Tool. Below is a table of a few of the configuration parameters can customize. You'll know if a configuration value is used because it will appear in the starting logs like the following image...

Environment Var

Description

UDT_collaborationServer_url

Collaboration server URL

UDT_pluginUrls

Comma-delimited URLs to plugins that should be loaded by default

UDT_auth_proxy_corsproxy

Proxy to use for CORS requests, e.g. to make api requests that are disallowed by CORs

UDT_auth_s3iam_accessKeyId

Access Key for uploading/importing from AWS S3 buckets

UDT_auth_s3iam_secretAccessKey

Secret Access Key for uploading/importing from AWS S3 buckets

UDT_s3iam_region

Region of S3 Bucket

UDT_auth_cognito_identityPoolId

Cognito Identity Pool Id

UDT_auth_cognito_region

Cognito Region

UDT_auth_cognito_userPoolId

Cognito user pool id

UDT_auth_cognito_userPoolWebClientId

Cognito user pool web client id

UDT_auth_cognito_storage_awsS3_bucket

Bucket to use for Cognito object storage

UDT_auth_cognito_storage_awsS3_region

Region of bucket to use for Cognito

UDT_labelhelp_disabled

Disable remote paid collaboration requests

UDT_labelhelp_apikey

API Key for requesting work from Label Help

Independent Collaboration Server

Sometimes, you may want to run the Collaboration Server on a different machine than the Client Application, you can do this by using the npm module.

# via npm
npm install -g udt-collaboration-server

udt-collaboration-server --port 3001

These are the most common configuration values, but you can also customize hotkeys or any other attribute the appears in the .

AppConfig
udt.dev
Desktop Application
Configuration values are shown in a table on start