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License and a few questions #12871

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Developer-Moon opened this issue Apr 2, 2024 · 5 comments
Closed
1 task done

License and a few questions #12871

Developer-Moon opened this issue Apr 2, 2024 · 5 comments
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question Further information is requested Stale

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@Developer-Moon
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Question

I intend to use the code on this website (https://github.com/LongxingTan/tfyolo - YOLOv5 tensorflow) commercially.

  1. What licensing policy should I follow to use this? (Because you are the original author of YOLOv5)
    ex) AGPL-3.0 License? Enterprise License? or LongxingTan (https://github.com/LongxingTan/tfyolo)?

  2. If the first question concerns you.

    • 2.1 Do I have to disclose the code when using it commercially?
    • 2.2 I am trying to do TCP communication with YOLO v5. If I have to disclose my code, do I also have to disclose my TCP code?
    • 2.3 Is it okay if I obfuscate your code and make it public?

Additional

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@Developer-Moon Developer-Moon added the question Further information is requested label Apr 2, 2024
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github-actions bot commented Apr 2, 2024

👋 Hello @Developer-Moon, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.

If this is a 🐛 Bug Report, please provide a minimum reproducible example to help us debug it.

If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our Tips for Best Training Results.

Requirements

Python>=3.8.0 with all requirements.txt installed including PyTorch>=1.8. To get started:

git clone https://github.com/ultralytics/yolov5  # clone
cd yolov5
pip install -r requirements.txt  # install

Environments

YOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):

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If this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training, validation, inference, export and benchmarks on macOS, Windows, and Ubuntu every 24 hours and on every commit.

Introducing YOLOv8 🚀

We're excited to announce the launch of our latest state-of-the-art (SOTA) object detection model for 2023 - YOLOv8 🚀!

Designed to be fast, accurate, and easy to use, YOLOv8 is an ideal choice for a wide range of object detection, image segmentation and image classification tasks. With YOLOv8, you'll be able to quickly and accurately detect objects in real-time, streamline your workflows, and achieve new levels of accuracy in your projects.

Check out our YOLOv8 Docs for details and get started with:

pip install ultralytics

@glenn-jocher
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@Developer-Moon hello! Thanks for reaching out and for your interest in YOLOv5. I'll directly address your inquiries:

  1. For commercial use of YOLOv5, regardless of the implementation (including the TensorFlow version at the mentioned repository), you need to adhere to the AGPL-3.0 license stipulations associated with our work, unless you obtain an Ultralytics Enterprise License. The licensing of any derivative work, like the one you mentioned, does not exempt you from this requirement.

    2.1 If you're using Ultralytics models, architectures, or code under the AGPL-3.0 license for commercial purposes, you are indeed required to fully open source your entire project under the same AGPL-3.0 license. There are no exceptions to this rule.

    2.2 In line with the AGPL-3.0 requirements, if your project incorporates our code and you choose to open source it under AGPL-3.0, you must disclose all related code, including any TCP communication code that directly interacts with or is part of the project using YOLOv5.

    2.3 Obfuscating the code does not exempt you from the obligations under AGPL-3.0. If you choose to distribute or use the project commercially under AGPL-3.0, the code must be made available in a form that is accessible and modifiable by others.

If your use case requires keeping your project closed-source, I strongly encourage you to consider obtaining an Ultralytics Enterprise License. This would allow commercial use without the need to open source your project.

For more detailed information on licensing and potential next steps, please refer to our documentation at https://docs.ultralytics.com/yolov5/.

We're here to support you, so if you have any more questions or need further clarification, don't hesitate to ask. Best wishes on your project! 🚀

@Developer-Moon
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Thank you very much for your kind reply

I want to know one thing clearly

I understand that communication with the AGPL program through Pipe, Socket, IPC, and Command Line Arguments as a separate program from the AGPL program is not considered a derivative work of the GPL

our current state

Project 1 : Yolo v5 + Client
Project 2 : Server

The two projects are independent and have socket communication with each other

In the case above, should I also disclose the second project, Server Code?

@glenn-jocher
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Hey @Developer-Moon, glad you found the previous response helpful! 😊

Concerning your setup with Project 1 and Project 2 communicating over sockets:

  • If Project 1 utilizes YOLOv5 and is under AGPL-3.0, and Project 2 (Server) operates independently without including or directly interacting with the YOLOv5 codebase, then Project 2 wouldn't inherently be considered a derivative work requiring disclosure under AGPL-3.0.

However, it's crucial to ensure that the separation between the two projects is clear and that Project 2 does not use or incorporate AGPL-3.0 licensed code indirectly. If in doubt or your use case is complex, consulting with a legal expert on open-source licensing is always a good step.

Hope this clarifies your query! If you have any more questions, feel free to ask. Best of luck with your projects! 🚀

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github-actions bot commented May 4, 2024

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

@github-actions github-actions bot added the Stale label May 4, 2024
@github-actions github-actions bot closed this as not planned Won't fix, can't repro, duplicate, stale May 14, 2024
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