ascii-video

Load the source video frames with ffmpeg or OpenCV, sample per-cell luminance and color, map values to a character palette on a fixed grid, composite pre-rasterized font bitmaps onto a pixel canvas with NumPy, then pipe raw RGB frames to ffmpeg for H.264 encoding.

Analyze the audio with SciPy FFT to extract 6 frequency bands, RMS energy, spectral centroid, and beat detection with exponential decay. Drive value field generators, particle systems, and beat-reactive shaders from those per-frame features, then encode with the audio muxed back in.

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 blend mode over overlay when compositing dark layers.

No GPU is required. Rendering runs on CPU with NumPy-vectorized effects and a per-cell font compositing loop at roughly 100-200ms per frame, parallelized across worker processes that each pipe frames to their own ffmpeg encoder.

Using stderr=subprocess.PIPE on a long-running ffmpeg process deadlocks once the stderr buffer fills at about 64KB. Redirect stderr to a log file instead and keep stdin as the raw video pipe.

Not all Unicode glyphs render in every monospace font, and some characters collapse to blobs at small font sizes. Validate palettes at initialization by test-rendering each glyph and silently dropping characters that produce blank bitmaps.