Evaluation of model on test set

[aus10powell]

I am aware that there is a method, model.val() to retrieve metrics on the validation dataset. However I haven't be able find a method for a test set, e.g. model.evaluate(config='test.yaml'). This would be useful when evaluation of performance on production datasets, or new datasets that are not in original distribution.

[glenn-jocher]

@aus10powell hello! For evaluating your YOLOv8 model on a test set, you can use the same val mode with a different dataset. You would just need to specify your test set configuration in a YAML file similar to how you define your validation set. Make sure your test set is properly annotated and structured like your training and validation datasets.

When you run the val command, simply point to your test set configuration file instead of the validation set. This will effectively evaluate your model on the test set, providing you with the performance metrics you're looking for. Remember, the key is in the dataset configuration and ensuring your test data is correctly prepared. Happy testing! 😊