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dc.contributor.author | Asadullah, 01-134211-013 | |
dc.contributor.author | Saad Ahmed, 01-134211-077 | |
dc.date.accessioned | 2025-05-13T07:07:26Z | |
dc.date.available | 2025-05-13T07:07:26Z | |
dc.date.issued | 2024 | |
dc.identifier.uri | http://hdl.handle.net/123456789/19517 | |
dc.description | Supervised by Mr. Qazi Mohsin Ejaz | en_US |
dc.description.abstract | The retail landscape in Pakistan is shifting towards online platforms, but the footwear industry faces challenges like size accuracy, lack of innovation, and limited online options. FitFoot aims to address these issues by creating an e-commerce platform tailored for Pakistani consumers. Utilizing technologies like augmented reality and deep learning, FitFoot offers features such as virtual try-ons and precise size predictions to enhance the online shopping experience. FitFoot focuses on eliminating the need for physical store visits and resolving confusion from varying size standards. By employing computer vision and foot measurement prediction algorithms, the mobile app offers a seamless and accurate shopping experience. Pre-trained YOLOv5 models and Blender-generated 3D shoe models ensure realistic virtual try-ons, pushing the boundaries of footwear retail innovation in Pakistan. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Computer Sciences | en_US |
dc.relation.ispartofseries | BS(CS);P-02284 | |
dc.subject | Fit Foot | en_US |
dc.subject | Virtual | en_US |
dc.subject | Try-on AR | en_US |
dc.title | Fit Foot : Virtual Try-on AR | en_US |
dc.type | Project Reports | en_US |