Face-Sight

Introduction

This is a real-time face detection app that uses the YOLOv7 model trained on a custom dataset. Given an image or a video stream, the app can detect faces and apply various transformations in real-time such as counting the number of faces, blurring faces, replacing faces with another image, and highlighting faces.

Features

• Real-Time Face Detection: Detects faces in an image or a video stream using the YOLOv7 model.
• Real-Time Face Count: Counts the number of faces in real-time.
• Real-Time Face Blur: Blurs the faces in real-time for privacy protection.
• Real-Time Face Pixelation: Pixelates the faces in real-time for privacy protection.
• Real-Time Face Replacement: Replaces the faces in real-time with another image.
• Real-Time Face Highlight: Highlights the faces in real-time.

Installation

Follow these steps to get the Face Detection App up and running:

1. Clone the Repository:

git clone https://github.com/yourusername/your-repo-name.git

2. Set Up a Virtual Environment (Optional but Recommended)

python -m venv env

3. Activate the Virtual Environment:

• On Windows:

  .\env\Scripts\activate

• On Unix or MacOS:

  source env/bin/activate

4. Run the config.py file: Run the script file to install the YOLOv7 model:

python config.py

Usage

To run the app using Streamlit:

• On Windows:

  streamlit run app.py

• On Unix or MacOS:

  streamlit run app.py

Then, open your web browser and go to http://localhost:8501 to view the app.

Acknowledgements

This project uses the YOLOv7 repo for face detection. You can find the original YOLOv7 repository here.

License

This project is licensed under the GNU GENERAL PUBLIC LICENSE. See the LICENSE file for details.