video-analyzer

To extract a color palette and design system from a video, you need to analyze scene-based frames using FFmpeg workflows and AI vision. This process detects colors, typography cues, and layout patterns, returning a structured JSON payload with design tokens.

Yes, you can use FFprobe to identify scene changes and extract representative frames for UI design analysis. By probing video metadata and capturing frames at scene cuts, AI vision can then derive component inventories and spacing units.

You can extract video metadata like duration, resolution, and codecs to build a structured JSON design system. The resulting payload summarizes colors, typography, spacing, layout, components, and assets detected from the analyzed video frames.

AI vision detects typography and layout patterns from video content by analyzing frames extracted at scene changes. It evaluates visual cues to identify typography scales, component structures, and accessibility signals, compiling them into a machine-readable JSON format.

The best way to automate video analysis for UI component extraction is combining FFprobe scene detection with AI vision workflows. This identifies scene-based frame sequences and derives a structured JSON payload containing component inventories and design-system data.

Yes, FFmpeg and FFprobe are required to extract design tokens like spacing and components from videos. These tools handle the underlying video probing and frame extraction workflows needed to generate the structured JSON design-system summary.