import streamlit as st


def about():
    st.markdown("""
# About Me

## Social Links

- **GitHub**: [https://www.github.com/prabhukiran8790](https://www.github.com/prabhukiran8790)
- **LinkedIn**: [https://www.linkedin.com/in/prabhukirankonda](https://www.linkedin.com/in/prabhukirankonda)
- **Twitter**: [https://twitter.com/prabhukirantwt](https://twitter.com/prabhukirantwt)
- **Email**: [prabhukiran426@gmail.com](mailto:prabhukiran426@gmail.com)

## Website

Visit my website at [https://prabhukirankonda.vercel.app](https://prabhukirankonda.vercel.app).

# About the Project

This project is focused on GFPGAN, a remarkable creation by the ARC Lab at Tencent PCG. GFPGAN stands for **Generative Face Progressive Growing Adversarial Network**. It is an advanced face restoration model designed for various applications, with a primary focus on restoring the appearance of faces in old photographs and enhancing AI-generated faces.

## Key Features

- **Face Restoration**: GFPGAN is an innovative solution for restoring the quality and appearance of faces in vintage or damaged photographs.
- **AI-Generated Faces Enhancement**: It can also be used to enhance the realism and quality of AI-generated faces, making them look more natural and lifelike.
- **Practical Application**: This algorithm provides a practical and efficient approach to improving the visual quality of facial images, which can have numerous applications in image editing and restoration.

GFPGAN represents a significant advancement in the field of computer vision and image processing, opening up new possibilities for improving the visual quality of images containing faces.

For more details and updates about GFPGAN [github.com/TencentARC/GFPGAN](https://github.com/TencentARC/GFPGAN)

""")