Ideogram Image-to-image reference potential space reconstruction

This is an AI image-to-image redrawing application based on Ideogram 4, reference image, structured JSON backtracking, latent space reconstruction.

Users only need to upload a reference image, and the system will first scale and analyze the image. Then, through a visual model, it observes the content of the image and automatically generates a structured JSON Prompt suitable for Ideogram 4. At the same time, the reference image will also be rescaled and encoded into a latent space via VAE, providing structural reference for subsequent generation.

Unlike ordinary text-to-image generation, this process does not rely solely on a single prompt; and unlike ordinary image-to-image generation, it does not simply feed the original image into the model for denoising. Instead, it combines "visual backtracking prompts" and "reference image latent space reconstruction" as dual sources of information.

The entire process is automated: reference image analysis, visual structure backtracking, JSON Prompt generation, width and height adjustment, reference image latent encoding, redrawing intensity control, Ideogram 4 scheduling and sampling, and final image output.

The final output is a newly reconstructed image based on the reference image, retaining the general composition and visual direction of the original image while generating a cleaner, more unified, and more suitable version for secondary creation.

It is suitable for applications such as reference image redrawing, cover redesign, poster restructuring, product image redrawing, ad image secondary creation, tattoo image redrawing, social media image generation, character image reconstruction, and design reference image regeneration.

If packaged as a RunningHub application, the core selling point can be directly expressed as:

Upload a reference image, automatically backtrack the visual structure, and regenerate high-quality images using Ideogram 4.