ascii-video

Sample frames from the source video, map per-cell luminance to characters from a density-sorted palette, and color cells from the original pixels. Render each frame onto a pixel canvas with pre-rasterized font bitmaps and pipe raw RGB frames to ffmpeg for H.264 encoding.

Analyze the audio with 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 so visuals pulse and shift with the music.

No GPU is required. The pipeline runs on CPU with NumPy-vectorized effect math and Pillow font rasterization, parallelized across worker processes. A 1080p 24fps frame renders in roughly 100-200ms, with quality profiles adapting to detected hardware.

ASCII characters are small bright marks on black backgrounds, so linear brightness multipliers clip highlights while leaving frames dark. Use percentile-based adaptive tonemapping with gamma correction (default gamma 0.75) to lift shadows without blowing out bright cells.

Piping ffmpeg stderr to subprocess.PIPE deadlocks once the 64KB buffer fills during long encodes. Redirect stderr to a log file instead, and keep stdin as the raw RGB frame pipe.

Not all fonts render every Unicode glyph, and some characters collapse to blobs at small font sizes. Validate palettes at initialization by rendering each character and silently dropping blank glyphs before use.