How to insert a custom backbone in YOLOv8 ?

[arnobjohn]

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Greetings.

I am trying to implement a backbone network which is a combination of ResNet and FPN. I am trying to use it to train a custom dataset but not sure how to do so. The modified backbone is in python file as "resnet_fpn.py".

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[glenn-jocher]

Hello! To integrate your custom backbone into YOLOv8, you'll need to modify the model configuration file (YAML file) to point to your new backbone. Here’s a brief guide on how to do it:

1. Model Configuration: In your model's YAML file, replace the existing backbone specification with the path to your custom backbone script. For example:

   backbone: path/to/resnet_fpn.py

2. Import Custom Backbone: Ensure that your resnet_fpn.py is properly set up to be imported. It should define the backbone in a way that YOLOv8 can utilize.

3. Train Your Model: With the backbone set, you can proceed to train your model:

   yolo train data=your_dataset.yaml model=your_model.yaml

Make sure your custom backbone matches the input and output specifications expected by YOLOv8. Good luck with your model training! 🚀

[arnobjohn]

Thanks for your reply @glenn-jocher. Actually I am trying to use resnet_fpn in the YOLOv8 model. A guide on how to do so will be very much helpful.

[glenn-jocher]

Hello! To integrate the resnet_fpn backbone from the provided repository into YOLOv8, you'll need to modify your model's YAML configuration file. Here's a quick example of how you might set it up:

# Example YAML configuration
backbone: path/to/resnet_fpn.py  # Ensure this path is correct

Make sure that resnet_fpn.py is structured to be compatible with YOLOv8, particularly in how it handles inputs and outputs. After setting up the YAML file, you can train your model using:

yolo train data=your_dataset.yaml model=your_custom_model.yaml

This should get your custom backbone up and running with YOLOv8! 🚀

[arnobjohn]

Thanks for your reply @glenn-jocher. I have a following question to ask.

I am trying to implement PVTv2 in place of c2f in backbone. Will it be possible? If so can you kindly mention the steps.

TIA

[glenn-jocher]

Hello!

Yes, integrating PVTv2 as a backbone in YOLOv8 is possible. Here's a brief outline of the steps you'd follow:

1. Clone PVTv2 Repository: Ensure you have the PVTv2 modules available locally or in your project environment.

2. Modify YOLOv8 YAML Configuration: Update the backbone section in your YOLOv8 model's YAML configuration file to point to your PVTv2 implementation. You might need to adjust the module to ensure compatibility with YOLOv8's expected input and output formats.

3. Adjustments for Compatibility: Ensure that the PVTv2 model's output features match what is expected by the YOLOv8 head in terms of feature map sizes and channel dimensions.

4. Train the Model: With the backbone integrated and configurations set, proceed to train your model using the modified settings.

Make sure to test the integration thoroughly to catch any issues with dimensions or performance early in your development cycle.

Best of luck with your model enhancement! 🚀