Software To Help You Turn Your Data Into AI
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Discover the 9 most popular free and paid image annotation tools to know about heading into 2023. Compare their features and pricing, and choose the best image labelling tool for your use case.
It’s 2023.
And annotating images is still one of the most time-consuming steps in bringing a computer vision project to market. To help you out, we put together a list of the most popular image annotation tools out there.
Whether you are:
This guide will help you compare the top annotation tools and find the right one for you.
We will compare each based on key factors - including annotation functionality, support for different data types and use-cases, QA/QC capabilities, security and data privacy, data management, integration with the machine learning pipeline, and customer support.
We’ll be updating this review periodically with notable feature releases and the latest annotation tools coming to market. So let's get to it!
The 9 most popular image annotation tools:
Encord Annotate is an automated annotation platform for AI-assisted image annotation, video annotation, and dataset management. It's the best option for teams that are:
Benefits & Key features:
Best for teams who:
Pricing: Free trial model with simple per-user pricing thereafter
Further reading:
Scale AI, now Scale, is a data and labeling services platform that supports image, audio, text, and video annotations. As of 2023, Scale has also expanded into new use cases, like user experience optimization, large language models, and synthetic data.
Benefits & Key features:
Best for: Workforce management
Pricing: On a per-image basis
💡 More insights on data labeling with Scale:
Teams looking for annotation tools for Autonomous Vehicle vision should know… Scale is one of the earliest platforms on the market to support 3D Sensor Fusion annotation for RADAR and LiDAR use cases, and their capabilities are some of the most widely adopted.
Teams looking for medical imaging annotation tools should know… Platforms like Scale will usually not support DICOM or NIfTI data types nor allow companies to work with their own annotators on the platform. So if you’re looking to annotate medical images, like CT, X-Ray, or MRI scans, you’ll want to look for a medical purpose-built platform (built for radiologist or physician annotators and specialist formats like DICOM and NIfTI) like Annotate.
Teams looking for labeling services should know… Scale is a very popular option for data labeling services. Other alternatives (discussed later in this article) are Appen and Playment.
CVAT (Computer Vision Annotation Tool) is a free, open-source, web-based annotation toolkit built by Intel. For image labeling - CVAT supports four types of annotations (points, polygons, bounding boxes, and polylines), as well as a subset of computer vision tasks (image segmentation, object detection, and image classification). In 2022, CVAT’s data, content, and GitHub repository were migrated over to OpenCV, where CVAT continues to be open-source.
Benefits & Key features:
Best for: Students, researchers, and academics testing the waters with image annotation (perhaps with a few images or a small dataset)
Pricing: Free!
💡 More insights on image labeling with CVAT:
If your team is looking for a free annotation tool, you should know… CVAT is one of the most popular open-source tools in the space, with over 1 million downloads since 2021 — other popular free image annotation alternatives to CVAT are 3D Slicer, Labelimg, VoTT (Visual Object Tagging Tool - developed by Microsoft), VIA (VGG Image Annotator), LabelMe, and Label Studio.
If data security is a requirement for your annotation project… Commercial labeling tools will most likely be a better fit — key security features like audit trails, encryption, SSO, and generally-required vendor certifications (like SOC2, HIPAA, FDA, and GDPR) are usually not available in open-source tools.
Further reading:
Labelbox is a US-based data annotation platform founded in 2017. Like most of the other platforms mentioned in this guide, Labelbox offers both an image labelling platform, as well as labelling services. Teams can annotate a wide range of data types (PDF, audio, images, videos, and more).
Benefits & Key features:
Best for: Teams looking for a powerful platform to quickly annotate documents and text
Pricing: Varies based on the volume of data, percent of the total volume needing to be labeled, number of seats, number of projects, and percent of data used in model training.
💡 More insights on image labeling with Labelbox:
Teams looking for document processing annotation should know that… Labelbox has been heavily investing in its Document and Conversational AI products, released in 2023. Its document annotation capabilities are quickly gaining traction, particularly within the financial services industry.
Teams carrying out annotation projects that are use-case specific should know that… As generalist tools, platforms like Labelbox are great at handling a broad variety of data types. If you’re working on a unique use-case-specific annotation project (like scans in DICOM formats or high-resolution images that require pixel-perfect annotations), other commercial image annotation platforms will be a better fit.
Playment is a fully-managed data annotation platform. The workforce labeling company was acquired by Telus in 2021 and provides computer vision teams with high-quality training data for various use cases, supported by manual labelers and a machine learning platform.
Benefits & Key features:
Best for: Teams looking for a fully managed solution to get labeled data from (just share data and label guidelines)
Pricing: Enterprise plan
Appen is a data labeling services platform founded in 1996, making it one of the first and oldest solutions in the market. The company offers data labeling services for a wide range of industries and in 2019, acquired Figure Eight to build out its software capabilities and help businesses also train and improve their computer vision models.
Benefits & Key features:
Best for: Teams looking for image data sourcing and collection alongside annotation services
Pricing: Enterprise plan
Dataloop is an Israel-based data labeling platform that provides a comprehensive solution for data management and annotation projects. The tool offers data labeling capabilities across images, text, audio, and video annotation, helping businesses train and improve their machine learning models.
Benefits & Key features:
Best for: Teams looking for a powerful platform to annotate wide variety of data types
Pricing: Free trial and an enterprise plan
💡 More insights on image labeling with Dataloop:
Teams carrying out specific image and video annotation projects that are use-case specific should know that… As generalist tools, platforms like Dataloop are built to support a wide variety of simple use cases, so other commercial platforms are a better fit if you’re trying to label use-case-specific annotation projects (like high-resolution images that require pixel-perfect annotations in satellite imaging or DICOM files for medical teams).
V7 is a UK-based data annotation platform founded in 2018. The company enables teams to annotate training data, support the human-in-the-loop processes, and also connect with annotation services. V7 offers annotation of a wide range of data types alongside image annotation tooling, including documents and videos.
Benefits & Key features:
Best for: Students or teams looking for a generalist platform to easily annotate different data types in one place (like documents, images, and short videos)
Pricing: Various options, including academic, business, and pro
Hive was founded in 2013 and provides cloud-based AI solutions for companies wanting to label content across a wide range of data types, including images, video, audio, text, and more. Hive’s platform allows engineers to bring their own pre-trained ML models into the platform, and leverage them for content moderation (including detection of AI-generated data).
Benefits & Key features:
Best for: Teams labeling images and other data types for the purpose of content moderation. Hive is especially popular with social media platforms like Reddit, BeReal, and Quora.
Pricing: Enterprise plan
There you have it! The 9 Best Image Annotation Tools for computer vision in 2023.
For further reading, you might also want to check out a few 2023 honorable mentions, both paid and free annotation tools:
Forget fragmented workflows, annotation tools, and Notebooks for building AI applications. Encord Data Engine accelerates every step of taking your model into production.