Advanced Customization - Ultralytics YOLOv8 Docs

[giscus[bot]]

Advanced Customization - Ultralytics YOLOv8 Docs

Learn how to train and customize your models fast with the Ultralytics YOLO 'DetectionTrainer' and 'CustomTrainer'. Read more here!

https://docs.ultralytics.com/usage/engine/

[junaidul-islam]

Hi, can someone explain more detail regarding custom loss function?

[glenn-jocher]

@junaidul-islam hello! Customizing the loss function in YOLOv8 involves creating a new loss module that computes the loss according to your specific requirements. You would typically subclass the existing loss class and override the necessary methods to implement your custom logic.

To integrate your custom loss, you'll need to ensure that it returns a scalar tensor representing the loss value, and that it's properly connected to the rest of the training pipeline. This means it should be compatible with the backpropagation process used to update the model weights.

Remember to thoroughly test your custom loss function to ensure it behaves as expected and contributes positively to the training process. For more detailed guidance, please refer to the 'Advanced Customization' section in our documentation. 📚