All the right tools to get the job done

Configure every aspect of training from target classes to online augmentations, monitor metrics and terminal logs in real-time.

Noticeable example app:

Train YOLOv5

Dashboard to configure and monitor training

Visualize, analyze and improve performance

Understand how your model works on ground truth and new data and find how to correct negative output and increase performance.

Noticeable example app:

Classes stats for images

Detailed statistics for all classes in images project

Apply models in various scenarios and interfaces

Put pre-trained or custom neural network models to use in labeling interfaces to archive extraordinary results.

Noticeable example app:

RITM interactive segmentation SmartTool

State of the art object segmentation model in Labeleing Interface

Boost training with synthetic data

Generate synthetic datasets that drastically improve model results, especially when there is not enough ground truth.

Noticeable example app:

Flying objects

Generate synthetic data: flying foregrounds on top of backgrounds

Query and transform, run augmentations

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Perform all the necessary actions on your data, from importing and converting to skeletonization of masks and rasterization.

Noticeable example app:

Sliding window split

Configure, preview and split images and annotations with sliding window

Visualizations

Get to the core of things

With so many things you can on Supervisely, it's essential to have a clear and streamlined way to transform existing information on the platform into meaningful reports and charts. Luckily, Supervisely has all the right tools:

API & SDK + App Engine + Widgets Library = Apps, Apps, Apps!

Labeling performance

Powered by the following apps:

Labeling Jobs Stats

General statistics for all labeling jobs in team

Labeling Events Stats

Total number of labeling actions and annotated unique images in a time interval

Objects stats

Powered by the following apps:

Object Size Stats

Detailed statistics and distribution of object sizes (width, height, area)

Labels spatial distribution

Build labels distribution heatmap for dataset.

Classes stats for images

Detailed statistics for all classes in images project

Improvements

Transforming insights into actions

Visualizations you have seen can be presented in a form of static reports — a great tool to summarize information and give you a better understanding of what's going on.

But it becomes a much more useful instrument, when you add communication loop into this formula. Now, with the help of interactive widgets, we can build complex tools that significantly boost performance in many tasks across the platform.

Visualizations + Actions

Powerful Tools

Example: Object detection metrics

Powered by the following apps:

Object detection metrics

Interactive Confusion matrix, mAP, ROC and more

Confusion matrix for selected classes provides a descriptive information about false positive outputs: say, we see that there are 11 images on which birds were detected as dogs.

Next, we can click on the cell and see those images:

Now, if we select an image, we can clearly see the error. We can immediately open the image in labeling tool and fix the mistake or create a new issue in issue tracker.

There is more numbers and dimensions you can explore, such as per-classes metrics. Let's select "chair" class and sort Table widget to find images with the largest amount of chairs:

Or see overall picture with per-image metrics:

Find more visualizations in
Supervisely Ecosystem

Constantly growing ecosystem of hundreds of ready-to-use apps that extend and add new functionality.

Learn about Ecosystem

SUPERVISELY FOR ENTERPRISES

On-premise edition built for your business

A fully customizable AI infrastructure, deployed on cloud or your servers with everything you love about Supervisely, plus advanced security, control, and support.

Maximum security: hosted behind firewall on your servers with advanced governance and privacy settings
Effortless integrations: single sign-on with LDAP or OpenID, cloud storage in AWS or Azure and powerful API & SDK
Priority support: dedicated slack chat, guided onboarding and personalized training sessions with experts

supervisely install
> downloading pre-requirements...
> pulling docker images...
> installing software...
> Done! Supervisely is running on port :80

supervisely update
> checking for updates...
> Your version is up to date!

#support

Team Manager 17:33

Hello @supervisely! Is there a way to create a project via API?

Supervisely 17:35

Sure thing, check out this docs!

Here’s why our customers trust us

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.

Dmitriy Slutskiy

PhD Research Engineer

BMW Group is using the Supervise.ly solution to create automated verifications for ensuring a very high product quality across the whole production chain in vehicle and vehicle component manufacturing.

BMW Group uses Supervise.ly to annotate manufacturing images from production lines in their world-wide plants for enhancing quality inspections using deep learning. The Supervise.ly tooling also supports the process for continuously updating AI models using semi-automated labeling.

Supervise.ly is integrated into the BMW Group AI Platform in order to empower computer vision based AI use cases.

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.

Travis Prosser

Engineering Specialist

We have been using Supervisely for a few years now to help label and organize our data for AI training. The interface is user-friendly and the tools are intuitive to use, which has made the annotation process much more efficient for our team. We run Supervisely locally, which allows us to stay in control of our data. We also use Supervisely for annotation reviews, and the review tools have been invaluable in ensuring the quality and accuracy. The Python SDK has also been incredibly helpful in automating and streamlining our workflow. In addition, the support team on Slack has been extremely helpful and responsive. The ability to collaborate with my colleagues on the same project has also been a huge time-saver.

Overall, we have been extremely satisfied with Supervisely and would highly recommend it to anyone in need of a reliable and efficient annotation solution.

Mike Slembrouck

CTO