Real-Time Facial Recognition Project

Author: Vitor Mendes
Email: vitor.mendes@ieee.org

Description

This repository contains a real-time facial recognition project using a deep learning model. The project includes scripts for real-time video capture, face classification, and a pre-trained model for facial recognition.

Repository Structure

• main.py: The main script that initializes the facial recognition system.
• face_recognition.py: Script responsible for capturing real-time video and performing facial recognition.
• face_recognition_model.h5: Pre-trained model file for facial recognition.
• class_labels.npy: File containing the class labels for facial recognition.

Requirements

Make sure you have Python installed on your machine. The project's dependencies can be installed using the requirements.txt file.

Dependencies

• numpy
• opencv-python
• tensorflow
• keras

To install the dependencies, run the following command:

```bash pip install -r requirements.txt ```

How to Run

1. System Initialization: To start the facial recognition system, run the `main.py` script:

   ```bash python main.py ```

2. Real-Time Video Capture: The `face_recognition.py` script handles real-time video capture and face detection. This script is automatically called by `main.py`.

Code Organization

• Models: The facial recognition model is loaded from the `face_recognition_model.h5` file. This model is used to predict the classes of detected faces.

• Class Labels: The class labels for facial recognition are stored in the `class_labels.npy` file.

• Video Capture and Processing: Video capture and processing are managed by the `face_recognition.py` script, which uses the OpenCV library to capture frames in real time and perform face detection.

Contact

For questions or suggestions, please contact the author: Vitor Mendes (vitor.mendes@ieee.org).