Before using the smart labeler tool for object detection, what must you do?

To effectively utilize the smart labeler tool for object detection, it is essential to first train an initial object detection model. This step is crucial because the smart labeler operates by enhancing a pre-existing model that has already learned basic object detection capabilities. The model must understand the foundational patterns and characteristics of the objects you want to identify.

By training the initial model with a dataset that is representative of your specific use case, you enable the smart labeler to provide meaningful suggestions and improvements based on the model's learned features. This preparatory work ensures that the subsequent labeling and refinement process can be conducted efficiently and accurately.

Since the other options involve steps that either precede or are alternatives to the foundational training needed for the smart labeler, they are not prerequisites for using the tool effectively.