VideoCutterAI is a Python-based open-source application designed to automate video slicing tasks with AI. It analyzes visual and audio cues—such as scene changes, speaker transitions, silence gaps, and subtitle timestamps—using computer vision and signal processing techniques. Users can configure parameters like clip duration, overlap margins, and sensitivity thresholds to fine-tune output segments. The tool integrates with FFmpeg for fast, lossless cutting and supports batch processing of entire video folders. Advanced options include face-detection-based segmentation and keyword-triggered cuts when paired with ASR transcripts. As a flexible CLI or library, it plugs into custom pipelines for creating social media snippets, lecture highlights, or automated broadcast clips, saving significant editing time.

AI MV Generator applies advanced beat detection algorithms to analyze input audio files and coordinates them with diffusion-based video frame generation. Users provide audio tracks and optional style prompts or seed visuals; the system processes waveform data, extracts rhythm patterns, and generates a sequence of image frames reflective of each audio segment’s mood. Frames are then interpolated to create smooth motion, producing a cohesive music video. Users can tweak parameters such as style prompts, frame rate, resolution, and duration to achieve desired aesthetics. The pipeline integrates seamlessly with GPU-accelerated inference for fast rendering and outputs standard video formats compatible with popular editing tools, streamlining AI-driven video production.