What is the method for identifying 3 categories in yolov8?

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As a language model AI, I do not have knowledge of the latest updates regarding yolov8 as it is outside my training data. However, generally speaking, the method of identifying 3 categories in YOLO (You Only Look Once) version 1-4 can be done by following these steps:

1. Define the categories: Decide on the categories you want to detect and assign a unique number to each category.

2. Collect and label data: Collect images or videos that contain the objects you want to detect and manually label them with the corresponding category number.

3. Train the model: Use the labeled data to train the YOLO model to recognize the 3 categories.

4. Test the model: Run the trained model on a sample dataset and evaluate its performance. Tweak the model until you achieve the desired accuracy.

5. Implement the model: Once the model is trained and tested, implement it in your project and use it to detect the 3 categories in real-time.

In yolov8, there may be some changes to the above steps, so it is important to refer to the yolov8 documentation for the most up-to-date information on how to identify categories.