GitHub - axmstandart1-beep/axioma: Compression redefined through human perception. · GitHub
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axioma
Compression redefined through human perception.
axioma abandons brute-force discrete mathematics and adopts a perceptual-first architecture — achieving 90–96% compression ratios on video and rich media with zero ugly macroblocks and zero CPU meltdown.
The Perceptual Revolution
Traditional compression engines rely on heavy, block-based discrete mathematics. They work, but they are heavy, generate heat, and have no understanding of what the human eye actually perceives.
axioma is a complete departure.
We built the core around a theory of human perception . Instead of minimizing an abstract mathematical error, axioma preserves what matters to human senses — edge continuity, texture flow, motion clarity — while intelligently discarding invisible noise.
The result:
Radically lighter compute – no complex block transforms or heavy entropy loops.
Extreme ratios – consistent 90–96% reduction on heavy video streams.
Zero macroblock artifacts – uses film grain synthesis and perceptual quantization to reconstruct natural textures.
Cool, silent operation – keeps CPU usage minimal even on mobile ARM hardware.
How It Works
Adaptive Router
Every incoming stream is instantly classified by a zero-latency router:
Semantic Text Mode: Extracts templates and tokenizes repetitive structures for logs, JSON, and databases.
Perceptual Media Mode: Applies psychovisual quantization, adaptive masking, and grain synthesis for video and raw media.
Quick Start
git clone [https://github.com/axmstandart1-beep/axioma.git](https://github.com/axmstandart1-beep/axioma.git)<br>cd axioma<br># Run perceptual compression<br>python3 av1_axioma.py
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