How to Replace RTDETR Backbone with a Custom Backbone (e.g., ViT)?

[monggus525]

Hi Ultralytics team,

Thank you for your amazing contributions to the community! I’m working with RTDETR and would like to replace its default backbone with a custom backbone, such as Vision Transformer (ViT), Swin-Transformer.

Could you guide me on the following:

Which files or modules handle the backbone configuration in the RTDETR implementation?
Any recommendations or best practices for integrating custom backbones into RTDETR?
I’d appreciate any pointers or documentation that could help.

Thanks in advance!

[UltralyticsAssistant]

👋 Hello @monggus525, thank you for your interest in Ultralytics 🚀! We recommend checking out the Docs for detailed information about model customization and configuration, which may address parts of your query.

If you're looking to modify the RTDETR backbone, you may need to dive deep into the architecture files for custom integrations. For guidance on backbone configuration and customization, we recommend looking into the model definition files under the respective directories. If you'd like us to assist further, it would be great if you could specify any files or errors you’ve been working with and provide a minimum reproducible example 🐛.

For integrating cutting-edge backbones like Vision Transformer (ViT) or Swin-Transformer, consider experimenting within a Python>=3.8 environment along with PyTorch>=1.8 to ensure all dependencies are compatible. Make sure you're also following our Tips for Best Training Results for optimal performance.

Here are some resources and actions to get started:

Upgrade

Ensure you’re using the latest version of the ultralytics package so you are working with the most recent models and updates:

pip install -U ultralytics

Environments

You can utilize the following environments to experiment with your custom models and backbones easily:

• Notebooks with free GPU:
• Google Cloud Deep Learning VM. See GCP Quickstart Guide
• Amazon Deep Learning AMI. See AWS Quickstart Guide
• Docker Image. See Docker Quickstart Guide

Community

Feel free to join the Ultralytics community to share your work or get advice:

• For real-time chat, head to Discord 🎧.
• Prefer in-depth discussions? Join our Discourse.
• Share your insights or queries on the Subreddit.

Status

If the badge above is green, all Continuous Integration (CI) tests are currently passing, verifying the compatibility and functionality of YOLO models across commonly used environments.

Lastly, note that this is an automated response 🤖, and an Ultralytics engineer will follow up with additional assistance soon! 😊

[glenn-jocher]

Thank you for your kind words! To replace the RTDETR backbone with a custom one like ViT or Swin-Transformer, you can modify the input_proj module in the RTDETRDecoder class, located in ultralytics/nn/modules/head.py. Ensure your custom backbone outputs compatible feature maps, and adjust the channel dimensions accordingly. For further details, refer to the RT-DETR documentation. Let us know if you encounter any challenges!