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| dc.contributor.author | Maira Imran, 01-135202-034 | |
| dc.contributor.author | Kainat Arshad, 01-135202-032 | |
| dc.date.accessioned | 2024-08-20T06:19:44Z | |
| dc.date.available | 2024-08-20T06:19:44Z | |
| dc.date.issued | 2024 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/17721 | |
| dc.description | Supervised by Ms. Mahvish Pervaiz | en_US |
| dc.description.abstract | The "AI Wardrobe Stylist" project aims to empower users with little knowledge of the fashion industry by providing them with personalized outfit recommendations tailored to Pakistani culture and traditions. The objective is to assist users in effortlessly planning their outfits through a mobile application, thus alleviating the need for manual closet sorting. Utilizing an Agile SDLC Model, an Android application with an AI backend has been developed. The AI model processes user inputs, including occasion type, location, date, and physical attributes, to generate outfit recommendations considering factors such as weather forecast, cultural norms, and individual features. Unlike existing systems, which rely solely on images, this project’s machine learning backend offers contextually relevant suggestions, bridging the gap in outfit recommendation systems tailored to Pakistani society. The outcome is an innovative solution that revolutionizes outfit planning by integrating AI technology with cultural specificity, enhancing users’ fashion experiences. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Computer Sciences | en_US |
| dc.relation.ispartofseries | BS (IT);P-2485 | |
| dc.subject | AI | en_US |
| dc.subject | Wardrobe | en_US |
| dc.subject | Stylist | en_US |
| dc.title | AI Wardrobe Stylist | en_US |
| dc.type | Project Reports | en_US |