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In this tutorial hosted by Brad from Roboflow, the focus is on how to process video data for training a computer vision model. Building on previous lessons, the tutorial demonstrates taking a video, slicing it into individual frames, and annotating those frames for model training. The example used is a video shot at an aquarium, showcasing fish and sharks swimming, illustrating the concept that consecutive frames share high similarity. The goal is to guide viewers through the process of preparing video data, shifting from utilizing model outputs to leveraging videos as essential input for training.