Smile Detection using OpenCV

This project uses OpenCV to detect faces and smiles in real-time through a webcam feed. It uses Haar Cascades for face, eye, and smile detection.

Features

• Real-time face detection.
• Smile detection within detected faces.
• Visualizes detections by drawing rectangles around faces and smiles.

Requirements

To run this project, you need to have the following installed:

• Python 3.x
• OpenCV (cv2)

How to Run

1. Clone this repository to your local machine. Ensure you have OpenCV installed using the command:

pip install opencv-python

2. Run the script:

python smileDetection.py

The program will open a video stream using your webcam. To stop the video stream, press the q key.

How It Works

• The program captures video frames from the webcam in real-time.
• Each frame is converted to grayscale and processed using the Haar Cascade Classifiers for face, eye, and smile detection.
• Rectangles are drawn around detected faces and smiles to visualize the detections.

Example

When the program is running, it looks like this:

• Faces are highlighted with a blue rectangle.
• Smiles are highlighted with a red rectangle.

Acknowledgements

• OpenCV Haar Cascades were used for face and smile detection.
• The code was adapted from the OpenCV tutorials and examples.