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Real-Time Face, Eyes, and Smile Detection

Face Detection Example

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