Face Recognition

Overview

This project implements face recognition using Python and OpenCV. It detects and recognizes human faces in real-time or from static images. The system can be adapted for applications such as security, monitoring, and access control.

Features

• Face Detection: Identifies human faces in images or video streams.
• Real-Time Recognition: Processes video streams to recognize faces.
• Custom Dataset: Supports creating and training with custom datasets.
• Integration-Ready: Easily integrates into larger systems.

Project Structure

Face-Recognition/  
│  
├── face_recognition.py        # Main script for face detection and recognition  
├── dataset/                   # Folder containing images of faces for training  
│   ├── person1/               # Subfolder for person1's face images  
│   ├── person2/               # Subfolder for person2's face images  
│   └── ...  
├── models/                    # Pre-trained models or saved training data  
│   ├── face_model.pkl         # Example model file  
│   └── ...  
├── utils/                     # Utility scripts for preprocessing and analysis  
│   └── helper_functions.py    # Example utility script   
└── README.md                  # Project documentation  

Technologies Used

• Python: Core programming language for the project.
• OpenCV: For image processing and computer vision.
• Dlib/DeepFace (if applicable): Enhances facial recognition accuracy (if used).

License

This project is licensed under the MIT License. You are free to use, modify, and distribute this software under the terms of this license.