Face Shape Predictor

Personalized recommendations in fashion and beauty (e.g., suggesting flattering eyeglass frames or hairstyles) often lack a scientific basis. This project leverages the power of machine learning and computer vision to predict a person's face shape (e.g., oval, square, round) from an image, providing a data-driven approach to personalization. Using Python, OpenCV, and Dlib for facial landmark detection, the model analyzes key facial proportions to make its prediction. The application is built with Streamlit, providing an interactive web interface where users can upload their photo and instantly receive their result.