Streamlit Face Detection Application

This repository contains a Streamlit application for webcam-based face detection. The application uses OpenCV and a Haar Cascade classifier to detect faces from the webcam feed.

Contents

• LICENSE: License file for the project.
• README.md: This file. Provides an overview of the project.
• Streamlit_cam.py: Main Streamlit application script.
• haarcascade_frontalface_default.xml: Haar Cascade XML file for frontal face detection.
• webcam_cv3.py: Python script for webcam operations using OpenCV3.

Installation

1. Clone the repository:

   https://github.com/Shreyaprasad21/Face-Detection-Applciation.git
   cd Face-Detection-Application

2. Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate   # On Windows, use `venv\Scripts\activate`

3. Install the required packages

Usage

1. To run the Streamlit application:

   streamlit run Streamlit_cam.py

   or

   python -m streamlit run Streamlit_cam.py
   

2. The application will start and can be accessed at http://localhost:8501 in your web browser.

Files Description

• Streamlit_cam.py: This is the main script for the Streamlit application. It initializes the webcam, captures the video stream, and applies the Haar Cascade classifier to detect faces.
• haarcascade_frontalface_default.xml: Pre-trained Haar Cascade model for detecting frontal faces.
• webcam_cv3.py: An alternative script for handling webcam feed using OpenCV3 directly. It can be used for testing and debugging purposes.

License

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

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.