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README.md
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# PRISM 2.0 - Advanced AI Content Analysis
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- **Single Analysis**: Detailed breakdown of individual images.
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- **Batch Analysis**: Process multiple files at once.
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- **AI Models**: Powered by InternVL, EasyOCR, and CLIP.
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- **Interactive UI**: Beautiful React-based interface with 3D animations.
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##
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# PRISM 2.0 - Advanced AI Content Analysis
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[](https://devranx-prism2-0.hf.space/)
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Prism is a state-of-the-art AI application designed for deep content analysis of images and documents. It leverages advanced multi-modal models to ensure content compliance, safety, and quality control.
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## 🌟 Features
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### 🔍 Advanced Visual Analysis
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- **Ribbon & Layout Detection**: precision detection of visual elements.
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- **Image Quality Assessment**: Checks for blur, resolution, and pixel variance.
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- **GNC (General Non-Compliance) Checks**: Identifies unauthorized visual gestures or icons.
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### 📝 Text & Content Intelligence
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- **Tagline Verification**: content and legibility analysis.
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- **Risk Assessment**: Detects high-risk content, gambling references, and illegal activities.
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- **Competitor Analysis**: Identifies competitor brand mentions.
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- **Sensitive Content Shield**: Filters inappropriate, religious, or violent imagery.
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### ⚡ Powerful Capabilities
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- **Single & Batch Processing**: Analyze one image or thousands at once.
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- **Interactive Reports**: Detailed breakdown of passes, fails, and specific issues.
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- **High-Performance Backbone**: Powered by **InternVL2.5-1B-MPO** for vision-language understanding and **EasyOCR** for robust text extraction.
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## 🚀 Live Demo
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Experience Prism 2.0 live on Hugging Face Spaces:
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👉 **[https://devranx-prism2-0.hf.space/](https://devranx-prism2-0.hf.space/)**
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## 🛠️ Tech Stack
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- **Frontend**: React (Vite) with a premium, responsive UI.
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- **Backend**: Flask (Python) for API handling and orchestration.
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- **AI Models**:
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- `InternVL2.5-1B-MPO` (Vision Language Model)
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- `EasyOCR` (Optical Character Recognition)
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- `CLIP` (Semantic Understanding)
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- **Deployment**: Dockerized for seamless scalability.
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## 📦 Installation (Local)
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1. **Clone the repository**
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```bash
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git clone https://github.com/devsingh02/PRISM.git
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cd PRISM
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```
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2. **Set up Python Environment**
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```bash
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python -m venv .venv
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source .venv/bin/activate # On Windows: .venv\Scripts\activate
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pip install -r requirements.txt
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```
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3. **Run the Application**
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```bash
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python app.py
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```
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The app will run at `http://localhost:7860`.
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## 🐳 Docker Support
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Prism is fully containerized.
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```bash
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docker build -t prism-app .
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docker run -p 7860:7860 prism-app
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```
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