Using videos as training data

Analyzing video data for computer vision models involves treating videos as sequences of individual images, which can be processed using tools like Roboflow Pro to extract frames at a chosen rate, balancing the volume of data with ease of annotation. After extracting frames, Roboflow Annotate allows for efficient labeling, utilizing features such as the Repeat Previous tool to track objects across frames by modifying prior annotations. Once annotations are complete, models can be trained and used for further labeling or prediction tasks, streamlining the process of working with video data in computer vision projects.