semvec/pypi-packages huggingface dataset:
quantumvision 0.1.0
Quantum-Inspired Computer Vision Framework (Edge Detection, Contrast Enhancement)
License: MIT
Requires Python: >=3.8
Keywords: quantum computing, computer vision, edge detection, contrast enhancement, AI, image processing, quantum-inspired

# QuantumVision  
**Quantum-Inspired Computer Vision Framework**  
*Version 0.1.0*  

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## Overview  

**QuantumVision** is a Python research library that bridges **quantum mechanics** and **classical computer vision**.  
It models image pixels as quantum states with **amplitude** and **phase** components, enabling quantum-inspired operations such as interference-based edge detection and fidelity-driven contrast enhancement.  

This framework demonstrates how physical analogies—phase interference, coherence, and fidelity—can yield **interpretable nonlinear transformations** for visual perception and image analysis.

Currently implemented modules:  

1. **`qedge`** — Quantum-Inspired Edge Detection  
2. **`qcontrast`** — Quantum State Contrast Enhancement  

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## Key Features  

| Module | Function | Quantum Analogy | Outcome |
|---------|-----------|----------------|----------|
| **qedge** | `qedge_detect()` | Phase interference (`sin²(Δθ)`) | Enhanced edge localization without convolution kernels |
| **qcontrast** | `qcontrast_enhance()` | Quantum state fidelity (`ψ·ψ̄`) | Nonlinear brightness amplification preserving global luminance |

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## Installation  

From PyPI:  
```bash
pip install quantumvision
```
Once installed, you can import and use the core functions:
```python
from quantumvision import qedge_detect, qcontrast_enhance


## Scientific Motivation  

Traditional computer vision algorithms (e.g., Sobel, Laplacian) are based on linear spatial derivatives.  
In contrast, **QuantumVision** introduces a *nonlinear, phase-based formalism* inspired by quantum mechanics, where intensity variations are treated as phase differences in probability amplitudes.  

This yields algorithms that are:
- More robust to illumination and contrast changes,  
- Mathematically grounded in wave interference,  
- Intuitively interpretable as “quantum probability fields.”

## License  
MIT © 2025 Shambhavi Prasad

## Contact  
Author: Shambhavi Prasad  
Email: shambhaviprasad21@gmail.com  
GitHub: https://github.com/Shambhavi2112