Skip to main content

Labelo - Collaborative Data Annotation Tool

Annotate and collaborate across multiple data types with ease.

Python Release License PyPI

Website • Docs • Blogs

Table of Contents

What is Labelo

Labelo is an open-source, scalable platform designed to simplify and accelerate the process of data annotation. Whether you're working with images, video, audio, or text, Labelo provides a comprehensive set of tools to help you label and review data efficiently, all while collaborating seamlessly with your team.

Features

  • Workspaces: Organize and manage multiple projects within dedicated workspaces.
  • Dashboard & Analytics: Gain insight into project performance with detailed charts and customizable layouts.
  • Team Management: Invite members, assign roles (Administrator, Manager, Reviewer, Annotator), and track activity.
  • Annotation Tools: A feature-rich editor supporting multiple data types and formats for efficient labeling.
  • Review System: Seamless workflow for reviewing annotations with comment and approval systems.
  • Data Management: Powerful tools for filtering, sorting, and performing bulk actions in grid or list views.

Supported Data Types

  • Text: .txt
  • Audio: .wav, .mp3, .flac, .m4a, .ogg
  • Video: .mp4, .mpeg4, .webp, .webm
  • Images: .jpg, .jpeg, .png, .gif, .bmp, .svg, .webp
  • HTML: .html, .htm, .xml
  • Time Series: .csv, .tsv
  • Common Formats: .csv, .tsv, .json

Quick Start

To get started with Labelo:

  1. Create a Project:

    • Run the Labelo server and open your browser at http://localhost:8080.
    • Use the Labelo UI to create a new project within a workspace.
  2. Import Data:

    • Navigate to your project and use the data import tools to upload images, videos, audio files, or text documents.
  3. Annotate Data:

    • Select an item from your dataset and use the annotation tools to label your data. You can draw bounding boxes, create segments, or add text labels depending on the data type.
  4. Review Annotations:

    • Once annotations are complete, use the review system to check, comment on, and approve annotations.
  5. Export Data:

    • After reviewing, you can export annotated data in various formats supported by Labelo.

Installation

Install Locally with pip

To install Labelo using pip:

# Requires Python >=3.8
pip install labelo

# Start the server at http://localhost:8080
labelo

Install Locally with Virtual Environment

# Set up a virtual environment.
python3 -m venv env  
source env/bin/activate  

# Install Labelo.
pip install labelo  

# Run Labelo.
labelo

Install Locally with Docker

# Pull the latest image
docker pull cybrosystech/labelo:latest

# Run Labelo in a Docker container
docker run -p 8080:8080 -v $(pwd)/mydata:/labelo/data cybrosystech/labelo:latest

Access the application at http://localhost:8080. All generated assets, including the SQLite3 database and uploaded files, will be stored in the ./mydata directory.

Install with Poetry for Development

You can run the latest version of Labelo locally without installing the package from PyPI. Follow these steps for local development:

# Install all package dependencies.
pip install poetry
poetry install

# Run database migrations.
poetry run python labelo/manage.py migrate

# Collect static files.
poetry run python labelo/manage.py collectstatic

# Start the server in development mode at http://localhost:8080.
poetry run python labelo/manage.py runserver

License

This software is licensed under the Apache 2.0 LICENSE © Cybrosys. 2024

Contributing to Labelo

We value feedback and contributions from our community. Whether it’s a bug report, new feature, correction, or additional documentation, we welcome your issues and pull requests. Please read through this CONTRIBUTING document before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your contribution.

Metadata

Release files for labelo 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for labelo 1.0.0
File Size Uploaded Provenance Actions
labelo-1.0.0.tar.gz 91.1 MB Without provenance Details for labelo-1.0.0.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for labelo 1.0.0
File Interpreter ABI Platform Actions
labelo-1.0.0-py3-none-any.whl Python 3 none any Details for labelo-1.0.0-py3-none-any.whl

Total release size: 183.8 MB

Release files / labelo-1.0.0.tar.gz

Download URL labelo-1.0.0.tar.gz
Size 91.1 MB
Tags Source
SHA-256 checksum
How to use checksums
2037580dfadf0fa7ba27e783706a3212a9893453291757944798d0c4f7defce3
BLAKE2b-256 checksum
How to use checksums
678e903b1c11568227557f9dded552cd334e66e6bc3033bc21f19be0032c7cc8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via poetry/1.8.2 CPython/3.10.12 Linux/6.8.0-45-generic

Release files / labelo-1.0.0-py3-none-any.whl

Download URL labelo-1.0.0-py3-none-any.whl
Size 92.6 MB
Tags Python 3
SHA-256 checksum
How to use checksums
2c65519340e0bdfc87e12d1762bf36c9e5afef538f7a8c2c3533aa7ac6057cb3
BLAKE2b-256 checksum
How to use checksums
0a6e825db5ca5b2c03959fa94fa146d00ecdb66095e9b518f5d50cf628a8cb32
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via poetry/1.8.2 CPython/3.10.12 Linux/6.8.0-45-generic

Security for labelo 1.0.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page