Open source data labeling and annotation tool for text, images, audio, video, and time series
Apache-2.0
- TypeScript
- JavaScript
- Python

About Label Studio
Label Studio is an open source data labeling tool for preparing raw data and improving existing training data. It supports audio, text, images, videos, and time series in a single UI, with export to various model formats.
It can be customized for custom datasets and used for multi-modal labeling and AI evaluation, including agent traces, LLM evals, RLHF, computer vision, document AI, NLP, and audio transcription. It also supports local machine learning model setup and integration with existing tools.
Label Studio can run locally with Docker, pip, poetry, or Anaconda, and can be deployed in a cloud instance. It is licensed under Apache 2.0 and maintained by HumanSignal, with the official Docker image published on Docker Hub.
Key features
- Label audio, text, images, videos, and time series
- Export labeled data to various model formats
- Customize for custom datasets
- Set up machine learning models
- Run locally or deploy in a cloud instance
Details
- First released
- 2019
- Platforms
- Windows · macOS · Linux · Web
- Self-hosting
- Local install and cloud deployment
- Deployment
- self-hostable · cloud
- License
- Apache 2.0
- Backend
- Docker · pip · poetry · Anaconda
