Multimodal Video Analysis with CLIP using Intel Gaudi2 HPUs

James Gallagher's guide explores using the multimodal model CLIP, developed by OpenAI, for classifying frames in a video, which is particularly useful for media indexing. By leveraging the high-performance capabilities of the Gaudi2 system, developed by Habana, an Intel company, the guide illustrates how to assign descriptive labels to video frames, such as "office" or "park," and analyze the content across various timestamps. The tutorial provides a step-by-step approach to installing necessary dependencies and calculating CLIP vectors for each frame, allowing users to identify the most relevant labels and group them by intervals for comprehensive video analysis. This process can be scaled to process thousands of videos, offering practical applications such as building search engines for specific scenes or classifying video content to comply with broadcasting regulations. The guide also highlights the potential to index large video repositories or create systems that classify videos in real-time as they are submitted, showcasing the versatility and efficiency of combining CLIP with Gaudi2 for video classification.