🔍 Lucid TRACE

Technological Review of Artificial Content in Evidence

Lucid TRACE is a forensic video analysis tool designed to verify the authenticity of digital evidence. It uses a FastAPI backend to extract frames and run AI detection (via Sightengine/TruthScan), and a React frontend to provide a clean, user-friendly interface for investigators.

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🚀 Key Features

• Full-Stack Architecture: Decoupled React frontend and Python backend for scalability.
• Stochastic Sampling: Extracts random frames to prevent temporal overfitting.
• Dual-Metric Analysis: Calculates both Average Confidence and Max Spike to catch subtle deepfake edits.
• Evidence Hashing: Generates SHA-256 hashes for chain-of-custody verification.

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🛠️ Installation & Setup

1. Backend (Python/FastAPI)

1. Navigate to the backend folder:

   cd backend
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Start the Server:
   • Standard Command:

     uvicorn main:app --reload
     

   • If "uvicorn" is not recognized (Windows):

     python -m uvicorn main:app --reload
     

   The API will start at: http://127.0.0.1:8000

2. Frontend (React/Vite)

1. Open a new terminal and navigate to the frontend folder:

   cd frontend
   

2. Install Node dependencies:

   npm install
   

3. Start the UI:

   npm run dev
   

   Open your browser to the link provided (usually http://localhost:5173).

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📂 Project Structure

lucid-trace/
├── backend/                 # Python Logic
│   ├── main.py              # API Entry Point
│   ├── video_processor.py   # OpenCV Frame Extraction
│   ├── detector.py          # AI Detection Logic
│   └── requirements.txt     # Python Dependencies
└── frontend/                # React UI
    ├── src/
    │   ├── App.jsx          # Main Interface
    │   └── App.css          # Dark Mode Styling
    └── package.json         # Node Dependencies