Published Paper Details:

Fashion holds significant sway in our everyday lives, serving as a mirror of our personal style and identity. Yet, navigating the world of fashion and personal style presents challenges, particularly in choosing outfits that flatter individual body types and shapes. This process often proves daunting and time-consuming, leading to indecision and a lack of confidence in one's appearance. To tackle these hurdles, this study aims to develop an ML-based Outfit Suggestion System. Introducing an innovative approach, this system harnesses machine learning methodologies, including deep learning, computer vision, and natural language processing. By scrutinizing an extensive dataset encompassing clothing items and body shape attributes, the system furnishes tailored outfit recommendations designed to suit individual body types and shapes. This research marks a notable stride in the evolution of fashion recommendation systems, offering a promising avenue for fashion enthusiasts seeking personalized outfit guidance across varied contexts.