ascii-video

Decode the source video with ffmpeg, sample per-frame luminance and edges, map brightness values to characters from a density-sorted palette, and composite pre-rasterized font bitmaps onto a pixel canvas. Pipe the raw RGB frames back to ffmpeg for H.264 encoding.

Analyze the audio with SciPy FFT to extract frequency bands, RMS energy, spectral centroid, and beat detection per frame. Drive value field generators, particle systems, and shader intensity from those features, then render character grids and encode with the original audio muxed.

No GPU is required. The pipeline runs on CPU with vectorized NumPy operations and parallel workers via concurrent.futures, rendering 1080p at roughly 100-200ms per frame. Hardware detection adapts resolution and worker count automatically.

ASCII characters are small bright dots on black backgrounds, so most frame pixels are dark and linear brightness multipliers clip highlights. Use percentile-based adaptive tonemapping with gamma correction (default 0.75) to lift shadows without washing out bright areas.

Setting stderr=subprocess.PIPE on a long-running ffmpeg process deadlocks once the buffer fills at about 64KB. Redirect stderr to a log file instead and keep only stdin piped for raw frame data.

Yes, but not all monospace fonts render every Unicode glyph. Validate palettes at initialization by rendering each character and checking for blank output, silently dropping glyphs the selected font cannot draw.