heartexlabs/label-studio
Label Studio
Label Studio is a multi-type data labeling tool and data annotation workspace designed to prepare datasets for machine learning training. It functions as a cloud-integrated data pipeline that imports raw data from storage, manages the annotation process, and exports labels into standardized formats.
The platform features a machine learning model integration framework that connects to external model servers. This enables model-assisted annotation and active learning, allowing the system to perform pre-labeling and refine predictions based on human feedback.
The software provides project management tools for organizing datasets and assigning tasks to users via role-based access. It supports various data types and utilizes backend-agnostic storage adapters to connect with local filesystems or cloud storage providers.
The application can be installed via manual setup or one-click deployments on cloud infrastructure.
Features
- Data Labeling Platforms - Functions as a comprehensive platform for preparing and annotating diverse datasets for machine learning training pipelines.
- Multi-Type Data Annotation - Supports labeling various data types using a standardized output format to ensure compatibility across training pipelines.
- Universal Annotation Schemas - Stores all labels in a universal JSON schema to ensure compatibility across different machine learning training pipelines.
- Data Annotation Workflows - Provides automated pipelines that import raw data, apply labels via a web interface, and export it into standardized formats.
- Annotation Format Converters - Converts labeled data into standardized formats compatible with various machine learning models for training.
- Annotation Dataset Creation - Creates high quality annotated datasets for training machine learning models across various data formats and types.
- Model Integrations - Provides a framework for connecting external machine learning model servers to perform pre-labeling and active learning.
- Annotation Project Management - Coordinates multi-user labeling tasks and manages large datasets within a shared workspace to ensure consistency.
- Cloud-Integrated Labeling Pipelines - Functions as a workflow tool that imports data from cloud storage and exports labels into various machine learning formats.
- Model-Assisted Labelers - Integrates machine learning models to automatically generate initial annotations and refine training data.
- ML Model Server Integrations - Enables the connection of external model servers to automate data pre-labeling via automated predictions.
- Active Learning - Connects machine learning models to the labeling process to automate pre-labeling and refine predictions via human feedback.
- Hybrid Cloud Storage Configuration - Saves application assets and uploaded files using local directories or compatible cloud storage for data persistence.
- Training Data Pipelines - Organizes and cleans raw data through labeling and formatting to make it compatible with model training pipelines.
- External Data Connectors - Links the labeling interface to external data sources through a modular system of import and export scripts.
- Storage Backend Adapters - Implements a driver layer that abstracts data persistence across local filesystems and cloud storage buckets.
- Model Prediction Interfaces - Communicates with external machine learning servers via standardized API calls to fetch predictions for pre-labeling.
- Role-Based Access Control - Controls data visibility and annotation assignments by mapping user accounts to specific project permissions.
- Pipeline Integration - Allows embedding the annotation process into larger automated data processing workflows via a standardized interface.
- Annotation - Multi-type data labeling and annotation tool.
- Computer Vision Libraries - Multi-type data labeling and annotation tool.
- Data Annotation - Multi-type data labeling and annotation platform.
- Image Annotation Tools - Multi-modal data labeling tool with standardized output formats.
- Multi-Domain Annotation - Configurable annotation tool supporting various data types.
- Multi-Modal Annotation - Configurable platform supporting diverse data types and workflows.
- Multimodal Annotation Tools - Versatile labeling tool supporting multiple data types with standardized output.
- Developer Tools - Provides a multi-type interface for data annotation and labeling.
