Supervisely
Supervisely SDK for Python - convenient way to automate, customize and extend Supervisely Platform for your computer vision task
Install / Use
/learn @supervisely/SuperviselyREADME
Website: https://supervisely.com
Supervisely Ecosystem: https://ecosystem.supervisely.com
Dev Documentation: https://developer.supervisely.com
Source Code of SDK for Python: https://github.com/supervisely/supervisely
Supervisely Ecosystem on GitHub: https://github.com/supervisely-ecosystem
Complete video course on YouTube: What is Supervisely?
Table of contents
- Complete video course on YouTube: What is Supervisely?
- Table of contents
- Introduction
- Development 🧑💻
- Main features 💎
- Start in a minute
- Magically simple API
- Customization is everywhere
- Interactive GUI is a game-changer
- Develop fast with ready UI widgets
- Convenient debugging
- Apps can be both private and public
- Single-click deployment
- Reliable versioning - releases and branches
- Supports both Github and Gitlab
- App is just a web server, use any technology you love
- Built-in cloud development environment (coming soon)
- Trusted by Fortune 500. Used by 65 000 researchers, developers, and companies worldwide
- Community 🌎
- Contribution 👏
- Partnership 🤝
- Cite this Project
Introduction
Every company wants to be sure that its current and future AI tasks are solvable.
The main issue with most solutions on the market is that they build as products. It's a black box developing by some company you don't really have an impact on. As soon as your requirements go beyond basic features offered and you want to customize your experience, add something that is not in line with the software owner development plans or won't benefit other customers, you're out of luck.
That is why Supervisely is building a platform instead of a product.
Supervisely Platform 🔥
<a href="https://supervisely.com/"> <img src="https://user-images.githubusercontent.com/73014155/178843741-996aff24-7ceb-4e3e-88fe-1c19ccd9a757.png" style="max-width:100%;" alt="Supervisely Platform"> </a>You can think of Supervisely as an Operating System available via Web Browser to help you solve Computer Vision tasks. The idea is to unify all the relevant tools within a single Ecosystem of apps, tools, UI widgets and services that may be needed to make the AI development process as smooth and fast as possible.
More concretely, Supervisely includes the following functionality:
- Data labeling for images, videos, 3D point cloud and volumetric medical images (dicom)
- Data visualization and quality control
- State-Of-The-Art Deep Learning models for segmentation, detection, classification and other tasks
- Interactive tools for model performance analysis
- Specialized Deep Learning models to speed up data labeling (aka AI-assisted labeling)
- Synthetic data generation tools
- Instruments to make it easier to collaborate for data scientists, data labelers, domain experts and software engineers
Supervisely Ecosystem 🎉
<a href="https://ecosystem.supervisely.com/"> <img src="https://user-images.githubusercontent.com/73014155/178843764-a92b7ad4-0cce-40ce-b849-17b49c1e1ad3.png" style="max-width:100%;" alt="Supervisely Platform"> </a>The simplicity of creating Supervisely Apps has already led to the development of hundreds of applications, ready to be run within a single click in a web browser and get the job done.
Label your data, perform quality assurance, inspect every aspect of your data, collaborate easily, train and apply state-of-the-art neural networks, integrate custom models, automate routine tasks and more - like in a real AppStore, there should be an app for everything.
Development 🧑💻
Supervisely provides the foundation for integration, customization, development and running computer vision applications to address your custom tasks - just like in OS, like Windows or MacOS.
What developers can do
There are different levels of integration, customization, and automation:
- HTTP REST API
- Python scripts for automation and integration
- Headless apps (without UI)
- Apps with interactive UIs
- Apps with UIs integrated into labeling tools
Level 1. HTTP REST API
Supervisely has a rich HTTP REST API that covers basically every action, you can do manually. You can use any programming language and any development environment to extend and customize your Supervisely experience.
ℹ️ For Python developers, we recommend using our Python SDK because it wraps up all API methods and can save you a lot of time with built-in error handling, network re-connection, response validation, request pagination, and so on.
<details> <summary>cURL example</summary>There's no easier way to kick the tires than through cURL. If you are using an alternative client, note that you are required to send a valid header in your request.
Example:
curl -H "x-api-key: <your-token-here>" https://app.supervisely.com/public/api/v3/projects.list
As you can see, URL starts with https://app.supervisely.com. It is for Community Edition. For Enterprise Edition you have to use your custom server address.
Level 2. Python scripts for automation and integration
Supervisely SDK for Python is specially designed to speed up development, reduce boilerplate, and lets you do anything in a few lines of Python code with Supervisely Annotatation JSON format, communicate with the platform, import and export data, manage members, upload predictions from your models, etc.
<details> <summary>Python SDK example</summary>Look how it is simple to communicate with the platform from your python script.
import supervisely as sly
# authenticate with your personal API token
api = sly.Api.from_env()
# create project and dataset
project = api.project.create(workspace_id=123, name="demo project")
dataset = api.dataset.create(project.id, "dataset-01")
# upload data
image_info = api.image.upload_path(dataset.id, "img.png", "/Users/max/img.png")
api.annotation.upload_path(image_info.id, "/Users/max/ann.json")
# download data
img = api.image.download_np(image_info.id)
ann = api.annotation.download_json(image_info.i
