QuadFrame Vision Video Intelligence

QuadFrame Vision is an AI-powered video captioning and understanding platform built for the AMD Hackathon. The system automatically processes video URLs, intelligently selects the most informative frames, and generates accurate natural-language captions using Google's Gemma 4 Vision Language Model accelerated with AMD ROCm. Unlike traditional approaches that analyze every frame, QuadFrame Vision performs adaptive scene detection and key-frame selection to reduce computation while preserving important visual information. This significantly improves efficiency without sacrificing caption quality. The platform supports multiple caption styles including formal, sarcastic, humorous technical, and humorous non-technical, making it suitable for accessibility, media automation, social media content generation, education, and intelligent video indexing. The entire solution is packaged as a Docker container for one-command deployment and is designed to run efficiently on AMD Instinct GPUs with automatic CPU fallback when GPU resources are unavailable. The application accepts a JSON task file containing multiple video URLs and produces structured JSON outputs, making it easy to integrate into existing AI pipelines and enterprise workflows. Key features include intelligent frame extraction, automated video downloading, robust error handling with retry mechanisms, scalable batch processing, configurable inference settings, and production-ready architecture. The modular design separates video ingestion, frame analysis, AI inference, and output generation, allowing future extensions such as multilingual captioning, video summarization, visual question answering, and content moderation. QuadFrame Vision demonstrates how AMD ROCm and modern vision-language models can be combined to build scalable, efficient, and deployable multimodal AI applications that transform raw video content into meaningful structured information for real-world use cases.