Image annotation is the process of manually defining regions in an image and creating text-based descriptions of those regions. This is a crucial first step in building the ground truth to train computer vision models. There are a wide range of use cases for image annotation, such as computer vision for autonomous vehicles or recognizing sensitive content on an online media platform.

Data scientists are often happy to automate or outsource the time-intensive and manual task of image annotation. You can use the following image annotation tools to quickly and accurately build the ground truth for your computer vision models.

Image Annotation Tools for Computer Vision

LabelImg: LabelImg is an open source graphical image annotation tool that you can use to label object bounding boxes in images.

Lionbridge AI: With over 500,000 contributors working on the Lionbridge AI platform, you can quickly annotate thousands of images and videos with relevant tags. Lionbridge AI’s image annotation services are available in 300 languages.

TrainingData.io: TrainingData.io is a medical image annotation tool for data labeling. It supports DICOM image format for radiology AI.

Spare5: Spare5 is a crowdsourcing service for tasks such as data and image annotation, language assessment, and more.

Hive: Hive is a text and image annotation service that helps you create training datasets for content categorization, computer vision, and more.

Appen: Appen provides training data for machine learning models. It provides data annotation solutions for computer vision, text annotation, automatic speech recognition, and more.

Figure Eight: Figure Eight (now an Appen company) is a data annotation platform that supports audio and speech recognition, computer vision, natural language processing, and data enrichment tasks.

Scale: Scale’s API is a data annotation outsourcing company that you can use to create the ground truth for your machine learning models.

Labelbox: Labelbox is a platform for data labeling, data management, and data science. Its features include image annotation, bounding boxes, text classification, and more.

VGG Image Annotator: VGG is an open source image labeling tool that for straightforward tasks that do not require project management. It is available as an online interface and can also be used offline as an HTML file.

Supervise.ly: Supervise.ly is an image annotation and data management tool that you can use create image and video datasets for machine learning models. The platform also includes a self-hosted infrastructure for training your machine learning models and continuing to improve them with human-in-the-loop.

RectLabel: RectLabel is an image annotation tool that you can use for bounding box object detection and segmentation, compatible with MacOS. It includes efficient features such as Core ML to automatically label images, and export to YOLO, KITTI, COCO JSON, and CSV formats.

Prodigy: Prodigy is an annotation tool for various machine learning models such as image classification, entity recognition and intent detection. You can stream in your own data from live APIs, update your model in real-time, and chain models together to build more complex systems.

Dataturks: Dataturks is a data annotation outsourcing company that offers many data annotation capabilities, including image segmentation, named entity recognition (NER) tagging in documents, and POS tagging.

ImageTagger: ImageTagger is an open source online platform for collaborative image labeling.

Fast Annotation Tool: Fast Annotation Tool is an open source online platform for collaborative image annotation for image classification, optical character reading, etc.

LabelMe: LabelMe is an open data annotation tool to build image datasets for computer vision research.

Playment: Playment is an image annotation company that you can use to build training datasets for computer vision models. The services offered include bounding boxes, cuboids, points and lines, polygons, semantic segmentation, and object recognition.

Cogito Tech: Cogito Tech provides machine learning training data. The services offered include image annotation, content moderation, sentiment analysis, chatbot training, and more.

OCLAVI: OCLAVI provides annotation tools to help machine learning models learn.

Humans in the Loop: This tool provides data labeling to train and improve your machine learning solutions. Their use cases include face recognition, autonomous vehicles, and figure detection.

WorkAround: WorkAround is a training data annotation platform for AI developers. From open data to business, you can host and annotate data, manage projects, and build datasets alongside top universities and companies.

TaQadam: TaQadam offers on-demand annotation with agents-in-the-loop. Equipped with our mobile application, agents have a simple and secure way to work on your dataset.

Anno-Mage: Anno-Mage is a new image annotation tool that incorporates an existing state-of-the-art object detection model called RetinaNet to show suggestions of 80 common object classes while annotation to reduce the amount of human effort to be put in to annotate images.