Transform Your Data into AI-Ready Formats with Label Studio
Label Studio is a free self-hosted open-source data labeling platform designed for flexibility in fine-tuning large language models, preparing training data, or validating AI models.
It supports a wide range of data types, including images, audio, text, time series, and video, across various applications like image classification, object detection, audio transcription, and sentiment analysis.
This platform is particularly useful for Python developers and data engineers through its library mode and integrates with large news archives like commoncrawl.org for article extraction.
Its audience includes data scientists, AI researchers, and developers looking for a versatile tool to enhance their machine learning models.
Enterprise Users
Label Studio is used by big players such as Intel, Meta, Google, IBM, CloudFlare, SRI, Nvidia, and many more.
Features
- Supports a wide range of data types
- Useful for Python developers and data engineers
- Integrates with large news archives for article extraction
- Flexible and configurable layouts and templates
- ML-assisted labeling with ML backend integration
- Connects to cloud object storage (S3 and GCP)
- Supports computer vision
- Image classification
- Object detection
- Semantic segmentation
- Advanced filters in Data Manager for dataset preparation and management
- Supports multiple projects, use cases, and data types
- Rich documentation
- Easy to install using PIP or Docker
- Supports macOS Intel and Silicon
- Install using Anaconda
- Can be easily deployed on Microsoft Azure, Google Cloud and Heroku
- Include a rich template set and a template engine
- Emotion Recognition
- Audio Transcription
- Supports time series labeling
- Video labeling
License
Apache-2.0 license
Resources & Downloads
HumanSignal
