Comments (2)
@melader111 hello!
In such cases where discrepancies occur in parameter counts between Ultralytics models and officially reported values, it typically involves how certain operations or layers are accounted, or potential enhancements made in our implementations.
For consistency in comparisons, especially in academic or controlled studies, I would recommend sticking with one source for all model implementations. If you're aiming for a comparison with official metrics and publications, using official model code and numbers might be easier to align with reported results.
However, if you're evaluating based on performance or integration capabilities, Ultralytics models are optimized for implementation and might provide practical advantages.
Hope this helps! 😊
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👋 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:
- Docs: https://docs.ultralytics.com
- HUB: https://hub.ultralytics.com
- Community: https://community.ultralytics.com
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 ⭐
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