https://github.com/denatajp/smiledetection

A real-time face and smile detection application using the OpenCV library. By utilizing the webcam, the program automatically detects faces and smiles, drawing boxes around the detected areas. It uses Haar Cascade Classifiers for object detection and runs interactively until the user presses the q key to stop.
https://github.com/denatajp/smiledetection

object opencv pyhton

Last synced: 2 months ago
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A real-time face and smile detection application using the OpenCV library. By utilizing the webcam, the program automatically detects faces and smiles, drawing boxes around the detected areas. It uses Haar Cascade Classifiers for object detection and runs interactively until the user presses the q key to stop.

• Host: GitHub
• URL: https://github.com/denatajp/smiledetection
• Owner: denatajp
• Created: 2024-09-05T04:27:36.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-09-05T09:44:26.000Z (9 months ago)
• Last Synced: 2025-04-04T05:19:10.908Z (2 months ago)
• Topics: object, opencv, pyhton
• Language: Python
• Homepage:
• Size: 5.86 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
![](https://img.shields.io/badge/Python-red?style=for-the-badge&logo=python) 

# 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:

``` bash

pip install opencv-python

```

2. Run the script:

``` bash

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.

![image](https://github.com/user-attachments/assets/6eb083bb-5a6d-4283-98c1-e0ef344ad3eb)

# Acknowledgements

- OpenCV Haar Cascades were used for face and smile detection.

- The code was adapted from the OpenCV tutorials and examples.