Real-Time Face Counter

This GitHub repository contains a Python script that utilizes OpenCV to perform real-time face detection and counting using your webcam. It's perfect for event organizers, researchers, or anyone interested in analyzing crowds or experimenting with computer vision.

Features:

• Real-time detection: Accurately detects faces in live video streams from your webcam.
• Face counting: Displays the total number of detected faces on the video frame.
• OpenCV powered: Leverages the capabilities of the robust OpenCV library for efficient detection.
• User-friendly: No complex setups, simply run the script and point your camera.
• Open-source and customizable: Modify the code to tailor it to your needs.

Requirements:

• Python 3.6+
• OpenCV (pip install opencv-python)

How to use:

1. Clone this repository or download the script.
2. Run the script: python main.py.
3. Point your webcam towards the area you want to analyze.
4. The script will display the video feed with bounding boxes around detected faces and the total count.
5. Press q to exit the application.

Contributing:

We welcome contributions to improve this script! Feel free to fork the repository and submit pull requests with enhancements or bug fixes.

License:

This project is licensed under the MIT License. See the LICENSE file for details.

Additional notes:

• This script uses the Haar Cascade classifier, which may not be perfect in all lighting conditions or scenarios.
• For more advanced face detection, consider exploring deeper learning techniques.
• You can experiment with different values for scaleFactor and minNeighbors in the detect_objects function to adjust the detection sensitivity.

Contact:

For any questions or feedback, please feel free to open an issue on this repository.