Open source part of a code to avoid the empresarial license

[felipequentino]

Hi! I have a startup that has a product that detects objects. The product has 2 parts: one part I detect and do tracking of objects using Pytorch, that has MIT License, and is the "unique, important" part of my product, the other part is a simple ALPR using YOLOv8 to complement my product. Both parts sends information to a Dashboard, but they are INDEPENDENT, so the ALPR isn't connected in any way with the Pytorch part. The only thing that the two parts do in common is to send informations to the dashboard, here is a Venn diagram:

When I launch the product, I want to deploy the ALPR part in a jetson nano and make the ALPR code open source, avoiding paying for the empresarial license. This is OK to do? Making open source ONLY the ALPR part? 

[UltralyticsAssistant]

👋 Hello @felipequentino, thank you for reaching out and sharing details about your use case 🚀! Your application sounds fascinating, and we appreciate you considering Ultralytics solutions as part of your product.

For guidance regarding licensing and the use of YOLOv8 within your project, we recommend reviewing our LICENSE and consulting the YOLOv8 Quickstart Guide. These resources can be instrumental in clarifying your questions, although it's always wise to consult a legal professional for specific scenarios like this.

To better assist you, here are some general guidelines depending on the nature of your inquiry:

• If this is a 🐛 Bug Report, please ensure you provide a minimum reproducible example so we can understand and troubleshoot the issue effectively.
• If this is a ❓ Custom Usage Question, please share additional context, including code snippets, system setup, or examples, so we can provide more tailored insights.

In case you'd like to explore alternative configurations or deployment setups for your ALPR system, this might interest you:

Verified Environments

YOLOv8 can be run in any of the following environments, verified for efficiency and compatibility:

• Notebooks:
• NVIDIA Jetson devices, like the Nano you mentioned: We recommend verifying hardware compatibility with the latest ultralytics releases and referring to any specific acceleration configurations for Jetson setups.
• Docker solutions: See our Docker Quickstart Guide.

For more assistance or real-time discussions, consider joining our Ultralytics community:

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• Discourse for in-depth discussions
• Reddit for sharing and learning with the community

Additionally, ensure you're using the latest version of ultralytics to take advantage of all enhancements and bug fixes. You can upgrade with the command below:

pip install -U ultralytics

This is an automated response to help guide your discussion. An Ultralytics engineer will review and provide further assistance soon. Let us know if there’s anything else you’d like to share in the meantime! 😊

[glenn-jocher]

@felipequentino thank you for your question. To comply with the AGPL-3.0 license, you are required to open source your entire project that uses any Ultralytics models, code, or architecture, not just a part of it. This includes the ALPR component, the PyTorch part, and any shared or independent components that interact with it, directly or indirectly, such as the dashboard. If you prefer not to open source everything, you must obtain an Ultralytics Enterprise License. You can learn more or apply here: https://ultralytics.com/license.

[felipequentino]

Ok Glenn, thanks for your answer.

[glenn-jocher]

@felipequentino you're welcome! Please feel free to reach out if you have further questions about Ultralytics or YOLO.