ascii-video

Decode the source video with ffmpeg, sample per-frame luminance and edges, map brightness values to characters from a density palette, and render colored character grids onto a pixel canvas with Pillow font bitmaps. 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 encode frames to MP4 with the audio muxed.

No GPU is required. The pipeline runs on CPU using NumPy-vectorized effects and Pillow font rasterization, with concurrent.futures splitting frames across worker processes. A 1080p 24fps frame renders in roughly 100-200ms per worker.

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

ffmpeg deadlocks when stderr is piped on long encodes because the buffer fills at about 64KB. Redirect stderr to a log file instead of subprocess.PIPE, and write raw RGB frames to stdin while keeping stdout as DEVNULL.

Not all Unicode glyphs render in every monospace font, 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.