Which option is suitable for categorizing event footage without training your own ML model?

The best choice for categorizing event footage without the need to train your own machine learning model is the option that leverages pre-built APIs. These APIs come with predefined models that have already been trained on extensive datasets, allowing users to perform various tasks, such as image and video analysis, without requiring technical expertise in machine learning or the resources necessary to build and train a custom model.

Using pre-built APIs can significantly streamline the process of categorizing event footage because they are designed to handle common tasks, such as object detection, scene recognition, and action classification. This means that users can quickly access capabilities that cover a wide range of applications and categories without investing time and effort into model development.

Other options, such as custom machine learning or self-served model training, would involve developing and training models from scratch, which contradicts the requirement of not wanting to train an ML model. The data labeling service, while valuable for preparing datasets for training, does not directly address the need for categorization without model training. Therefore, the most efficient solution for categorizing footage in this scenario is indeed the use of pre-built APIs.