Open-source alternatives to Cvat

Images to inference with no labeling (use foundation models to train supervised models).

The Bio-Image Indexing and Graphical Labelling Environment (BIIGLE) is a web service for the efficient and rapid annotation of still images and videos. Read the paper or take a look at the manual.

An open source online platform for collaborative image labeling

Collaborative Annotation Toolkit for Massive Amounts of Image Data

:fire: One of the most comprehensive open-source data annotation platform.

A lightweight tool for labeling 3D bounding boxes in point clouds.

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.

PigeonXT is an extention to the original Pigeon, created by Anastasis Germanidis. PigeonXT is a simple widget that lets you quickly annotate a dataset of unlabeled examples from the comfort of your Jupyter notebook.

Data Preparation for Satellite Machine Learning

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:

Adala: Autonomous DAta (Labeling) Agent framework

Leverage machine learning algorithms to easily segment, classify, track and count your cells or other experimental data. Most operations are interactive, even on large datasets: you just draw the labels and immediately see the result. No machine learning expertise required.

Label-Detect

Create rich adata annotations in jupyter notebooks.

:pencil2: Web-based image segmentation tool for object detection, localization, and keypoints

A cross-platform desktop image annotation tool for machine learning

OpenLabeler is an open source desktop application for annotating objects for AI appplications

KNOSSOS is a software tool for the visualization and annotation of 3D image data and was developed for the rapid reconstruction of neural morphology and connectivity.

Label Objects and Save Time (LOST) - Design your own smart Image Annotation process in a web-based environment.

The open platform for image labeling Try it now » Explore docs · Report Bug · Request Feature · Join the Community

Curate, Annotate, and Manage Your Data in LightlyStudio.

A JavaFX desktop application for creating image-object-annotations with bounding boxes.

VoTT is a computer vision annotation software and machine learning dataset preparation tool. It is a desktop application designed for drawing bounding boxes and assigning tags to objects in images and videos to create training datasets for object detection models. The application utilizes a cross-platform desktop interface to manage image and video assets. It features a local-first storage integration to handle large media assets directly from the host machine's file system and includes frame-rate controlled video sampling to extract specific images from video streams for labeling. The softw

To speedup and simplify image labeling/ annotation process with multiple supported formats.

Viewers is a zero-footprint DICOMweb medical imaging viewer and a modular plugin framework. It serves as a diagnostic interface for rendering 2D and 3D medical images, providing a web-based clinical workflow engine to automate image layouts and toolsets. The project distinguishes itself through a highly extensible architecture that allows for the development of custom clinical workflows, specialized viewing modes, and the integration of external functional extensions. It includes a dedicated command line interface for managing these plugins and supports white-labeling through a comprehensive