Collaborate together with your team to transform existing assets into labeled data, trained models and deployed solutions.
How Supervisely keeps your assets organized, safe and easy to access.
When there are dozens of people constantly labeling thousands of assets that just keep popping up every day, it’s absolutely essential to store your images and videos in a structured and a well-maintained way. Luckily, Supervisely has datasets that act like folders on your desktop. Put datasets with the same settings, like classes and tags into projects.
Too many projects on a single list? Split them into workspaces and then teams with different members and access rights.
Invite or manually organize your users into private teams with custom access roles which control access to different features and resources.
Let your manager download project, but deny labeler to remove existing annotations.
Total commander inspired data manager lets you view, rename and copy anything, from teams to datasets.
Get yourself a peace of mind with built-in backup system and two-level trash bin.
Each user has a trash bin they can empty, but only an instance administrator can confirm final data removal from the server.
See your labeling statistics, annotation activity and platform insights.
Find anomalies in number of classes labeled or sizes.
Don’t worry about formats, import and export — focus on what’s important.
You don’t have to convert your existing data into Supervisely format before uploading: not only we support practically every file type imaginable, from your everyday .jpeg to uncommon .tiff, we already have built-in converters from dozens of popular dataset formats like Pascal VOC, Cityscapes or KITTI.
Export just .json annotations in Supervisely Format, an entire project with images or videos or even select of built-in conversion scripts to automatically generate output in a desired format, say, binary masks for image segmentation, YOLO format, or even code your custom “Download as...” context item — it’s super easy with our Python SDK!
Datasets, object classes, key-value tags and many other things that build a project in Supervisely can easily be represented as a bunch of .json files ready to be imported in or exported out without losing any of project settings and annotated objects information.
Moreover, Supervisely Format is not just a file format description — it comes with a Python SDK, that helps you load, modify and export your datasets programmatically without even knowing how it’s built inside. Converting existing labels into Supervisely Format is very simple!
No matter where you data is — Supervisely works great with remote storages.
You already have Terabytes of videos on a remote storage like AWS S3, Azure Cloud, GCS or even an internal HTTP web server? No need to worry about uploading it again!
Set credentials, browse your remote storage via built-in application and select images or videos to form a project in Supervisely — your assets will fetch in labeling interface your from remote storage with on-fly protection from direct access.
By default Supervisely stores its data locally on your server hard disk. But what if you run out of space and trash bin is already empty?
No worries! Connect a remote cloud storage, including AWS S3, Azure Cloud and GCS and forget about free space ever again — your uploads and generated artifacts will be automatically saved on this cloud storage.
Avoid mistakes and don’t lose time with multi-level quality assurance process.Learn more
Collaborate with your team to transform existing assets into labeled data.Learn more
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We use Supervisely since 2019. The key advantage of this tool is that Supervisely provides a complete data treatment pipeline. An important advantage is that a Supervisely instance can be deployed autonomously on a Client infrastructure, and distributed on different servers.
It helps to treat enterprise’s internal and often confidential data in a secured way. Together with a user-friendly interface, a clear documentation and a friendly and reactive support team it helps us to do Data Scientist work better and faster.”
We originally set out to look for tools that could help us with data annotation, and we discovered that Supervisely excels at that and much more. It has become an integral part of our workflow in annotation, model training, and evaluation.
We've been exceedingly impressed with the customer support, addition of new features, and the flexibility of the publicly available SDK/API. The Supervisely team has also been fast to respond to support questions, and has shown a lot of openness when given feedback on potential improvements.
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