Data Labeling Python Packages

label-studio

Label Studio is a multi-type data labeling and annotation tool with standardized output format

segments-ai

Segments.ai Python SDK

cleanlab

Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

bbox-visualizer

Make drawing and labeling bounding boxes a piece of cake

composeml

A machine learning tool for automated prediction engineering. It allows you to easily structure prediction problems and generate labels for supervised learning.

auto-labeling-pipeline

doccano auto labeling pipeline helps doccano to annotate a document automatically.

doccano

Open source annotation tool for machine learning practitioners.

toloka-kit

Toloka-Kit is a Python library for working with Toloka API.

cleanlab-studio

Client interface to Cleanlab Studio

potato-annotation

potato: the portable annotation tool

doccano-client

A simple client for doccano API.

langformers

🚀 Unified NLP Pipelines for Language Models

coral-annotation-tool

CAT: Coral Annotation Tool for Structure from Motion (SfM) Orthomosaic coral reef annotation.

panlabel

Universal annotation converter

hover

:speedboat: Label data at scale. Fun and precision included.

cleanlab-cli

Client interface to Cleanlab Studio

pyheartex

Heartex Python SDK - Connect your own models to Heartex Data Labeling

dash-annotate-cv

A Python library for computer vision annotation tasks using Dash

knowlyr-datalabel

Serverless annotation framework with LLM pre-labeling, inter-annotator agreement analysis & offline HTML interface. CLI + MCP ready.

superpipe-py

build unstructured to structured data transformation pipelines

example-package-elisno

The standard package for data-centric AI, machine learning with label errors, and automatically finding and fixing dataset issues in Python.

swiftlabel

Keyboard-first image classification tool for ML practitioners

kern-refinery

The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.

labelkit

Superpipe - optimized LLM pipelines for structured data