Bank_Management

Apna Bank - Banking System with Face Recognition Admin Authentication

Overview

Apna Bank is a simple banking application that provides a secure interface for both administrators and regular users. The system includes face recognition technology for administrator authentication and standard password protection for regular user accounts.

Features

User Features

• Account Creation: New users can create accounts with a username and password
• Balance Checking: Users can check their current account balance
• Deposits: Users can deposit money into their accounts
• Withdrawals: Users can withdraw money with proper PIN verification
• Password Management: Users can change their passwords

Admin Features

• Secure Access: Face recognition technology for admin authentication
• User Management: Administrators can view all registered users and their details

Technical Components

Face Recognition System

• Uses OpenCV and LBPH (Local Binary Patterns Histograms) Face Recognizer
• Face data collection and model training capabilities
• Real-time face detection and recognition for admin login

Data Management

• User data stored in CSV format for simplicity
• Secure PIN verification for sensitive operations

Project Structure

.
├── bank2.py               # Main banking application
├── user.csv               # User data storage
├── dataset/               # Face samples storage directory
│   └── admin.*.jpg        # Admin face samples
├── trainer.yml            # Trained face recognition model
└── new.ipynb              # Jupyter notebook with face recognition setup code

Setup and Installation

Prerequisites

• Python 3.x
• Required libraries:
  • pandas
  • numpy
  • matplotlib
  • opencv-python (cv2)
  • pillow (PIL)

pip install pandas numpy matplotlib opencv-python pillow

Face Recognition Setup

1. Run the save_faces.py script to collect admin face samples:

   # This will capture 30 images of your face for training
   # Code available in new.ipynb

2. Train the face recognition model:

   # This will create trainer.yml file used for recognition
   # Code available in new.ipynb

Usage

Starting the Application

Run the main application file:

python bank2.py

Main Menu Options

1. Admin Login (Face Unlock): Access administrative features using face recognition
2. User Login: Regular user login with username and password
3. Create Account: Create a new user account
4. Exit: Exit the application

User Menu Options

1. Check Balance: View current account balance
2. Deposit: Add funds to account
3. Withdraw: Remove funds from account (requires PIN verification)
4. Change Password: Update account password
5. Logout: Return to main menu

Security Features

• Face recognition for admin access
• PIN verification for withdrawals
• Password protection for all accounts

Future Enhancements

• Money transfer functionality between accounts
• Transaction history tracking
• Enhanced security measures
• Web or mobile interface

Contributing

Feel free to fork this repository and submit pull requests with any enhancements.

License

[Your License Choice]

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This project was created for educational purposes and demonstrates basic banking functionalities along with face recognition security.