Open-source alternatives to Data Annotator For Machine Learning

DataGym.ai is a modern, web based workbench to label images and videos. It allows you to manage your projects and datasets, label data, control quality and build your own training data pipeline. With DataGym.ai´s API and Python SDK you can integrate it into your toolchain.

The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get the most value out of your AI Data.

QSL is a simple, open-source media labeling tool that you can use as a Jupyter widget. More information available at https://qsl.robinbay.com. It supports:

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 manag

Adala: Autonomous DAta (Labeling) Agent framework

Website · Docs · Changelog · Tutorials · Academy · Blog

hover is a tool for mass-labeling data points that can be represented by vectors.

Tornado is an open source Human-in-the-loop machine learning tool. It helps you label your dataset on the fly while training your model through a simple web user interface. It supports all data types: structured, text and image.

Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.

Video and Image Analytics for Multiple Environments

Xtreme1 is an all-in-one open-source platform for Multimodal training data.