PictoPy

This project seeks to create a desktop application for an image gallery, with machine learning models powering its functionality in the background. This will enable features such as object, face, and scene tagging. The user interface will mimic that of a traditional gallery app, with capabilities like expansion and sliding. Data will be stored in lightweight databases utilizing SQLite, while the backend will employ YOLO architecture-driven (and similiar) models. At the end of this project, my aim is to establish a streamlined ML pipeline integrating multiple models. This pipeline will preprocess and store photos, allowing users to search for specific types of photos based on generated tags.