What is Label Studio used for?

Label Studio is an open-source data labeling tool for audio, text, images, video and time series, exporting to many model formats. It is a good fit for building training sets for computer vision models, and annotating text and audio for NLP projects.

Is Label Studio open source?

Yes. Label Studio is open source under the Apache-2.0 licence. Its source code is on GitHub at HumanSignal/label-studio and is written mainly in TypeScript.

Is Label Studio free?

Yes. Label Studio is open source, so the software itself is free to use. A managed cloud version is also available.

Can I self-host Label Studio?

Yes. Label Studio can be self-hosted on your own server or infrastructure.

What is Label Studio an alternative to?

Label Studio is an open-source alternative to Roboflow, Scale AI, Labelbox and SuperAnnotate. Other open-source alternatives to Roboflow include CVAT.

Is Label Studio actively maintained?

Yes. The most recent commit to Label Studio was on 2 October 2026, and the latest release is 1.23.2, published on 29 September 2026. The project has 28k stars on GitHub.

Label Studio: open-source alternative to Roboflow, Scale AI

About Label Studio

Label Studio is an open-source tool for labeling and annotating data. It handles audio, text, images, videos and time series through a straightforward interface, and exports the labels in formats suited to various machine learning models. Teams use it to prepare raw data or to improve existing training data so models become more accurate. It is written mainly in TypeScript and released under the Apache-2.0 license.

You can install it locally with Docker, Docker Compose, pip, poetry or Anaconda, or deploy it on a cloud instance. The Docker Compose option provides a production-ready stack of Label Studio, Nginx and PostgreSQL. By default the Docker image serves the app on port 8080 and stores a SQLite database and uploaded files in a local directory. The README also covers labeling templates, connecting machine learning models and integrating with existing tools, and mentions a Starter Cloud edition with a free trial.

Key features

Labeling for audio, text, images, video and time series
Export to various model formats
Included templates for common labeling tasks
Connect ML models for assisted labeling
Docker Compose stack with Nginx and PostgreSQL
Install with pip, Docker, poetry or Anaconda

Good fit for

→Building training sets for computer vision models
→Annotating text and audio for NLP projects

Built with: TypeScript
Tags: data-labeling; annotation; machine-learning; computer-vision; mlops; datasets; image-annotation; self-hosted

Label Studio: questions and answers

What is Label Studio used for?: Label Studio is an open-source data labeling tool for audio, text, images, video and time series, exporting to many model formats. It is a good fit for building training sets for computer vision models, and annotating text and audio for NLP projects.
Is Label Studio open source?: Yes. Label Studio is open source under the Apache-2.0 licence. Its source code is on GitHub at HumanSignal/label-studio and is written mainly in TypeScript.
Is Label Studio free?: Yes. Label Studio is open source, so the software itself is free to use. A managed cloud version is also available.
Can I self-host Label Studio?: Yes. Label Studio can be self-hosted on your own server or infrastructure.
What is Label Studio an alternative to?: Label Studio is an open-source alternative to Roboflow, Scale AI, Labelbox and SuperAnnotate. Other open-source alternatives to Roboflow include CVAT.
Is Label Studio actively maintained?: Yes. The most recent commit to Label Studio was on 2 October 2026, and the latest release is 1.23.2, published on 29 September 2026. The project has 28k stars on GitHub.