Casual fashion lookbook poster prompt
Creates a scrapbook-style poster suggesting 10 types of casual clothing for a subject, maintaining facial structure from a reference photo.
This is a gpt-image-2 prompt case for Fashion & Beauty. Use the copy-ready prompt below to generate similar visuals, and review YouMind OpenLab awesome-gpt-image-2 attribution plus commercial-use rights before reuse.
Prompt
Copy-ready prompt
For the person in the attached image, please find 10 suitable casual and fashionable outfits. Each outfit should be presented as a whole, but the person's pose, expression, and facial features should differ from the original image, while maintaining facial structure consistency. These 10 outfits should be distinguished by different poses and expressions to ensure the overall pose, expression, and clothing type do not appear monotonous or stiff. Additionally, please provide 10 suggestions for casual clothing that are not recommended for this person. The poster should use a portrait-sized scrapbook style, with a precise, clean, and orderly layout. The poster's visual effect should not appear stiff or monotonous, placing the person in the reference photo in the main position. The arrangement of the person's face and clothing in the attached image must not be altered. The poster should be 8K resolution. The face and body must be completely identical to the uploaded image.
Reuse and source notes
Use this prompt safely after previewing the case.
- 1.Copy the prompt or open it directly in Dovoo with the generation button.
- 2.Adjust variables, aspect ratio, and reference images for your own use case.
- 3.Before publishing or paid usage, verify source rights, attribution requirements, and brand or likeness risks.
Can I use this prompt commercially?
Commercial-use status is unknown. Review the original source, license, brand constraints, and legal requirements before paid usage.
Where does this case come from?
This case is imported from YouMind OpenLab awesome-gpt-image-2; keep attribution visible and check the source URL before reuse.