ForensicAI

ForensicAI is a comprehensive video analysis system that combines object detection and forensic intelligence powered by large language models (LLMs).

Features

• Real-time Video Analysis: Process live camera feeds or existing video files
• Object Detection: Identify and track objects using YOLO
• LLM-Powered Insights: Generate descriptions and insights for detected scenes
• Forensic Timeline: Visualize events in a chronological timeline
• Interactive Dashboard: Modern React frontend with real-time updates
• Frame Analysis: Ask questions about specific video frames

Architecture

The project consists of two main components:

1. Backend: Python-based server using Flask for API endpoints and video processing
2. Frontend: React application with Tailwind CSS for the user interface

Installation

Prerequisites

• Python 3.8 or higher
• Node.js 16 or higher
• npm or yarn

Automated Installation

Use the provided installation script:

./install.sh

Manual Installation

Backend

cd backend
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env
# Edit .env with your configuration

Frontend

cd frontend
npm install

Running the Application

Development Mode

# From the frontend directory
npm run start

This will start both the backend Flask server and the frontend Vite development server.

Production Mode

Backend:

cd backend
source venv/bin/activate
python run.py --prod

Frontend:

cd frontend
npm run build

The built frontend will be served by the Flask server at http://localhost:5000

API Documentation

See backend/README.md for detailed API documentation.

License

MIT License