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I could not really find a satisfying answer here yet, this question touches it but kind of reversed.

  1. For example the training framework for Yolo v7 is used to train a neural network using the config (cfg) file from the repo which is licensed under GPL-3 using custom data.

  2. Now the model gets exported to onnx (or tflite or any other major inference runtime) and used with inference scripts that are completely self-written (inference done by onnxruntime, especially post-processing like decoding and nms self-written).

Is (2) now derivative work and must be distributed under GPL-3 too by using the neural network weights?

Rohit Gupta
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sofa28
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    The non-answer to this question is that there is no clear answer to this yet. It's going to be an evolving area of copyright law over the next few years. – Philip Kendall Aug 17 '22 at 19:55
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    It is not really answerable legally. I suspect it is probably going to be regarded as output data of a GPL program, just like mentioned in the question https://opensource.stackexchange.com/questions/5478/is-the-output-of-an-open-source-program-licensed-the-same The other possibility, as mentioned in the first question you linked to, is that the model data are not even copyrightable, as they were not created by a human. – Brandin Aug 18 '22 at 08:03
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    Thanks to both of you, that is what I thought after not finding a lot of resources on this matter. Interestingly, some Kaggle competitions do not allow YOLO models because of the GPL 3 License. Also the creator of Yolo v3 and v5 does not really have an answer. Maybe, I compile some results of my search on this later when I have time. Many thanks so far! – sofa28 Aug 18 '22 at 12:30

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