Date of Award

5-2025

Document Type

Project

Degree Name

Master of Science in Computer Science

Department

School of Computer Science and Engineering

First Reader/Committee Chair

Dr. Jin

Abstract

The Virtual Makeup Streamlit application presents an advanced approach to digital cosmetic try-on by allowing users to apply makeup to their facial images in real time. This project uses computer vision and web technologies to create an interactive and user-friendly platform that capitalizes on the increasing popularity of virtual try-on solutions in the cosmetics industry.

At its core, the system uses effective facial detection and semantic segmentation techniques to recognize and separate facial areas such as lips and hair. Techniques such as U-Net and Resnet, and Midepipe are used to create accurate segmentation masks, which are essential for accurate makeup application.

The application further enhances the user experience by integrating rule-based overlay methods that apply makeup filters specific to the detected facial features. This ensures that the cosmetic effects, including lipstick, eye shadow, and blush, seamlessly integrate with the user’s skin tone and lighting environment.

By combining advanced image processing methods with an intuitive Streamlit interface, the Virtual Makeup Application not only demonstrates technical advances but also opens up new possibilities for practical applications in virtual retail and customized beauty consultations.

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