Skip to content

madhushree180/Shoplifting-Detection-Using-Video-Surveillance

Repository files navigation

readme_content = """# Enhanced Shoplifting Detection System

Features

  • 🔐 Secure login system
  • 🎥 Real-time video processing
  • 🚨 Automatic anomaly detection and capture
  • 📊 Live monitoring dashboard
  • 📁 Anomaly image management
  • 🔄 Alert system with different severity levels

Installation

  1. Run the installation script: python install_system.py
  2. Place your YOLOv8 model in config/shoplifting_weights.pt
  3. Run the system: python run_detection_system.py

Login Credentials

Usage

  1. Access the system at http://localhost:5000
  2. Login with the provided credentials
  3. Upload a video file
  4. Start detection
  5. Monitor live feed and captured anomalies

Directory Structure

  • config/ - Configuration files and model
  • uploads/ - Uploaded video files
  • anomalies/ - Captured anomaly images
  • logs/ - System logs
  • static/ - Static web assets
  • templates/ - HTML templates

API Endpoints

  • / - Login page
  • /dashboard - Main dashboard (requires login)
  • /upload_video - Upload video file
  • /start_detection - Start detection
  • /stop_detection - Stop detection
  • /video_feed - Live video stream
  • /anomalies - Get anomaly data
  • /anomaly_images/<filename> - Serve anomaly images

Configuration

Edit config/enhanced_parameters.py to customize:

  • Detection thresholds

  • High-value zones

  • Behavior patterns

  • Alert settings """

    with open("README.md", "w") as f: f.write(readme_content) print("✓ Created README.md")

def main(): """Main installation function""" print("🔧 Enhanced Shoplifting Detection System Installer") print("=" * 50)

# Install requirements
if not install_requirements():
    print("❌ Installation failed!")
    sys.exit(1)

# Create project structure
create_project_structure()

# Create sample files
create_sample_files()

print("\n✅ Installation completed successfully!")
print("\nNext steps:")
print("1. Place your YOLOv8 shoplifting detection model in 'config/shoplifting_weights.pt'")
print("2. Run: python run_detection_system.py")
print("3. Open browser to: http://localhost:5000")
print("4. Login with: madhu25@gmail.com / madhu123")

if name == "main": main()

About

AI-based Anomaly detection according 3 behaviors

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages