ascii-video

Decode the source video with ffmpeg, sample per-frame luminance and edges, map brightness values to a sorted character palette on a fixed grid, then 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 detection per frame. Drive value field generators, particle systems, and beat-reactive shaders from those features, then render and encode with ffmpeg.

No GPU is required. The pipeline runs on CPU using NumPy vectorized operations and Pillow font rasterization, with concurrent.futures workers for parallel encoding. Hardware detection adapts resolution and worker count automatically.

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 correction around 0.75, 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 roughly 64KB. Redirect stderr to a log file instead and keep stdin as the raw frame pipe.

The per-cell Python compositing loop runs at roughly 100-150ms per frame, so a 5-minute 1080p video takes about 17-33 minutes on typical hardware. Unicode palette characters may also render as blank glyphs in some fonts and must be validated at initialization.