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Cinematic Paper-Tear Double Exposure Portrait

Cinematic Paper-Tear Double Exposure Portrait

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Create a vertical cinematic double-exposure paper-tear collage portrait of {argument name="character description" default="a beautiful young South Asian woman"}. The composition shows one full-body woman walking forward in the lower center on a rain-soaked city street at dusk, wearing an elegant {argument name="outfit" default="teal embroidered South Asian salwar kameez with gold embellishments, matching dupatta, wide trousers, gold sandals, necklace, and ornate gold jhumka earrings"}. Behind her, fill the upper two-thirds with a huge ethereal close-up portrait of the same woman, softly blended into the background; preserve long silky dark hair parted to one side, warm medium-brown skin tone, delicate jewelry, and a serene fashion-editorial presence. Add a torn white paper edge running diagonally across the image from lower left to mid-right, separating the giant portrait above from the street scene below, with realistic fibrous paper texture and shadow. Background: {argument name="location" default="an atmospheric wet urban boulevard with blurred streetlights and warm golden bokeh"}, shallow depth of field, reflective pavement, misty rain haze, amber highlights, soft overcast sky. Style: high-quality cinematic photorealism, fashion magazine editorial, romantic moody lighting, 85mm lens look, creamy bokeh, subtle film grain, detailed embroidery and fabric texture, dramatic scale contrast between the close-up face and the small full-body figure. Constraints: no text, no logos, no watermark, no extra people, keep exactly 1 full-body walking figure and exactly 1 giant background close-up portrait, maintain realistic anatomy and natural fabric drape.

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How to use this prompt

Copy the prompt and paste it into GPT Image 2. Keep the composition, lighting and style terms as written — they are what produced this result. Swap the subject or scene details to make it yours, keep the aspect ratio, and attach the reference images the prompt mentions if any. Regenerate two or three times; the strongest version is usually not the first.