Metadata-Version: 2.4
Name: cineinfini-audit
Version: 0.1.2
Summary: Adaptive multi‑stage video quality audit pipeline
Author-email: Salah-Eddine BENBRAHIM <benbrahim.salah.eddine.777@gmail.com>
License: MIT
Project-URL: Homepage, https://github.com/CineInfini/Video_Quality_Auditor
Project-URL: Repository, https://github.com/CineInfini/Video_Quality_Auditor.git
Project-URL: Documentation, https://cineinfini.readthedocs.io
Keywords: video-quality,audit,SSIM,optical-flow,CLIP,DINOv2
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Multimedia :: Video
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: opencv-python>=4.8
Requires-Dist: numpy>=1.24
Requires-Dist: matplotlib>=3.5
Requires-Dist: pandas>=1.5
Requires-Dist: scipy>=1.9
Requires-Dist: scikit-image>=0.19
Requires-Dist: Pillow>=9.5
Requires-Dist: torch>=2.0
Requires-Dist: onnxruntime>=1.14
Requires-Dist: open-clip-torch>=2.20
Requires-Dist: transformers>=4.30
Requires-Dist: requests>=2.28
Requires-Dist: click>=8.1
Requires-Dist: markdown>=3.4
Requires-Dist: weasyprint>=60
Requires-Dist: plotly>=5.15
Provides-Extra: dev
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Requires-Dist: pytest-cov>=4.0; extra == "dev"
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Dynamic: license-file

# 🎬 CineInfini – Video Quality Auditor

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python 3.9+](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

**CineInfini** is an open‑source, modular pipeline for automatic, explainable video quality auditing. It goes beyond traditional fidelity metrics (PSNR, SSIM) by assessing **temporal stability, identity consistency, semantic coherence, and narrative flow** – all in a single GPU‑accelerated pipeline.

[Features](#-features) • [Installation](#-installation) • [Quick Start](#-quick-start) • [Documentation](#-documentation) • [Contributing](#-contributing)

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## ✨ Features

- **Adaptive shot detection** – HSV histogram with percentile‑based threshold  
- **7 intra‑shot metrics** – motion peak (optical flow), 3D‑SSIM, flicker, identity drift (ArcFace), long‑range SSIM, high‑frequency flicker, CLIP temporal consistency  
- **Inter‑shot coherence** – structure (SSIM), style (histogram), semantic (CLIP)  
- **Narrative coherence** – DINOv2 cosine similarity between shots  
- **Two‑stage audit** – automatically optimises processing parameters and composite weights  
- **GPU acceleration** – CUDA for CLIP/DINOv2, parallel shot processing (4 workers)  
- **Exhaustive reports** – Markdown dashboards with bar charts, radar plots, improvement suggestions, and JSON exports  
- **Benchmark mode** – compare multiple videos (synthetic / real) with inter‑video dashboards  

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## 🛠 Installation

### From PyPI (recommended)
```bash
pip install cineinfini-audit
