AI Text To Image Generation Web Application
| dc.contributor.advisor | Vágner, Anikó Szilvia | |
| dc.contributor.author | Ezeldin, Mohamed Hesham Mohamed Fathy | |
| dc.contributor.department | DE--Informatikai Kar | |
| dc.date.accessioned | 2026-02-12T17:44:32Z | |
| dc.date.available | 2026-02-12T17:44:32Z | |
| dc.date.created | 2025-07-17 | |
| dc.description.abstract | My thesis focuses on developing a web application that generates images from text prompts using OpenAI's DALL·E model. I built the frontend with React, JavaScript, HTML, and CSS, which sends user prompts to the backend for image generation. The backend processes these prompts through DALL·E and returns the generated images to the frontend. To enable community sharing, users can submit their name, prompt, and image, which the backend stores in Cloudinary and logs in MongoDB. The system provides feedback on the success or failure of each image-sharing attempt. This project showcases the integration of AI-driven image generation with modern web technologies. | |
| dc.description.course | Programtervező informatikus | |
| dc.description.degree | BSc/BA | |
| dc.format.extent | 49 | |
| dc.identifier.uri | https://hdl.handle.net/2437/404357 | |
| dc.language.iso | en | |
| dc.rights.info | Hozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében. | |
| dc.subject | Dalle Routes | |
| dc.subject | Fullstack | |
| dc.subject | Cloudinary | |
| dc.subject.dspace | Informatics::Computer Science | |
| dc.title | AI Text To Image Generation Web Application |
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