unexpected freezed layer about ultralytics

[glenn-jocher]

@MuhabHariri hi there,

Thank you for reaching out and providing details about the issue you're encountering with freezing layers in your custom YOLOv8 model. To assist you better, could you please provide a minimal reproducible code example? This will help us understand the context and reproduce the issue on our end. You can refer to our guide on creating a minimum reproducible example for more details.

Additionally, please ensure that you are using the latest versions of torch and ultralytics. You can upgrade your packages using the following commands:

pip install --upgrade torch ultralytics

Regarding your question, your interpretation is correct. In the YOLOv8 model, model.0 refers to the first layer, and model.19 would indeed correspond to the Detect layer if your YAML file is structured that way. The unexpected freezing of the model.19.dfl.conv.weight layer could be due to a misconfiguration or an unintended side effect in the model's layer freezing logic.

Once you provide the reproducible example and confirm the versions, we can dive deeper into the issue and identify why the Detect layer's weight is being frozen.

Looking forward to your response!

[glenn-jocher]

@MuhabHariri DFL layers should always be frozen, this is all good.

[MuhabHariri]

@glenn-jocher Thank you for your response. Could you clarify further why DFL layers should always be frozen?

[glenn-jocher]

Hi @MuhabHariri,

Thank you for your follow-up question!

The DFL (Distribution Focal Loss) layers are designed to be frozen because they are part of the final detection head, which is responsible for refining the bounding box predictions. Freezing these layers helps maintain the stability of the model's output during training, ensuring that the learned distribution of bounding box coordinates remains consistent. This is particularly important for maintaining the accuracy and reliability of the model's predictions.

If you have any more questions or need further clarification, feel free to ask! 😊