Auto-annotate data without doing mental gymnastics. Try the most intuitive image and video annotation platform. Label your data in seconds with V7.
After conducting an extensive research of annotation tools, we chose V7 as it fits our needs best due to its customizable workflows and automated QA.Read case study ->
V7 sped up our labeling 9–10x compared to VGG. The appeal of using V7 is that it's commercial off-the-shelf, very intuitive, and easy to use for non-technical people.Read case study ->
Thanks to V7, the image annotation is 30% faster, and considering also the QA process, we more than doubled the number of images we can label.Read case study ->
Automate labeling and gain unparalleled control of your annotation workflow. Scale your ground truth creation 10x today.
Create pixel-perfect annotations with one click. Train and test models online to improve their performance and accuracy.
Create annotation labels and segment objects with the most accurate auto-annotation tool on the market. Complete your annotation tasks faster than ever.
Get started quickly with a fast and easy setup process. Import data, create classes, and assign tasks with just a few clicks.
Use Python to streamline your data processing and model training. Use a flexible CLI & REST API to create advanced pipelines that meet all your needs!
Track changes and keep your projects organized. V7's version control features has got you covered and allow you to keep track of your training data exports.
V7 is designed to handle even the biggest files with ease. Take on high-resolution files with confidence and annotate thousands of objects without a single worry.
Meet legal industry standards and focus on your work without any hassle. You can use V7 and store your files locally to stay compliant with even the strictest regulations.
Gain insights into your data at every stage of its journey. Get access to annotators and models performance reports. Spot bottlenecks and resolve them without communication overhead.
Get the support you need, when you need it. V7's team is here for you to solve your problems and help you implement your ideas.
Start labeling right away. Thanks to V7’s intuitive UI, you’ll get your bearings the moment you open the app.
V7’s dataset management tool was developed with users in mind. Clean interface, quick preview options, detailed stats—all these make a difference.
Plug in your data, set up a workflow, and start annotating. With V7, you’ll get your labeling project up and running in a matter of minutes.
You will never walk alone. If you experience any technical issues, our support teams are just a click away.
Explore the features that world-leading AI companies take advantage of when building their AI products on V7.
V7 supports Supervisely's native file formats. See how easy it is to switch to V7 in minutes.
Annotations are formatted in JSON, which is easier to parse. V7 also offers a lot of pre-trained networks that we can utilize.
Learn why 15.000+ ML teams chose V7 over Supervisely for their computer vision projects
You can expect a seamless user experience, confidence in the stability, and reliability of V7.
Top-of-the-line performance standards, backed by regular software updates to keep you at the forefront of innovation.
Connect with V7 experts via your preferred channel for quick answers to your questions.
Receive expert support or advice whenever you need them.
Top-notch security and peace of mind for your datasets.
Your data is always safe with V7's advanced security features.
V7 can process various types of data, including images, medical imaging files, videos, volumetric series, and documents. The exact types of data that can be processed may depend on the specific use case and requirements. However, V7 supports the majority of visual data formats.
You can use V7’s Darwin-py SKD to interact with the platform via CLI or use it as a Python library. The full documentation and API reference is available in the V7 resource hub.
If you decide to train your computer vision models on our platform, all you need to do is complete at least 100 annotations of a specific class. Then, you can pick the datasets and classes to train object detection, classification, or instance segmentation models with no additional steps.
V7 offers three pricing plans: Team, Business, and Pro. The team plan starts at USD 5,000/year. For detailed pricing and feature overview, see the V7 pricing page.
Yes, V7 is equipped to handle large volumes of data for annotation. It offers efficient and scalable data management capabilities, making it a great solution for organizations with large datasets.
V7 can perform various types of annotations for tasks, including object detection, semantic segmentation, and image classification. There are multiple annotation classes, such as polygon masks, bounding boxes, keypoint skeletons for human pose estimation, etc.
V7 is a data training platform that focuses on automation and ease of use. It offers advanced machine learning capabilities, and V7’s key feature, Auto-Annotate, utilizes AI to quickly segment objects in an image, reducing the time required to make annotations by up to 10x.
V7 uses a system of credits that are consumed when you use specific tools or perform operations such as model training. When it comes to data labeling services, the cost depends on several factors, such as the size of the dataset, the complexity of the annotation tasks, and your deadline. Therefore, it's best to reach out to V7’s team to discuss your requirements and get a quote.
Customers who have used V7 have generally reported positive experiences with its automation and advanced machine-learning capabilities. V7 receives highly positive reviews on G2, a leading software review platform. Customers praise its features, ease of use, and overall effectiveness.
There is no limit to the amount of in-house labeling that can be performed using V7. It is designed to be flexible and scalable to meet the needs of various organizations and projects.
Yes, V7 can be used for in-house data labeling as it offers advanced data annotation features and can be integrated into the machine-learning team's workflow. In-house labeling is the default mode. It is a flexible and efficient platform for managing your data labeling process. But if you need help, our team can provide professional data labeling services too.
The time required to train a custom model depends on various factors, including the size of your data, the complexity of the model architecture, and the resources available for training. If you want to train or test V7 models on the platform itself, our Models feature allows you to train a model within several minutes.
V7 provides version control capabilities that enable you to manage and track changes to your models and annotated data over time. You can also use the export/import feature to revert to previous versions of your annotations if needed.
V7 takes the security and privacy of sensitive or confidential data very seriously—it’s SOC2, HIPAA, and ISO27001 compliant. It provides robust security features and implements industry-standard encryption techniques to ensure the protection of your files. Additionally, it offers flexible access controls that enable you to manage who can view and access your training data.
Yes, V7 offers a free trial version that allows you to test its features and capabilities before making a purchase. However, to unlock all the functionalities and all the potential that the platform offers, it is worth considering one of the paid plans. You can see the full feature breakdown and pricing of V7 here.
Yes, you can use V7’s data labeling service. Alternatively, you can use our computer vision models for specific tasks. For example, V7 offers several models for document processing to annotate invoices, receipts, and other documents. You can also simplify the annotation process by utilizing V7's AI-powered feature called Auto-Annotate. This feature automatically segments objects in a selected part of your image, reducing the time required to make annotations.
The V7 platform allows you to bring your own custom models, hosted on your own infrastructure. You can use them alongside the models trained using V7's own neural networks. The minimal requirements for the custom models are that they must be exposed via HTTP and make predictions in the form of JSON.
Yes, multiple people can label the same asset in V7, making it a powerful collaboration platform for your data labeling projects. V7 also includes comment tools, user permissions, or consensus stages that measure the level of agreement between different annotators, allowing you to quickly identify any discrepancies in annotations. These features help to improve the quality of your data labeling process and ensure that your annotations are accurate and consistent. With V7, you can manage large-scale data labeling projects with many collaborators.
Yes, V7 can be used with data stored on a server. V7 is designed to be flexible and can be integrated with various types of data storage solutions.