Authors - Srishti Mathur, Hrishita Patra, Suhani Verma, Dhruva R Prasad, Shylaja S.S Abstract - The conventional way of preparing an advertisement is an elaborate process incorporating human subjectivity and human resources heavily dependent on creativity. Making advertisements by human effort can be regarded as an inefficient utilization of capital for small to medium-scale businesses due to increased cost of production. Even in current advancements in the development of generative techniques including LLM-based strategies for Advertisement Generation with Prompts, creating apt prompts for the depiction of products requires human expertise, making them less accessible. In order to overcome the challenges presented by the current models, we introduce a fast, affordable, and scalable platform for the automation of advertisement generation for products leveraging the capabilities of pre-trained diffusion models. The proposed system requires no training or fine-tuning since everything is performed at the inference level. The AI-aware system for designing assists in the identification of color schemes and attributes from the images of the products, whereas the descriptions and categories of the items help identify the theme and pattern recommendations for advertisements. These recommendations are channeled through a pre-trained Stable diffusion model guided by the LLaMA language model.
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