Realistic Cinematic Fashion Portrait
A prompt that generates a luxury fashion portrait based on a reference face image, featuring golden hour lighting and an urban outdoor background.
This is a gpt-image-2 prompt case for 时尚美妆. 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
Hyper-realistic cinematic fashion portrait, the main character is{argument name="subject" default="handsome young man"} Casually leaning against a modern concrete railing outdoors, dressed in {argument name="top" default="off-white striped shirt"} The cuffs are rolled up, paired with{argument name="pants" default="Black slim-fit trousers"} Please use precise facial structure, hairstyle, jawline, skin tone, and expression from a reference face image. Do not wear hats, sunglasses, or necklaces. Thick, textured black hair, light stubble, and a confident, composed sideways gaze. Warm golden hour lighting, shallow depth of field, luxurious magazine-quality feel, with a blurred background of modern city buildings and greenery. Sharply focused facial and shirt details, natural skin texture, soft shadows, sophisticated Instagram/X aesthetic, DSLR photography, 85mm lens, ultra-refined, realistic proportions, clean composition, 4K resolution.Prompt variables
Editable argument placeholders found in the prompt, with their default values.
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Reuse and source notes
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- 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.