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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM45536
Volume:
9 |
4 |
Apr 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Artificial Intelligence (AI) and computer vision technologies have evolved rapidly, enabling new creative possibilities. One of the most exciting developments is text-to-image generation, where a system creates realistic images based on a natural language description. However, traditional models often struggle with subject consistency, making it hard to generate images that represent the same character across different scenes. Our project, “Text-to-Image Generator with Consistory,” addresses this problem using NVIDIA’s Consistency Model, known as Consistory. This model enables consistent subject generation across multiple scenes without needing retraining. We developed a web application using Streamlit for the frontend and integrated NVIDIA’s Consistency Model API as the backend. The system allows users to input a subject description and two different scene prompts. It generates high-quality, visually coherent images, maintaining subject identity across scenes. The application is useful for storytelling, branding, education, and entertainment.
KEYWORDS
Publication Date
4/22/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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