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 pixel values. Frames are composited with pre-rasterized font bitmaps and piped to ffmpeg for H.264 encoding.

Analyze the audio with 6-band FFT, RMS energy, spectral centroid, and beat detection with exponential decay. Drive value field generators, particle systems, and beat-reactive shaders like glitch bands and chromatic aberration from those per-frame features.

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, lowering to 0.50-0.60 for solarize or posterize scenes.

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 stdin as the raw RGB frame pipe.

Yes, the entire pipeline runs on CPU using NumPy-vectorized effect math and Pillow font rasterization. Rendering runs about 100-200ms per frame at 1080p, parallelized across worker processes, with quality profiles that adapt to detected hardware.

Any monospace font works, with auto-detection for Menlo, Consolas, DejaVu Sans Mono, and others. Unicode palettes like braille, katakana, and runes must be validated at init since unsupported glyphs render blank and are silently dropped.