This repository contains a Python application that utilizes the Streamlit framework to perform real-time face detection in images and video streams. The application uses a pre-trained face detection model to detect human faces, and draws bounding boxes around them for easy visualization.
To run this application, you must first install the required Python packages listed in the requirements.txt file. You can do this by running the following command in your terminal:
pip install -r requirements.txt
This will install all necessary packages, including Streamlit and the OpenCV and dlib computer vision libraries.
To run the application, simply navigate to the root directory of this repository in your terminal, and run the following command:
streamlit run app.py
This will start the Streamlit application, and open a new browser window with the user interface. From here, you can upload images or select a video stream source to perform real-time face detection.
If you would like to contribute to this project, feel free to submit a pull request with any changes or improvements you would like to make. We welcome contributions of all kinds, including bug fixes, new features, and code optimizations.
This project is licensed under the MIT License. For more information, please refer to the LICENSE file in this repository.
If you have any questions or feedback about this project, please feel free to contact us at the email address listed in the AUTHORS file. We would love to hear from you!