how to make changes in YOLOv8 backbone with resnet50

[suciptr]

hello.
I am an student with very limited knowledge of Deep Learning and Artificial Neural Networks.
I have an assignment to create a classification model with yolov8, then I want to make some modifications to the model that I have trained, I want to change the yolov8 backbone to resnet50.
Can someone teach and guide me? I will be very grateful.

[pderrenger]

👋 Hello @suciptr, thank you for your interest in Ultralytics 🚀! We recommend checking out the Docs as a starting point for exploring YOLOv8, which includes extensive Python and CLI examples that might help you better understand how to use and customize the model.

If this is a custom training ❓ question, it’s helpful to provide as much context as possible, such as your dataset samples, current approach, and any relevant logs or code snippets. This will assist Ultralytics engineers and the community in providing focused advice. For your specific goal of modifying the YOLOv8 backbone to ResNet50, this may involve deeper customization of the model architecture.

For real-time discussions and peer support, you can join our Discord 🎧. You may also find detailed discussions and shared knowledge on our Discourse platform or Subreddit.

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[glenn-jocher]

@suciptr hi! To help you modify YOLOv8's backbone to ResNet50, I recommend starting with the basic YOLOv8 training example first to get familiar with the framework. Here's a simple approach:

from ultralytics import YOLO

# Load a base YOLOv8 model
model = YOLO('yolov8n.yaml')  

# Train it on your dataset
model.train(data='path/to/data.yaml', epochs=100)

Once you're comfortable with basic training, you can explore modifying the model architecture by editing the YAML configuration file to use ResNet50 as the backbone. Would you like me to provide more specific guidance on working with the YAML config?

Let me know if you need help with any particular step and I'll be happy to assist further.

[suciptr]

yes please.
I have run the program above with my dataset, producing MAP 90s, because the results are good I was asked to change the backbone using resnet50.
I have tried several times to change the program code but still can't, because I have no basic in this matter. so please help me, I would be very helped 💫

[glenn-jocher]

To change the YOLOv8 backbone to ResNet50, you'll need to modify the model's YAML configuration file to define ResNet50 as the backbone. Unfortunately, YOLOv8 does not natively support ResNet50, so you'll need to integrate it manually by customizing the model architecture. This requires defining the ResNet50 backbone in the YAML file and ensuring compatibility with the YOLO head layers.

If you're new to these concepts, I recommend thoroughly reviewing the PyTorch ResNet50 implementation and Ultralytics' model configuration files for guidance. You can also explore the Ultralytics Docs or raise detailed questions in the community forums for additional support.

[suciptr]

is there any file have to change beside model.yaml?

[glenn-jocher]

To modify YOLOv8's backbone to ResNet50, you need to edit the model.yaml file to define the ResNet50 architecture. Additionally, you may need to adjust the ultralytics/nn/tasks.py file to ensure the ResNet50 model is correctly parsed and integrated. Let me know if you need further clarification.