ABSTRACT: Choosing what to wear is a daily decision that consumes time and often leads to under-used wardrobes and repeated outfits. This paper presents GET READY WITH SELF, a web-based personal styling application that lets users upload photographs of their own clothes, automatically recognises each garment's category and colours, and generates complete outfit combinations suited to the occasion (casual, office, formal, party, travel), the current weather and the user's saved style preferences. Recommended outfits can be saved to a weekly planner. The system uses an Angular and PrimeNG front end, a Python FastAPI back end, SQLite storage and lightweight local image-processing techniques, avoiding paid AI APIs. Outfit quality is computed through a weighted scoring model: colour harmony (40%), clothing compatibility (30%), occasion and style suitability (20%) and weather suitability (10%). This paper describes the motivation, architecture, technologies, algorithms, database design, workflow, limitations and future scope of the system.Keywords: digital wardrobe, outfit recommendation, colour harmony, clothing recognition, personal stylist, FastAPI, Angular, weighted scoring
GET READY WITH SELF: AN AI-POWERED DIGITAL WARDROBE AND AUTOMATIC OUTFIT RECOMMENDATION SYSTEM
MRS. MANALI CHURI MISS. MRUNALI CHOUDHARI