The only platform that unifies the best models, ML tools for analysis and model improvement and numerous applications built on top.
Build models from labeled data using the best architectures
Deploy trained models as API on cluster and use in other Apps
Use served models in infinite various applications
New models are easy to integrate by forking and wrapping
Integrate your model to benefit from Apps in Ecosystem
Explore our growing collections of machine learning tools
Create custom labeling UIs tailored for your task
Because Supervisely is built like OS for computer vision, we made possible integration of the best machine learning models and tools on a single platform.
You will find a well-known projects from data science community, as well as our own Apps, providing a complete solution for entire AI development pipeline.
Configure every aspect of training from target classes to online augmentations, monitor metrics and terminal logs in real-time.
Understand how your model works on ground truth and new data and find how to correct negative output and increase performance.
Put pre-trained or custom neural network models to use in labeling interfaces to archive extraordinary results.
Generate synthetic datasets that drastically improve model results, especially when there is not enough ground truth.
You noticed we have some of the best models and machine learning tools integrated to Supervisely and maybe thinking right now: why is better to use them as Supervisely Apps instead of cloning a GitHub repo and setting things up yourself?More about Apps
Don't waste dozen of hours figuring out how to install, configure and adapt another model from the internet — we did the hard part for you.
Thanks to streamlined way of building interfaces with Supervisely Apps, we can add GUI simplify interaction with integrated code.
Run automatically generated command in terminal to run Supervisely Agent and simply deploy new training tasks with a few clicks.
Since now those models and tools run in web and not on your personal PC, you can easily share and collaborate with your team members.
Project converted to App gets access to the whole Ecosystem: import from different formats, visualization, exploration and much more!
Feel to free explore Supervisely Ecosystem and find more integrated projects and, on top of that, much more custom built solutions by Community and Supervisely Team.Explore Ecosystem
MMClassification is an open source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project.
MMSegmentation is an open source semantic segmentation toolbox based on PyTorch. It is a part of the OpenMMLab project.
PyTorch implementation of the U-Net for image semantic segmentation with high quality images.
OpenMMLab Detection Toolbox and Benchmark.
YOLOv5 🚀 is a family of object detection architectures and models pretrained on the COCO dataset.
Detectron2 provides us Mask R-CNN Instance Segmentation baselines based on 3 different backbone combinations.
Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks.
State-of-the art click-based interactive segmentation integrated into Supervisely Image Annotator.
State-of-the art Multiple Object Tracking.
OpenMMLab's next-generation platform for general 3D object detection.
An extension of Open3D to address 3D Machine Learning tasks.
Connect your machines (servers or PCs) to Supervisely by running automatically generated command in the terminal. It starts Supervisely Agent — a tiny program that let's you run Supervisely Apps.
Start training neural networks, serve models, run various machine learning tools and other Apps from our Ecosystem right from the web interface.
We handle all the boring configuration, monitoring and log collection routine for you — simple focus on what you like!
bash <(curl -s "https://app.supervisely.com/api/agent/tkqvwSTC0ca5")
Most of our integrated models are trainable and each corresponding Supervisely App comes all the necessary functionality for effective model training.
You can configure every aspect of training from target classes to online augmentations, monitor metrics, visualizations and terminal logs in real-time.
Training supports multiple strategies for train / validation splits: random split with defined percentage, based on image tags or datasets.
Choose model architecture or how weight should be initialized.
Run a pre-trained model or your custom trained weights and deploy it on any machine, connected via Supervisely Agent.
Carefully selected machine learning toolboxes with open licenses and state-of-the-art models
Create and publish a new GitHub repo to Ecosystem by adding a simple bootstrap code
Create and publish a new GitHub repo to Ecosystem by adding a simple bootstrap code
Explore ecosystem of ready-to-use Supervisely Apps that work on top of deployed neural networks and supercharge various aspects of labeling with AI.
No-code integration of any deployed model in our labeling tools lets annotators apply AI in one click.
Apply any deployed model on images and videos that match required criteria or to an entire project.
Drastically improve labeling performance with applications that can use multiple model in steps.
Combine human expertise with machine performance to achieve outstanding results.
A fully customizable AI infrastructure, deployed on cloud or your servers with everything you love about Supervisely, plus advanced security, control, and support.Start 30 days free trial➔
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.
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.
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.
Supervisely provides first-rate experience since 2017, longer than most of computer vision platforms over there.
Join community of thousands computer vision enthusiasts and companies of every size that use Supervisely every day.
Our online version has over a 220 million of images and over a billion of labels created by our great community.
Speak with people who are on the same page with you. An actual data scientist will:
Get accurate training data on scale with expert annotators, ML-assisted tools, dedicated project manager and the leading labeling platform.Order workforce