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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On this page
  • Setup the Dataset
  • Import Data
  • Label your Data!
  • Export and Use

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  1. Building and Labeling Datasets

Image Segmentation

Segment instances on image datasets using the Universal Data Tool

PreviousCollaborative LabelingNextImage Classification

Last updated 4 years ago

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Setup the Dataset

Navigate to and click "New File"

Then select the Image Segmentation button from the Setup > Data Type page.

You can configure the Image Segmentation to create the right interface for your dataset. Use the Setup > Preview button to see your interface against either an example image or a sample from your dataset.

Configuring Regions and Labels

The Image Segmentation interface allows different types of regions, the options for regions are:

  • bounding-box

  • polygon

  • point

Each region can any number of labels, which can be configured under "Available Labels"

Import Data

You can use any of the following methods to import image data. If you're just getting started, you can quickly create a dataset using the COCO Images method!

Label your Data!

Export and Use

You can download your data using the download icon at the top.

Use the Label tab to label your data. Look at the to label with others.

You can use the to convert UDT files into PNG masks, or other formats that are helpful for machine learning datasets.

Import COCO Dialog
Import from Google Drive
Import from AWS S3 Bucket
Import from List of URLs
Import from CSV or JSON
Upload or Open Directory
Collaborative Labeling Guide
Universal Data Tool Converter
udt.dev
Click "New File" on udt.dev
Image Segmentation with Bounding Box Classification
Download your data in CSV or JSON format to use the annotations
It's very common to convert into PNGs