This project aims to develop a facial recognition system using artificial intelligence and machine learning techniques. The system is designed to identify and verify individuals based on their facial features, with potential applications in security, law enforcement, and identity verification.

Key Features

Face Detection: The system can detect faces in images and videos using OpenCV and Haar cascades. Face Recognition: The system uses a machine learning model (e.g., Convolutional Neural Networks (CNNs) or Support Vector Machines (SVMs)) to recognize and identify faces based on their unique features. Database Management: The system stores and manages a database of known faces, allowing for efficient face recognition and verification. Real-time Processing: The system can process and recognize faces in real time, making it suitable for applications that require rapid identification.

Technical Details Programming Languages: Python, OpenCV, and scikit-learn Machine Learning Models: Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) Database: SQLite or MongoDB Operating System: Windows, Linux, or macOS

Project Structure data: Contains the dataset used for training and testing the machine learning models models: Holds the trained machine learning models src: Contains the source code for the facial recognition system utils: Holds utility functions for data preprocessing, feature extraction, and visualization

How to Run

Clone the repository to your local machine
Install the required dependencies using pip install -r requirements.txt
Run the facial recognition system using python main.py
Follow the instructions in the README.md file for further details on usage and configuration

License This project is licensed under the MIT License. See the LICENSE file for details.

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