Label Studio
An open-source data labeling tool for annotating audio, text, images, videos, and time series with a simple UI and standardized output.
What is Label Studio?
Label Studio is an open-source data labeling and annotation tool that supports multiple data types including audio, text, images, videos, and time series. It provides a simple UI for preparing raw data or improving existing training data to build more accurate machine learning models. The tool outputs data in standardized formats and integrates with ML pipelines for pre-labeling and active learning.
Machine learning engineers, data scientists, and annotation teams who need to create or refine labeled datasets for training ML models across various domains like computer vision, NLP, and audio processing.
Developers choose Label Studio for its flexibility in handling diverse data types, customizable labeling interfaces, and strong integration capabilities with ML models and existing tools via REST API. Its open-source, self-hostable nature allows full control over data and infrastructure.
Overview
Label Studio is a multi-type data labeling and annotation tool with standardized output format
Use Cases
Best For
- Creating labeled datasets for computer vision projects like object detection or image classification
Related Projects
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
