Row 69986

Row ID: 69986 | Dataset Entry | Axioma AXP Content Repository

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Hi data scientists/computer vision people, I’m working on building a commercial app that involves an object detection model. I’m considering using YOLOv7 with my own training data, but I’m concerned about the licensing. YOLOv7 is licensed under GNU GPL 3.0, which would require me to make the source code of my whole app open source if YOLOv7 is integrated into it.

I’m curious about how others handle this situation. Specifically:

1. Do developers often resort to using different, older models that have more permissive licenses for commercial applications? 2. Are there any alternative approaches, such as training a model from scratch using the YOLOv7 repo (so that it is not a derivative of the repo), and build my own inference pipeline that does not use the YOLOv7 codebase for inference? For example using ONNX.

I would really appreciate any insights or experiences.

Thanks!

FieldValue
text Hi data scientists/computer vision people, I’m working on building a commercial app that involves an object detection model. I’m considering using YOLOv7 with my own training data, but I’m concerned about the licensing. YOLOv7 is licensed under GNU GPL 3.0, which would require me to make the source code of my whole app open source if YOLOv7 is integrated into it. I’m curious about how others handle this situation. Specifically: 1. Do developers often resort to using different, older model…
label r/datascience
dataType post
communityName r/datascience
datetime 2024-05-23
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Raw Record

{
  "text": "Hi data scientists/computer vision people,  \n  \nI’m working on building a commercial app that involves an object detection model. I’m considering using YOLOv7 with my own training data, but I’m concerned about the licensing. YOLOv7 is licensed under GNU GPL 3.0, which would require me to make the source code of my whole app open source if YOLOv7 is integrated into it.\n\nI’m curious about how others handle this situation. Specifically:\n\n1. Do developers often resort to using different, older models that have more permissive licenses for commercial applications?\n2. Are there any alternative approaches, such as training a model from scratch using the YOLOv7 repo (so that it is not a derivative of the repo), and build my own inference pipeline that does not use the YOLOv7 codebase for inference? For example using ONNX.\n\nI would really appreciate any insights or experiences.\n\nThanks!",
  "label": "r/datascience",
  "dataType": "post",
  "communityName": "r/datascience",
  "datetime": "2024-05-23",
  "username_encoded": "Z0FBQUFBQm5Lak1lQ3JBSGllX0M3RkJ2UFFONUhEcUduTVp6NGtrUUJQMmNOaUV0eDdOX2l2aVY5Z1JobjFhejRmSU1QTU1MX1o0QUFyc0s3aExpMXIxdkE0MWJlN3o5eUE9PQ==",
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}
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