Browsing by Author "Dur-e-Sameen, Minahil Ijaz and Taifa Mustafa"

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    Generative AI for Sketch transformation into Styled 2d images
    (UMT, Lahore, 2025) Dur-e-Sameen, Minahil Ijaz and Taifa Mustafa
    The pace of advancement in AI-based generative models has had a profound impact on the world of digital art, allowing machines to enhance creative processes and ambiguities in ways that often allows for a more efficient and imaginative way to create. The initiative that is introduced here takes advantage of these systems to bridge hand-drawn sketches to modern digital artwork through the development of an AI-powered platform that converts sketches to 2D images rich with style. Though text-to-image generating tools have proliferated in popularity, efficient sketch-to-image conversion tools remain relatively sparse, and even fewer allow for similar multiple artistic styles along with user's choice and control. To address this gap, we present here a learning-based system that combines Stable Diffusion with ControlNet for deep learning supports to learn the structure of the sketch and output information and quality in various artistic styles (i.e., realistic, cartooning, anime). To complete the task of the application, we created a front-end application using React and Vite and we developed a back-end API based on FastAPI for communicating with the model and handle task processing. We set up Supabase for user authentication, images stored, and user history.