Text-to-Image Generator with Consistory

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.

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-04-22
DOI
https://doi.org/10.55041/ijsrem45536
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Text-to-Image Generator with Consistory

P. S. Ramesh
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Cell Image Analysis Techniques
article

Text-to-Image Generator with Consistory

P. S. Ramesh
article en

Abstract

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.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(04)
Openalex Percentile: Top 93%
Cell Image Analysis Techniques
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