Image Based Clothing Style Recommendation System

In the ever-evolving world of fashion and e-commerce, personalization plays a crucial role in enhancing the shopping experience for customers. presents a novel Clothing Style Recommendation System that leverages deep learning techniques, particularly the deep-face, to provide tailored fashion suggestions to user’s based on their gender, height, favorite color, and age preferences. The system draws upon a vast dataset of clothing items from Amazon, which allows it to recommend outfits that align with the user’s unique style and demographics. The recommendation process begins by collecting user information regarding user image, height, favorite color and predict gender and age of user. system aims to overcome the limitations of traditional clothing recommendation methods by integrating both explicit user preferences (image of user, height, and favorite color) By considering these diverse elements, the system offers a more personalized fashion shopping experience. The implementation of this clothing style recommendation system is based on a large and diverse dataset from Amazon, encompassing a wide range of clothing items. The use of deep learning allows the system to continuously adapt and improve its recommendations, ensuring that users are presented with the latest and most fashionable clothing choices.