cos-comparison 0.1.1

Local similarity comparison for feature extraction – biologically inspired, zero‑training edge / pattern detection.

Cos Comparison

Local similarity comparison for feature extraction – biologically inspired, zero‑training edge / pattern detection.

Core Idea

Information is produced by local comparison in raw data.
This module implements the center‑surround antagonism mechanism from neuroscience, extracting edges, textures, and keypoints using only sliding window similarity.

The main formula (cosine‑modulated similarity):

$$ \text{cosmod} = \frac{2,(A\cdot B)}{|A|^2 + |B|^2} $$

• Spurt for real AGI
• No training, no labels, no backpropagation
• Works on 1D, 2D, 3D, 4D data (audio, images, video, volumes)
• Supports passive (reflex) and active (template matching) modes
• Pure Python core + optional NumPy / C acceleration

Installation

pip install cos-comparison