docs: Update README

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rushtehrani
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[![license](https://img.shields.io/github/license/onepanelio/core?color=01579b)](https://opensource.org/licenses/Apache-2.0) [![license](https://img.shields.io/github/license/onepanelio/core?color=01579b)](https://opensource.org/licenses/Apache-2.0)
Production scale, Kubernetes-native vision AI platform, with fully integrated components for model building, automated labeling, data processing and model training pipelines. Production scale, vision AI platform, with fully integrated components for model building, automated labeling, data processing and model training pipelines.
<img width="100%" src="img/onepanel.gif">
## Why Onepanel? ## Why Onepanel?
- End-to-end workflow and infrastructure automation for production scale vision AI - End-to-end automation for production scale vision AI pipelines
- Automatic resource management and on-demand scaling of CPU and GPU nodes - Best of breed, open source deep learning tools seamlessly integrated in one unified platform
- Easily scale your data processing and training pipelines to multiple nodes - Infrastructure automation so you can easily scale your data processing and training pipelines to multiple nodes
- Collaborate on all your deep learning tools and workflows through a unified web interface and SDKs - Customizable, reproducible and version controlled tooling and pipeline templates
- Scalability, flexibility and resiliency of Kubernetes without the deployment and configuration complexities - Scalability, flexibility and resiliency of Kubernetes without the deployment and configuration complexities
## Features ## Features
<table> - Annotate images and video with automatic annotation of bounding boxes and polygon masks, integrated with training pipelines to iteratively improve models for pre-annotation and inference.
<tr> - JupyterLab configured with extensions for debugging, Git/GitHub, notebook diffing and TensorBoard and support for Conda, OpenCV, Tensorflow and PyTorch with GPU and <a href="https://github.com/onepanelio/templates/tree/master/workspaces/jupyterlab">much more</a>.
<td width="50%" align="center"> - Build fully reproducible, distributed and parallel data processing and training pipelines with real-time logs and output snapshots.
<h3>Image and video annotation with automatic annotation</h3> - Bring your own IDEs, annotation tools and pipelines with a version controlled YAML and Docker based template engine.
<img width="100%" src="img/auto-annotation.gif">
<p>
Annotate images and video with automatic annotation of bounding boxes and polygon masks, integrated with training pipelines to iteratively improve models for pre-annotation and inference
</p>
</td>
<td width="50%" align="center">
<h3>JupyterLab with TensorFlow, PyTorch and GPU support</h3>
<img width="100%" src="img/jupyterlab.gif">
<p>
JupyterLab configured with extensions for debugging, Git/GitHub, notebook diffing and TensorBoard and support for Conda, OpenCV, Tensorflow and PyTorch with GPU and <a href="https://github.com/onepanelio/templates/tree/master/workspaces/jupyterlab">much more</a>
</p>
</td>
</tr>
<tr>
<td width="50%" align="center">
<h3>Auto scaling, distributed and parallel data processing and training pipelines</h3>
<img width="100%" src="img/pipelines.gif">
<p>
Build fully reproducible, distributed and parallel data processing and training pipelines with real-time logs and output snapshots
</p>
</td>
<td width="50%" align="center">
<h3>Version controlled pipelines and environments as code</h3>
<img width="100%" src="img/tools.gif">
<p>
Bring your own IDEs, annotation tools and pipelines with a version controlled YAML and Docker based template engine
</p>
</td>
</tr>
</table>
- Track and visualize model metrics and experiments with TensorBoard or bring your own experiment tracking tools. - Track and visualize model metrics and experiments with TensorBoard or bring your own experiment tracking tools.
- Access and share tools like AirSim, Carla, Gazebo or OpenAI Gym through your browser with VNC enabled workspaces. - Extend Onepanel with powerful REST APIs and SDKs to further automate your workflows.
- Extend Onepanel with powerful REST APIs and SDKs to further automate your pipelines and environments.
- Workflows, environments and infrastructure are all defined as code and version controlled, making them reproducible and portable. ## Online demo
- Powered by Kubernetes so you can deploy anywhere Kubernetes can run. We have created an [online demo environment](https://onepanel.typeform.com/to/kQfDX5Vf?product=github) so that you can quickly try Onepanel.
Note that this is a shared demo environment with the following restrictions:
- Data is reset every few hours
- One type of node pool (machine type) with a limit of 5 concurrent nodes
- Certain actions may be restricted
## Quick start ## Quick start
See [quick start guide](https://docs.onepanel.ai/docs/getting-started/quickstart) to get started with the platform of your choice. See [quick start guide](https://docs.onepanel.ai/docs/getting-started/quickstart) to get started with the platform of your choice.
@@ -74,17 +51,17 @@ See [documentation](https://docs.onepanel.ai) to get started or for more detaile
To submit a feature request, report a bug or documentation issue, please open a GitHub [pull request](https://github.com/onepanelio/core/pulls) or [issue](https://github.com/onepanelio/core/issues). To submit a feature request, report a bug or documentation issue, please open a GitHub [pull request](https://github.com/onepanelio/core/pulls) or [issue](https://github.com/onepanelio/core/issues).
For help, questions, release announcements and contribution discussions, join us on [Slack](https://join.slack.com/t/onepanel-ce/shared_invite/zt-eyjnwec0-nLaHhjif9Y~gA05KuX6AUg). For help, questions, release announcements and contribution discussions, join us on [GitHub discussions](https://github.com/onepanelio/core/discussions).
## Contributing ## Contributing
Onepanel is modular and consists of the following repositories: Onepanel is modular and consists of the following repositories:
[Core API](https://github.com/onepanelio/core/) (this repository) - Code base for backend (Go)\ [Backend](https://github.com/onepanelio/core/) (this repository) - Code base for backend (Go)\
[Core UI](https://github.com/onepanelio/core-ui/) - Code base for UI (Angular + TypeScript)\ [Frontend](https://github.com/onepanelio/core-ui/) - Code base for frontend (Angular + TypeScript)\
[CLI](https://github.com/onepanelio/cli/) - Code base for Go CLI for installation and management (Go)\ [CLI](https://github.com/onepanelio/cli/) - Code base for installation and management CLI (Go)\
[Manifests](https://github.com/onepanelio/core-ui/) - Kustomize manifests used by CLI for installation and management (YAML)\ [Manifests](https://github.com/onepanelio/core-ui/) - Kustomize manifests used by installation and management CLI (YAML)\
[Python SDK](https://github.com/onepanelio/python-sdk/) - Python SDK code and documentation\ [Python SDK](https://github.com/onepanelio/python-sdk/) - Python SDK code and documentation (Python)\
[Templates](https://github.com/onepanelio/templates) - Various Workspace, Workflow, Task and Sidecar Templates\ [Templates](https://github.com/onepanelio/templates) - Various Workspace, Workflow, Task and Sidecar Templates\
[Documentation](https://github.com/onepanelio/core-docs/) - The repository for documentation site\ [Documentation](https://github.com/onepanelio/core-docs/) - The repository for documentation site\
[API Documentation](https://github.com/onepanelio/core-api-docs/) - API documentation if you choose to use the API directly [API Documentation](https://github.com/onepanelio/core-api-docs/) - API documentation if you choose to use the API directly