Label Studio is an open-source, configurable data annotation tool. Its purpose is to enable you to label different types of data using the most convenient interface with the standardized output format.
- Classify text for sentiment (screenshot)
- Named entities recognition (screenshot)
- Transcribe audio (screenshot)
- Classify audio (screenshot)
- Conversational modeling & chatbots (screenshot)
- Image object detection (screenshot)
Coming Soon:
- Audio regions (screenshot)
- Image line and points (screenshot)
- Image polygons (screenshot)
- Time series (screenshot)
- Video (screenshot)
Label Studio consists of two parts. Backend is a simple flask server that is used to load the data and save the results. The frontend is a React + MST app that is backend agnostic and can be used separately, for example if you want to embed labeling into your applications.
In order to launch server locally, launch
cd backend
bash start.shTo run it locally we include the compiled version of the frontend part and an example implementation of the backend.
Follow this guide for advanced usage & custom configuration
To extend the functionality of embed the labeling inside your app, you need to be able to compile it from the sources.
This guide explains how to do that
Editor configuration is based on XML-like tags. Internally tags are represented by a react view and mobx-state-tree model. Each tag has a set of parameters, and you can look it up in the documentation.
- Extensive UI configuration options
- Multiple datatypes supported: images, text, audios
- Hotkeys & History
- Converting to formats accepted by popular machine learning apps (check here for supported GitHub repositories)
This software is licensed under the Apache 2.0 LICENSE © Heartex.