Al Outfit Try-On and Suitability Checker

Abstract

file:///C:/Users/AdminThe Al Outfit Try-On and Suitability Checker is an intelligent system developed to improve the online shopping experience by allowing users to virtually try outfits before purchasing them. In current online shopping systems, customers often face difficulty in selecting suitable clothes because they cannot physically try them. This creates confusion about size, fitting, and overall appearance. The proposed system uses Artificial Intelligence, Computer Vision, and Machine Learning techniques to solve this problem. It allows users to capture or upload their image and virtually view how selected outfits look on them. The system processes the user image using OpenCV and detects body landmarks using MediaPipe Pose Detection. Based on body structure and alignment, the outfit is placed over the user image to create a virtual try-on effect. The system then analyzes the fitting and generates a suitability score to indicate how well the outfit matches the user. It also provides simple style suggestions for better outfit selection. The project is developed using Python as the backend language and Tkinter as the user interface. Hugging Face models are used to improve intelligent prediction and outfit suitability analysis. This system helps users make better purchase decisions, reduces product return rates, saves time, and provides a personalized shopping experience. It can be further extended for real-time fashion recommendation systems in e-commerce platforms./Downloads/V5I1093.pdf