КЛАСИФІКАЦІЯ ПРИВАБЛИВОСТІ ЛЮДСЬКИХ ОБЛИЧ ЗА ГЕОМЕТРИЧНИМИ ХАРАКТЕРИСТИКАМИ ЗОЛОТОГО ПЕРЕТИНУ

This work is devoted to the training of SVM classification model for predicting attractiveness of human’s face. We will use Python language with Mediapipe opensource library for face recognition and getting landmarks. Then we will use scikit-learn library for training the SVM model easily. For attractiveness measurements, we will use only geometrical values, as “golden ratios”, which should be equal to the number of “phi”. For deploying our model, we will use Gradio library. The focus on this work was to see, how effective golden ratios could be for analyzing human’s faces attractiveness.