AI Image Prompt Generation for Relevance and Low Processing Load
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Solution Overview
Problem
Existing generative artificial intelligence models often generate images that are not fully relevant to the user's intent due to imprecise queries and lack of capturing the user's intent, resulting in images that do not adequately express desired concepts.
Innovation Solution
A method involving a prompt engine that generates an image prompt using a set of descriptors, tailored to a specific generative AI model, to improve image relevance and reduce processing load by pre-processing user inputs and adjusting the prompt format to match the model's preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users provide simple queries to generative AI models, then the processing load is reduced, but the image relevance to user intent deteriorates
Solution Approach 1:
The system performs preliminary actions by collecting descriptors and generating an enhanced prompt before the actual image generation. The prompt generator creates a context-rich prompt that expands on the user's simple query, incorporating relevant descriptors and context information. This preliminary processing ensures that the generative AI model receives a detailed, intent-capturing prompt without requiring the user to provide complex queries, thus maintaining both low processing load and high image relevance.
2Manufacturing precision
If users provide detailed queries to generative AI models, then the image relevance improves, but the processing load increases
Solution Approach 1:
The system extracts the essential intent from the user's simple query and separates it from the detailed prompt construction. The prompt generator model takes the user's brief input and extracts the core meaning, then enriches it with context and descriptors. This extraction approach allows the system to achieve detailed, relevant image generation without requiring users to provide lengthy queries, thereby maintaining low processing load while improving image relevance.
3Manufacturing precision
If the prompt format is customized to match model preferences, then the image generation quality improves, but the device complexity increases
Solution Approach 1:
The prompt generator acts as an intermediary between the user's simple query and the generative AI model. It translates user input into the specific prompt format required by the model, handling the complexity of format customization internally. This intermediary layer improves image generation quality by providing properly formatted, context-rich prompts while shielding users from the underlying complexity, thus maintaining ease of operation.
4Manufacturing precision
If the system generates context-rich prompts, then the image relevance to user intent improves, but the processing requirements increase
Solution Approach 1:
The system performs preliminary action by generating context-rich prompts before the actual image generation process. The prompt generator collects descriptors, understands user intent, and creates a comprehensive prompt that encapsulates all necessary context. This preliminary enrichment ensures that the generative AI model receives a complete, well-structured prompt, improving image relevance while consolidating processing requirements into a single efficient step rather than requiring multiple iterative refinements.
Data Source
AI summary
An image generation system may receive a set of descriptors. An image generation system may generate a prompt input using the set of descriptors. An image generation system may apply a prompt generator model to the prompt input to generate an image prompt for a generative artificial intelligence (AI) model, wherein the image prompt includes a context generated based on the set of descriptors, wherein the image prompt includes a prompt format configured to be input into the generative AI model. An image generation system may input the image prompt to the generative AI model, the generative AI model using the image prompt to generate an image based on the context.