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“using this json as reference, generate a person holding my product [attach product image]” > GPT-Image 2.5 g… - AI prompt reference from CC Prompt Galaxy

GPT-Image Product Character Reference Workflow AI Image Prompt

Prompt

Using this JSON as reference, generate a person holding my product [attach product image]. GPT-Image 2.5 generates the photo with that person holding your product. Compare it with a version generated without the reference and look at the difference in lighting and color grading. Save the generated character photo you're happy with as your reference. For future generations, attach the character photo each time and ask it to preserve the same facial features. Now you have a reference character you can use across multiple product photos. You can also iterate the base JSON prompt and chat back and forth with GPT-6 Astra based on what you want, then repeat the same process. This gives you much more direction over the color grading instead of leaving everything up to the model. The basic colours and grainy look are some of the things that can make an image feel AI-generated, so pay attention to those when comparing your results. This is how you can start building a library of high quality UGC images around your own products. The JSON gives GPT-Image 2.5 the lighting and color direction, your character reference helps with consistency, and you control the product placement. Once you have that starting point, you can keep creating variations without writing everything from scratch. GPT-Image 2.5 Sunburst & Flare are available on Higgsfield. Try this with your own product and reference images there.

AI Image Content Analysis

Content: Structure: JSON sets lighting/color direction; attach product image to generate a person holding the product; save approved character as reference and reuse for facial consistency; compare no-reference version, iterate JSON/dialogue to control grade and grain, building a UGC library.

Pros: JSON guides light and color while character reference improves consistency; reusable workflow for batch product UGC variations.

Cons: Heavy reliance on reference images and specific models/tools; no lens, composition, or aspect-ratio guidance.

Reference image: Clearly reference-image dependent: requires product image and repeated character reference for facial consistency.

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