Real-Time Face, Eyes, and Smile Detection

This project demonstrates how to use OpenCV, a powerful computer vision library, to perform real-time detection of faces, eyes, and smiles via a webcam. The detection results are visualized by drawing rectangles around the detected features directly on the video feed.

Key Features

• Real-Time Detection: Utilizes the webcam to detect and display faces, eyes, and smiles in real-time.
• Haar Cascade Classifiers: Uses pre-trained Haar Cascade classifiers for accurate detection of facial features:
  • haarcascade_frontalface_default.xml: Detects faces.
  • haarcascade_eye.xml: Detects eyes within detected faces.
  • haarcascade_smile.xml: Detects smiles within detected faces.
• Visualization: Draws colored rectangles around detected features:
  • Blue rectangles for faces.
  • Green rectangles for eyes.
  • Red rectangles for smiles.

Requirements

• Python 3.10 and above
• OpenCV
• Jupyter Lab (for running the code in a notebook environment)

Installation

1. Clone the repository:

   git clone https://github.com/Arsalanzabeeb786/Face-Detection-with-OpenCV.git
   cd face-detection