/idea2img-optimizer

Optimize image generation prompts through human-in-the-loop black-box optimization, turning abstract ideas into concrete visuals.

Primary LanguageDockerfileMIT LicenseMIT

idea2img-optimizer

idea2img-optimizer is an experimental tool designed to bridge the gap between abstract mental imagery and concrete visual representations.
It leverages AI-powered image generation and human-in-the-loop black-box optimization techniques to transform users' conceptual ideas into tangible visual content.

Key Features

  • Integration with Diffusers (image generation library) and Optuna (black-box optimization library)
  • Human-in-the-loop feedback mechanism within a black-box optimization workflow for prompt refinement
  • User-friendly interface for idea input and image evaluation

How It Works

  1. Idea Input: Users provide a set of keyword prompts (image tags) for image generation.
  2. Initial Generation: The system generates a set of initial images based on randomly selected keywords from the user input.
  3. Human Feedback: Users provide scores on the generated images, indicating how closely they align with their mental concept.
  4. Optimization: The system utilizes this feedback to optimize the prompts and generate new images.
  5. Iteration: Steps 3 and 4 are repeated until the user is satisfied with the result.

Getting Started

WIP

License

This project is licensed under the MIT License.


If you have any questions or feedback, please open an issue in this repository.