A curated list of awesome data labeling tools

• labelImg - LabelImg is a graphical image annotation tool and label object bounding boxes in images
• CVAT - Powerful and efficient Computer Vision Annotion Tool
• labelme - Image Polygonal Annotation with Python
• VoTT - An open source annotation and labeling tool for image and video assets
• imglab - A web based tool to label images for objects that can be used to train dlib or other object detectors
• Yolo_mark - GUI for marking bounded boxes of objects in images for training neural network Yolo v3 and v2
• PixelAnnotationTool - Software that allows you to manually and quickly annotate images in directories
• OpenLabeling - Label images and video for Computer Vision applications
• imagetagger - An open source online platform for collaborative image labeling
• Alturos.ImageAnnotation - A collaborative tool for labeling image data
• deeplabel - A cross-platform image annotation tool for machine learning
• MedTagger - A collaborative framework for annotating medical datasets using crowdsourcing.
• Labelbox - Labelbox is the fastest way to annotate data to build and ship computer vision applications
• turktool - A modern React app for scalable bounding box annotation of images
• Pixie - Pixie is a GUI annotation tool which provides the bounding box, polygon, free drawing and semantic segmentation object labelling
• OpenLabeler - OpenLabeler is an open source desktop application for annotating objects for AI appplications
• Anno-Mage - A Semi Automatic Image Annotation Tool which helps you in annotating images by suggesting you annotations for 80 object classes using a pre-trained model
• CATMAID - Collaborative Annotation Toolkit for Massive Amounts of Image Data
• make-sense - makesense.ai is a free to use online tool for labelling photos
• LOST - Design your own smart Image Annotation process in a web-based environment
• Annotorious - A JavaScript library for image annotation.
• Sloth - Tool for labeling image and video data for computer vision research.

• YEDDA - A Lightweight Collaborative Text Span Annotation Tool (Chunking, NER, etc.). ACL best demo nomination.
• ML-Annotate - Label text data for machine learning purposes. ML-Annotate supports binary, multi-label and multi-class labeling.
• TagEditor - Annotation tool for spaCy
• SMART - Smarter Manual Annotation for Resource-constrained collection of Training data

• EchoML - Play, visualize, and annotate your audio files
• audio-annotator - A JavaScript interface for annotating and labeling audio files.
• audio-labeler - An in-browser app for labeling audio clips at random, using Docker and Flask.
• wavesurfer.js - Simple annotations tool, check the example.
• peak.js - Browser-based audio waveform visualisation and UI component for interacting with audio waveforms, developed by BBC UK.
• Praat - Doing Phonetics By Computer
• Aubio - Tool designed for the extraction of annotations from audio signals.

• UltimateLabeling - A multi-purpose Video Labeling GUI in Python with integrated SOTA detector and tracker
• VATIC - VATIC is an online video annotation tool for computer vision research that crowdsources work to Amazon's Mechanical Turk.

• Curve - Curve is an open-source tool to help label anomalies on time-series data
• TagAnomaly - Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)
• time-series-annotator - The CrowdCurio Time Series Annotation Library implements classification tasks for time series.
• WDK - The Wearables Development Toolkit (WDK) is a set of tools to facilitate the development of activity recognition applications with wearable devices.

• KNOSSOS - 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.

• semantic-segmentation-editor - Web labelling tool for camera and LIDAR data

• Label Studio - Label Studio is a configurable data annotation tool that works with different data types
• Dataturks - Dataturks support E2E tagging of data items like video, images (classification, segmentation and labelling) and text (full length document annotations for PDF, Doc, Text etc) for ML projects.