RT-DETR model hyperparameters about ultralytics

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[glenn-jocher]

Hello,

Thank you for reaching out and detailing your experience with the RT-DETR model. It's great to hear that you're exploring custom training!

For the official hyperparameters, you can find the default configuration in the default.yaml file directly within our repository. This file will provide you with a baseline for the hyperparameters used in our pre-trained models.

Regarding modifications and customizations, while we don't have a specific tutorial for modifying the RT-DETR model, I recommend looking at the Model Customization section of our documentation. This section provides guidance on how to tailor models to better fit specific needs, which might help you understand and replicate the successful modifications you mentioned.

If you have further questions or need more detailed assistance, feel free to ask!

[slwgsc]

Thanks for the reply!
Regarding the hyperparameters, what I want to express is whether ultralytics can offer the concrete value of parameters in order to obtain approximate training results for the original paper code(https://github.com/lyuwenyu/RT-DETR)
In addition, I sincerely hope that ultralytics can provide the resnet18 and rest34 yaml file in RT-DETR as soon as possible, which will facilitate our research and improvement.

[glenn-jocher]

Hello,

Thank you for your follow-up and for clarifying your needs!

For hyperparameters that closely match those used in the original RT-DETR paper, I recommend reviewing the configuration files and training scripts provided in the official RT-DETR repository. Typically, these files contain specific hyperparameter settings optimized for their models.

As for the request for ResNet18 and ResNet34 YAML files for RT-DETR, we appreciate your suggestion and understand how valuable these configurations could be for the community. I'll forward your request to our development team for consideration in future updates.

Your interest and suggestions are incredibly valuable to us, and they play a crucial role in shaping our roadmap. Thank you for contributing to the improvement of our resources!