Comments (5)
@chang50961471 yes, YOLOv5 does support incremental learning. You can find more information about how to use it in the Ultralytics Docs at https://docs.ultralytics.com/yolov5/. Let me know if you have any other questions!
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@chang50961471 yes, YOLOv5 does support incremental learning. You can find more information about how to use it in the Ultralytics Docs at https://docs.ultralytics.com/yolov5/. Let me know if you have any other questions!
Which module in the document introduces incremental data learning
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@chang50961471 yes, YOLOv5 does support incremental learning. You can find more information about how to use it in the Ultralytics Docs at https://docs.ultralytics.com/yolov5/. Let me know if you have any other questions!
According to the introduction of other problems, I only use the new data to train and use the already trained model, and there will be a lot of missing reports in the final trained model. How can this be handled well
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@chang50961471 Thanks for reaching out! It sounds like you are encountering issues with incremental learning. YOLOv5 supports incremental learning through the --multi-scale
and --resume
flags for fine-tuning on new data. You can refer to the Ultralytics Docs for a detailed guide on how to utilize these features effectively. Additionally, ensuring the compatibility of the new data with the existing model's classes and characteristics is essential for successful training. Let me know if you have further questions!
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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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