ascii-video

Decode the source video with ffmpeg, sample per-frame luminance and edges, then map brightness values to characters from a density-sorted palette on a fixed grid. Composite pre-rasterized font bitmaps onto a pixel canvas and pipe 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 onsets 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 in.

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 automatically adjusts resolution and worker count for low-memory systems.

ASCII characters are small bright dots on black backgrounds, so linear brightness multipliers clip highlights while leaving frames dark. Use percentile-based adaptive tonemapping with gamma around 0.75 instead, and prefer screen blending over overlay for dark layers.

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 pipe only raw RGB frames through stdin for the encode.

Yes, but not all monospace fonts render every Unicode glyph. Palettes should be validated at initialization by rendering each character and checking for blank output, silently dropping unsupported glyphs so the font never produces empty cells.