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This paper presents an AI-powered fashion outfit recommender, an intelligent wardrobe assistant designed to enhance personal fashion decision-making through image similarity models and personalized recommendation logic. Users can upload images of their clothing, which are processed using CLIP (Contrastive Language-Image Pre-training) for classification and recommendation. The platform integrates Express.js for backend APIs and interaction with the Flask server running the CLIP model. The system provides wardrobe suggestions, and when gaps are detected, it offers suitable alternatives from e-commerce platforms like Amazon and Flipkart. This paper details the system architecture, core functionalities, implementation strategy, and future potential of this AI-driven fashion assistant.
Keywords:
AI fashion assistant, smart wardrobe, Express.js, CLIP, outfit recommendation, e-commerce integration, image similarity, personalization, user privacy.
Cite Article:
"AI-Powered Fashion Outfit Recommender", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.c482-c490, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505257.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator