Outfit Suggestion System: Context-Aware Clothing Recommendation Using Image Processing and Weather Data

Abstract

Clothing choice is a routine activity that usually entails taking many factors into account, including weather, occasion, and individual preferences for style. Here is an automated fashion recommendation system based on image processing and weather forecasting that gives personalized wardrobe suggestions. The users can upload pictures of their clothes and they are categorized by style and color with the help of a lightweight image analysis module. The real-time weather information is incorporated into the recommendation system so that the recommended attire is contextually relevant. The system is developed as a web application with a Flask-based back-end and a React-based front-end to provide a smooth user experience. Experimentation results show excellent classification accuracy for clothing categories and positive user reactions regarding relevance in suggestions. The suggested solution minimizes decision fatigue, is more convenient, and is a real application of artificial intelligence for daily life.