DeepStableYolo: DeepSeek-Driven Prompt Engineering and Search-based Optimization for AI Image Generation

Hector D. Menendez, Gema Bello-Orgaz, Cristian Ramírez Atencia

Keywords: Generative AI, Large Language Models, Evolutionary Computation, DeepSeek, Stable Diffussion, YOLO, StableYolo, DeepStableYolo

TL;DR: Enhacing search-based image generation with visualization and LLM-enriched prompts

Abstract: AI-driven image generation heavily relies on effective prompt engineering and precise tuning of model parameters. The StableYolo framework addressed these challenges by integrating evolutionary computation with Stable Diffusion, enabling simultaneous optimization of both prompts and model parameters while using YOLO as a guiding metric to enhance image quality. In this work, we extend the capabilities of StableYolo by introducing mechanisms for prompt improvement through large language models (LLMs), aiming to maximize image generation quality. We incorporate DeepSeek to enhance prompt engineering, ensuring more effective and context-aware prompt generation. However, our refined approach demonstrates that enhancing prompts does not yield significant improvements in either the efficiency or quality of AI-generated images, suggesting that clear and concise prompts are equally effective in the process.

Submission Number: 13