List of the Top 25 Free Image Annotation Tools in 2025

Vertex AI offers a robust image annotation feature that helps organizations prepare visual datasets for training computer vision models. By identifying and tagging various elements, attributes, or specific areas within images, companies can develop more precise and tailored models for applications such as object detection and facial recognition. The platform includes both automated and manual annotation functionalities, allowing users to efficiently manage extensive amounts of image data while ensuring top-notch quality in annotations for machine learning algorithms. New users can take advantage of a $300 credit to explore the image annotation features available. This functionality empowers businesses to expedite the creation of visual AI solutions, enhancing the precision and dependability of their models.

APISCRAPY is a platform utilizing artificial intelligence to perform web scraping and automation, transforming any online data into actionable data APIs. AIMLEAP also offers a variety of other data solutions including: AI-Labeler: A tool that enhances annotation and labeling with AI assistance. AI-Data-Hub: Provides on-demand data essential for developing AI products and services. PRICE-SCRAPY: An AI-powered tool for real-time pricing data. API-KART: A comprehensive hub for AI-driven data API solutions. About AIMLEAP AIMLEAP is a globally recognized technology consulting and service provider, holding ISO 9001:2015 and ISO/IEC 27001:2013 certifications, specializing in AI-enhanced Data Solutions, Data Engineering, Automation, IT, and Digital Marketing services. The company has earned the distinction of being certified as ‘The Great Place to Work®’. Since its inception in 2012, AIMLEAP has successfully executed projects focused on IT and digital transformation, automation-based data solutions, and digital marketing for over 750 rapidly growing companies around the world. With a presence in multiple countries, AIMLEAP operates in the USA, Canada, India, and Australia, ensuring accessible support for its global clientele.

Ango Hub serves as a comprehensive and quality-focused data annotation platform tailored for AI teams. Accessible both on-premise and via the cloud, it enables efficient and swift data annotation without sacrificing quality. What sets Ango Hub apart is its unwavering commitment to high-quality annotations, showcasing features designed to enhance this aspect. These include a centralized labeling system, a real-time issue tracking interface, structured review workflows, and sample label libraries, alongside the ability to achieve consensus among up to 30 users on the same asset. Additionally, Ango Hub's versatility is evident in its support for a wide range of data types, encompassing image, audio, text, and native PDF formats. With nearly twenty distinct labeling tools at your disposal, users can annotate data effectively. Notably, some tools—such as rotated bounding boxes, unlimited conditional questions, label relations, and table-based labels—are unique to Ango Hub, making it a valuable resource for tackling more complex labeling challenges. By integrating these innovative features, Ango Hub ensures that your data annotation process is as efficient and high-quality as possible.

Our software is capable of recognizing objects within images and videos. With only a handful of images, you can effectively train a computer vision model, often completing the process in under a day. We are dedicated to assisting innovators like you in harnessing the power of computer vision technology. You can conveniently upload your files either through an API or manually, encompassing images, annotations, videos, and audio content. We offer support for various annotation formats, making it straightforward to incorporate training data as you collect it. Roboflow Annotate is specifically designed for swift and efficient labeling, enabling your team to annotate hundreds of images in just a few minutes. You can evaluate your data's quality and prepare it for the training phase. Additionally, our transformation tools allow you to generate new training datasets. Experimentation with different configurations to enhance model performance is easily manageable from a single centralized interface. Annotating images directly from your browser is a quick process, and once your model is trained, it can be deployed to the cloud, edge devices, or a web browser. This speeds up predictions, allowing you to achieve results in half the usual time. Furthermore, our platform ensures that you can seamlessly iterate on your projects without losing track of your progress.

SuperAnnotate stands out as a premier platform for developing superior training datasets tailored for natural language processing and computer vision. Our platform empowers machine learning teams to swiftly construct precise datasets and efficient ML pipelines through a suite of advanced tools, quality assurance, machine learning integration, automation capabilities, meticulous data curation, a powerful SDK, offline access, and seamless annotation services. By unifying professional annotators with our specialized annotation tool, we have established an integrated environment that enhances the quality of data and streamlines the data processing workflow. This holistic approach not only improves the efficiency of the annotation process but also ensures that the datasets produced meet the highest standards of accuracy and reliability.

Roora provides exceptional data annotation services specifically designed for machine learning applications, concentrating on the tagging of images, videos, and text across various industries like healthcare, autonomous vehicles, and retail. Utilizing cutting-edge methods such as bounding boxes, semantic segmentation, and object detection, Roora enables organizations to enhance the efficacy of their AI models significantly. The skilled team behind the platform ensures that the data labeling process is accurate, scalable, and secure, which greatly enhances the ability of AI systems to recognize and classify visual components in real-world applications, including facial recognition, medical diagnostics, and self-driving technology. This unwavering dedication to excellence and innovation establishes Roora as a frontrunner in the data annotation field, propelling the evolution of AI technology. Moreover, their expertise ensures that clients receive tailored solutions that meet their specific needs, further solidifying Roora's reputation in the industry.

Clarifai stands out as a prominent AI platform adept at processing image, video, text, and audio data on a large scale. By integrating computer vision, natural language processing, and audio recognition, our platform serves as a robust foundation for developing superior, quicker, and more powerful AI applications. We empower both enterprises and public sector entities to convert their data into meaningful insights. Our innovative technology spans various sectors, including Defense, Retail, Manufacturing, and Media and Entertainment, among others. We assist our clients in crafting cutting-edge AI solutions tailored for applications such as visual search, content moderation, aerial surveillance, visual inspection, and intelligent document analysis. Established in 2013 by Matt Zeiler, Ph.D., Clarifai has consistently been a frontrunner in the realm of computer vision AI, earning recognition by clinching the top five positions in image classification at the prestigious 2013 ImageNet Challenge. With its headquarters located in Delaware, Clarifai continues to drive advancements in AI, supporting a wide array of industries in their digital transformation journeys.

V7 Darwin is an advanced platform for data labeling and training that aims to streamline and expedite the generation of high-quality datasets for machine learning applications. By utilizing AI-enhanced labeling alongside tools for annotating various media types, including images and videos, V7 enables teams to produce precise and uniform data annotations efficiently. The platform is equipped to handle intricate tasks such as segmentation and keypoint labeling, which helps organizations optimize their data preparation workflows and enhance the performance of their models. In addition, V7 Darwin promotes real-time collaboration and allows for customizable workflows, making it an excellent choice for both enterprises and research teams. This versatility ensures that users can adapt the platform to meet their specific project needs.

Your AI Data Platform Top-Notch Training Data for Businesses Data Annotation Software for Machine Learning Enjoy a free Kubernetes Cluster for up to 3 users RELIED ON BY 5,000 SATISFIED UBERS GLOBALLY Images, Videos, and Text Spatial Tools Quadratic Curves and Cuboids, Segmentation Boxes, Polygons and Lines, Keypoints, Classification Tags, and More You have access to the precise spatial tool you require. Each tool is user-friendly, customizable, and provides robust options for data presentation, with all tools available in Video format. Attribute Tools Enhanced Meaning. Greater flexibility through: Radio buttons, Multiple selections, Date pickers, Sliders, Conditional logic, Directional vectors, and much more! Intricate knowledge can be captured and encoded into your AI systems, facilitating deeper insights. Streaming Data Automation Manual labeling can surpass automated labeling in speed by up to 10 times, significantly improving efficiency. Moreover, this rapid labeling process enhances project turnaround times, fostering quicker insights and development.

Leverage the power of UBIAI's cutting-edge labeling platform to significantly boost the speed of your personalized NLP model's training and deployment like never before! When working with semi-structured documents, such as invoices or contracts, it is crucial to retain the original formatting to ensure effective model training. By combining natural language processing with advanced computer vision techniques, UBIAI’s OCR capabilities enable you to perform tasks like named entity recognition (NER), relation extraction, and document classification directly on native PDF files, scanned images, or photos taken with a smartphone, all while keeping essential layout elements intact, resulting in a substantial improvement in the performance of your NLP model. The UBIAI text annotation tool allows for seamless execution of NER, relation extraction, and document classification tasks within a single, intuitive interface. In contrast to many other platforms, UBIAI uniquely supports the creation of nested and overlapping entities that represent multiple relationships, thus enhancing your data annotation efforts. This distinctive feature not only streamlines your workflow but also deepens the insights that your model can derive, ultimately leading to a more effective and comprehensive understanding of the data. Additionally, this streamlined process encourages collaboration among team members, fostering a more productive environment for model development.

Our organization stands out as the leading provider of data labeling services tailored for AI applications. We serve a diverse array of sectors including Automotive, Robotics, Fintech, Healthcare, E-commerce, Manufacturing, and Insurance. With a dedicated team of over 500 annotation specialists and support in multiple languages, we deliver precise and efficient services catering to both enterprise-level and R&D initiatives. Our offerings encompass a wide range of services such as Computer Vision and NLP annotation, comprehensive data processing, and beyond. By choosing Label Your Data, you can expect unmatched excellence in the quality of your training datasets. We prioritize the security and integrity of our clients' data above all else. To uphold the confidentiality of client information, our facilities and personnel have received certifications from ISO 27001 and PCI DSS (level 1), demonstrating our commitment to industry-leading security. Additionally, we strictly comply with essential industry regulations such as GDPR and CCPA, ensuring that your data remains protected at all times. Our unwavering dedication to quality and security makes us the ideal partner for your data labeling needs.

makesense.ai is a user-friendly online platform tailored for photo labeling, allowing users to bypass any installation concerns by simply accessing the website. It aims to deliver a truly cross-platform experience, making it compatible with any operating system. This tool is especially beneficial for small-scale deep learning initiatives in the field of computer vision, greatly simplifying the dataset preparation stage. Once users finish their labeling tasks, they can conveniently download the data in various formats that are supported. Developed with TypeScript, the application employs the robust combination of React and Redux, which contributes to a seamless and productive user experience. Thanks to its intuitive interface and flexible functionality, makesense.ai serves as an invaluable asset for both researchers and developers alike. Additionally, its ease of use encourages newcomers to explore the realm of photo labeling without feeling overwhelmed.

Enable a diverse range of annotation types for images and videos through a versatile, open-source web tool. This platform is built to scale effectively and features user-friendly “click and drag” capabilities that simplify the process of adding numerous attributes. It includes functionalities that allow the fitting of boundaries with Bezier curves and the option to duplicate common boundaries, enhancing efficiency. Users can pinpoint the specific areas where a driver is active and delineate lane lines, which is crucial for improving vision-based vehicle localization and trajectory planning. An easy four-click approach is utilized to precisely encapsulate objects of interest, while sophisticated algorithms leverage object tracking and interpolation methods to forecast annotations across different frames for bounding boxes. The tool also extends its prediction capabilities to individual object instances, with 2D tracking that has been further developed into a three-dimensional framework, thereby enriching the overall annotation experience. By incorporating these advanced features, this tool strives to optimize the workflow for individuals engaged in tasks related to image and video annotation, ultimately leading to enhanced productivity and accuracy. Furthermore, the platform's adaptability ensures that it can cater to the evolving needs of various users in this field.

An offline image annotation tool is designed to support both object detection and segmentation tasks effectively. Users can create various shapes such as polygons, cubic bezier curves, line segments, and points for accurate labeling of images. It also enables the drawing of oriented bounding boxes, particularly useful for aerial imagery analysis. Additionally, the tool allows users to label key points that can be interconnected by skeletons and offers the capability to paint pixels using brushes or superpixels. It ensures compatibility with different machine learning formats by supporting both PASCAL VOC XML and YOLO text reading and writing. Furthermore, users have the option to export their annotated data to CreateML for object detection and image classification tasks, as well as to COCO, Labelme, YOLO, DOTA, and CSV formats. The tool accommodates diverse project requirements by enabling the export of indexed color mask images and grayscale mask images. Users can easily modify settings related to objects, attributes, hotkeys, and fast labeling features to enhance their workflow efficiency. A customizable label dialog allows for smooth integration with attributes, and one-click buttons streamline the selection of object names. With an impressive auto-suggest feature that considers over 5000 object names, users can search for objects, attributes, and image names conveniently in a gallery view. Automatic labeling is facilitated through Core ML models, and the tool includes OCR technology for automatic text recognition. It also offers features to convert videos into image frames and execute image augmentation tasks. Language support covers English, Chinese, Korean, and 11 additional languages, thus catering to a wide-ranging user base and boosting productivity across various regions.

Mindkosh serves as your ultimate data management solution, simplifying the processes of curating, tagging, and authenticating datasets for artificial intelligence projects. Our exceptional data annotation platform integrates collaborative features with AI-driven tools, offering a comprehensive suite for classifying various data formats, such as images, videos, and 3D point clouds derived from Lidar technology. With regard to images, Mindkosh provides cutting-edge semi-automated segmentation, pre-labeling of bounding boxes, and fully automated OCR functionalities. In the realm of video annotation, the use of automated interpolation by Mindkosh greatly minimizes the requirement for manual labeling efforts. For Lidar datasets, our single-click annotation functionality allows for rapid cuboid creation with just one click, enhancing efficiency. If your primary goal is to have your data labeled, our superior data annotation services, paired with an intuitive Python SDK and a user-friendly web-based review system, deliver an unparalleled experience that stands out in the industry. Additionally, we are dedicated to ensuring that our platform continuously evolves to meet the changing demands of data management in AI applications.

Dokit manual software enables users to design, distribute, and monitor visual instructions, user manuals, and optimal practices suitable for any type of screen or device. The platform boasts a range of functionalities, including Cataloging/Categorization, collaborative tools, customizable Page templates, a user-friendly Visual editor, Drag & Drop capabilities, a Media Gallery, Image annotation features, multilingual support, the ability to import documents, an Approval workflow, notification systems, as well as forums and comment sections for enhanced communication. Additionally, Dokit stands as a viable alternative to competitor software such as Swipeguide and Speachme, making it a versatile choice for various instructional needs.

Our leading-edge platform designed for the entire computer vision workflow enables a transformation from image annotation to accurate neural networks at speeds that can reach ten times faster than traditional methods. With our outstanding data labeling capabilities, you can turn your images, videos, and 3D point clouds into high-quality training datasets. This not only allows you to train your models effectively but also to monitor experiments, visualize outcomes, and continuously refine model predictions, all while developing tailored solutions in a cohesive environment. The self-hosted option we provide guarantees data security, offers extensive customization options, and ensures smooth integration with your current technology infrastructure. This all-encompassing solution for computer vision covers multi-format data annotation and management, extensive quality control, and neural network training within a single platform. Designed by data scientists for their colleagues, our advanced video labeling tool is inspired by professional video editing applications and is specifically crafted for machine learning uses and beyond. Additionally, with our platform, you can optimize your workflow and markedly enhance the productivity of your computer vision initiatives, ultimately leading to more innovative solutions in your projects.

Elevate your annotation workflow with CVAT, a leading data engine for machine learning utilized by teams across various sizes and handling datasets of any scale. Designed with input from real-world teams facing practical challenges, CVAT boasts a rapid and intuitive interface, making it the preferred tool for innovative AI developers in multiple industries, including healthcare, retail, and self-driving technology. Daily, top-tier AI professionals incorporate CVAT into their processes, ensuring seamless project execution regardless of the data type or desired outcomes. CVAT shines with its compatibility across diverse formats such as images, videos, and 3D models, providing a rich selection of annotation tools like bounding boxes, polygons, points, skeletons, cuboids, and trajectories. Enhance your efficiency with sophisticated interactive features like intelligent scissors and histogram equalization, tailored to refine the annotation process. Moreover, CVAT offers insightful metrics such as annotator hours worked and objects annotated hourly, empowering teams to fine-tune their productivity for improved outcomes. With its extensive capabilities and adaptability, CVAT emerges as a crucial resource for any AI-centered initiative, paving the way for innovative developments in the field. Utilizing CVAT not only streamlines the annotation process but also positions teams to stay ahead in the competitive landscape of artificial intelligence.

Presenting a revolutionary data annotation tool that combines exceptional flexibility with straightforward installation processes. Users have the option to design personalized user interfaces or select from pre-existing labeling templates that suit their unique requirements. The versatile layouts and templates align effortlessly with your dataset and workflow needs. This tool supports a variety of object detection techniques in images, such as boxes, polygons, circles, and key points, as well as the ability to segment images into multiple components. Moreover, it allows for the integration of machine learning models to pre-label data, thereby increasing efficiency in the annotation workflow. Features including webhooks, a Python SDK, and an API empower users to easily authenticate, start projects, import tasks, and manage model predictions with minimal hassle. By utilizing predictions, users can save significant time and optimize their labeling processes, benefiting from seamless integration with machine learning backends. Additionally, this platform enables connections to cloud object storage solutions like S3 and GCP, facilitating data labeling directly in the cloud. The Data Manager provides advanced filtering capabilities to help you thoroughly prepare and manage your dataset. This comprehensive tool supports various projects, a wide range of use cases, and multiple data types, all within a unified interface. Users can effortlessly preview the labeling interface by entering simple configurations. Live serialization updates at the page's bottom give a current view of what the tool expects as input, ensuring an intuitive and smooth experience. Not only does this tool enhance the accuracy of annotations, but it also encourages collaboration among teams engaged in similar projects, ultimately driving productivity and innovation. As a result, teams can achieve a higher level of efficiency and coherence in their data annotation efforts.

ImgLab is a free tool designed to simplify the image annotation process for machine learning and artificial intelligence projects. With its intuitive interface, users can annotate images using different types of metadata such as bounding boxes, points, lines, and polygons to emphasize specific features or objects within the images. It supports multiple annotation formats, including COCO, Pascal VOC, and YOLO, ensuring that it works seamlessly with various machine learning models and platforms. Furthermore, ImgLab is capable of managing large image datasets, making it especially useful for addressing complex challenges in machine learning. This range of functionalities makes ImgLab an essential asset for both researchers and developers working in the AI sector. As the demand for effective image annotation tools continues to grow, ImgLab stands out as a reliable choice for enhancing productivity in AI-related tasks.

The entire machine learning and computer vision workflow is simplified and accelerated through a unified no-code platform. Sense enables users to design and deploy AI IoT solutions in diverse settings, whether in the cloud, on-site, or at the edge. Learn how Sense provides simplicity, reliability, and transparency for AI/ML teams, equipping machine learning engineers with powerful tools while remaining user-friendly for non-technical experts. With Sense Data Annotation, users can effectively label video and image data, improving their machine learning models and ensuring the development of high-quality training datasets. The platform also includes one-touch labeling integration, which facilitates continuous machine learning at the edge and streamlines the management of all AI applications, thus enhancing both efficiency and performance. This all-encompassing framework positions Sense as an essential asset for a variety of users, making advanced technology accessible to those with varying levels of expertise. Additionally, the platform's flexibility allows for rapid adaptation to evolving project requirements and fosters collaboration among teams.

Segments.ai delivers a comprehensive solution for annotating multi-sensor data by integrating 2D and 3D point cloud labeling into a single interface. The platform boasts impressive capabilities such as automated object tracking, intelligent cuboid propagation, and real-time interpolation, which facilitate faster and more precise labeling of intricate datasets. Specifically designed for sectors like robotics and autonomous vehicles, it streamlines the annotation process for data that relies heavily on various sensors. By merging 3D information with 2D visuals, Segments.ai significantly improves the efficiency of the labeling process while maintaining the high standards necessary for effective model training. This innovative approach not only simplifies the user experience but also enhances the overall data quality, making it invaluable for industries reliant on accurate sensor data.

Innotescus serves as a platform for annotating images and videos, fostering teamwork and efficient data management. By enhancing Computer Vision development, it offers user-friendly collaboration tools and intelligent annotation features that simplify the data handling process. Additionally, its data visualization capabilities and collaborative functions facilitate the early detection of data bias, thereby increasing the overall accuracy of the data. As a result, organizations can achieve quicker and more economical implementations of advanced Artificial Intelligence solutions. Ultimately, this platform not only promotes efficiency but also supports the development of more reliable AI systems.

High-quality data is essential for optimizing model performance to its fullest potential. You can generate and oversee training data tailored for various visual modalities. By troubleshooting models, enhancing performance, and personalizing foundational models, you can elevate your work. Implementing expert review, quality assurance, and quality control workflows enables you to provide superior datasets for your AI teams, leading to increased model efficacy. Encord's Python SDK facilitates the integration of your data and models while enabling the creation of automated pipelines for the training of machine learning models. Additionally, enhancing model precision involves detecting biases and inaccuracies in your data, labels, and models, ensuring that every aspect of your training process is refined and effective. By focusing on these improvements, you can significantly advance the overall quality of your AI initiatives.

Artificio, developed by Artificio Products Inc., represents a revolutionary automation tool designed to overhaul the data processing sector by eliminating the necessity for manual input of data. This cutting-edge software utilizes state-of-the-art AI and machine learning technologies to adeptly extract, organize, validate, and integrate unstructured data from multiple sources, including texts, PDFs, and images. By transforming various forms of unstructured information into coherent structured data, Artificio empowers organizations to maximize their digital intelligence capabilities, resulting in enhanced decision-making and greater operational efficiency. Its novel methodology paves the way for enterprises to refine their data management strategies significantly. Ultimately, Artificio not only streamlines complex data workflows but also fosters a more data-driven culture within organizations.