Label Studio

Label Studio is an open source data labeling tool that supports multiple projects, users, and data types in one platform. It allows for different types of labeling with various data formats and integrates with M/L backends. It's a flexible platform for fine-tuning LLMs, preparing training data, or validating AI models.

How to Use

Label Studio can be installed via PIP, Brew, Git, or Docker. After installation, you can launch the tool, import data, create projects, and start labeling using customizable tags and templates.

Label Studio's

Key Features

• Support for multiple data types (images, audio, text, video, time series)
• Configurable layouts and templates
• Integration with ML/AI pipelines via Webhooks, Python SDK, and API
• ML-assisted labeling
• Connection to cloud storage (S3, GCP)
• Data Manager with advanced filters
• Multiple projects and users support

Use Cases

• Computer Vision: Image classification, object detection, semantic segmentation
• Audio & Speech Applications: Classification, speaker diarization, emotion recognition, audio transcription
• NLP, Documents, Chatbots, Transcripts: Classification, named entity recognition, question answering, sentiment analysis
• Robots, Sensors, IoT Devices: Classification, segmentation, event recognition
• Multi-Domain Applications: Dialogue processing, optical character recognition, time series with reference
• Video: Classification, object tracking, assisted labeling
• GenAI: LLM Fine-Tuning, LLM Evaluations, RAG Evaluation