The only platform that unifies the best models, ML tools for analysis and model improvement and numerous applications built on top.
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.
Dashboard to configure and monitor training
Understand how your model works on ground truth and new data and find how to correct negative output and increase performance.
Detailed statistics for all classes in images project
Generate synthetic datasets that drastically improve model results, especially when there is not enough ground truth.
Generate synthetic data: flying foregrounds on top of backgrounds
Perform all the necessary actions on your data, from importing and converting to skeletonization of masks and rasterization.
Configure, preview and split images and annotations with sliding window
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 AppsDon'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 EcosystemMMClassification is an open source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project.
Dashboard to configure, start and monitor training
Deploy model as REST API service
MMSegmentation is an open source semantic segmentation toolbox based on PyTorch. It is a part of the OpenMMLab project.
Dashboard to configure, start and monitor training
Deploy model as REST API service
PyTorch implementation of the U-Net for image semantic segmentation with high quality images.
Dashboard to configure, start and monitor training
Deploy model as REST API service
OpenMMLab Detection Toolbox and Benchmark.
Dashboard to configure, start and monitor training
YOLOv5 🚀 is a family of object detection architectures and models pretrained on the COCO dataset.
Dashboard to configure and monitor training
Deploy model as REST API service
Detectron2 provides us Mask R-CNN Instance Segmentation baselines based on 3 different backbone combinations.
Dashboard to configure, start and monitor training
Deploy model as REST API service
Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks.
SmartTool integration of Efficient Interactive Segmentation (EISeg)
State-of-the art click-based interactive segmentation integrated into Supervisely Image Annotator.
State of the art object segmentation model in Labeleing Interface
State-of-the art Multiple Object Tracking.
Deploy model as REST API service
Visualize FairMOT checkpoints
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.
Use deployed neural network in labeling interface
Apply any deployed model on images and videos that match required criteria or to an entire project.
NN Inference on images in project or dataset
Drastically improve labeling performance with applications that can use multiple model in steps.
Use neural network in labeling interface to classify images and objects
Combine human expertise with machine performance to achieve outstanding results.
State of the art object segmentation model in Labeleing Interface
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➔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.
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