Face, Eye, Smile & Profile Detection with OpenCV

This project uses OpenCV and Haar Cascade classifiers to detect frontal faces, eyes, smiles, and profile faces in real time using your webcam.

Fictitious Use Case

Company: SeguriTech
Description:
SeguriTech is a fictitious company focused on smart security in office environments. The developed system allows real-time monitoring of employee access and behavior, detecting faces, smiles, and profiles to improve security and workplace atmosphere.

Features

• Frontal face detection
• Eye detection within the face
• Smile detection
• Profile face detection
• Real-time visualization with rectangles and labels

Requirements

• Python 3.x
• OpenCV (pip install opencv-python)

Usage

1. Clone this repository:

   git clone https://github.com/yourusername/seguritech-face-detection.git
   cd seguritech-face-detection

2. Install dependencies:

   pip install opencv-python numpy

3. Run the script:

   python practica.py

4. A window will open showing the real-time video.

   • Press q to exit.

Code Explanation

• Haar Cascade classifiers for face, eyes, smile, and profile are loaded.
• Video capture from the webcam is started.
• For each frame:
  • The frame is converted to grayscale.
  • Frontal and profile faces are detected.
  • For each face, eyes and smiles are detected.
  • Rectangles and labels are drawn over detected features.
• The system stops when the q key is pressed.

Credits

• Haar Cascade Classifiers: OpenCV
• Author: [Carlos Ramirez]