qip-lumina 0.2.1

A research-grade Hybrid Quantum-Classical Image Processing Framework with NISQ noise simulation.

QIP Framework v0.2.1

Hybrid Quantum–Classical Image Processing Framework for NISQ-Era Analysis

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🔬 Research Context

The Problem

Quantum Image Processing (QIP) promises exponential advantages in computational complexity and storage. However, current hardware noise (decoherence, gate errors) poses a significant bottleneck. This framework provides the tools to analyze these trade-offs through hardware-aware simulation and rigorous benchmarking.

Our Solution

We present a modular framework designed to analyze these trade-offs. By implementing optimized Gray Code encoding and realistic hardware-aware noise models, this framework allows researchers to benchmark quantum algorithms against classical baselines under realistic constraints.

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👥 Authors

• M. Sowmya Priya
• K. Lalitha

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🛠️ Framework Architecture

qip_project/
├── qip_framework/      # Core Library Logic
├── main.py             # System entry point (CLI)
├── inference.py        # Single-image processing script
├── scripts/            # Benchmarking & Data generation tools
├── data/               # Sample research datasets
├── results/            # Experimental outputs & CSV files
└── docs/               # Technical documentation

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▶️ Installation

pip install qip-lumina

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🚀 Usage

Run a Complete Experiment

python main.py --algo qhed --encoding qpie --image data/sample.png

Single Image Processing

python inference.py path/to/image.png

Generate Benchmark Dataset

python scripts/generate_research_data.py

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📦 Features

• Hybrid Quantum–Classical Image Processing
• FRQI Image Encoding
• QPIE Image Encoding
• Quantum Edge Detection (QHED)
• Hardware-aware NISQ Noise Simulation
• Classical vs Quantum Benchmarking
• Research Dataset Generation
• CLI-based Experiment Pipeline

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📚 Requirements

• Python 3.8+
• Qiskit
• Qiskit Aer
• NumPy
• Pandas
• OpenCV
• Matplotlib
• Scikit-image

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📄 License

Licensed under the MIT License.

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🏢 Developed By

Lumina-AI-Works

https://github.com/Lumina-AI-Works