Complex Structured Prompt for Rainy Times Square Scene with Detailed Subject Description

A highly detailed, structured JSON-like prompt designed for GPT Image 1.5 to generate a realistic, cinematic scene of a person in Times Square on a rainy night. It specifies complex elements like reflections, specific clothing details (a black faux-leather varsity jacket with embroidery), and camera aesthetics, ensuring the subject's face remains identical to an uploaded reference.

Prompt
{ "scene": { "location": "Times Square, New York", "time": "Rainy night", "composition": { "left_side": [ { "type": "LED billboard", "style": "vertical", "text_color": "white-on-black" }, { "type": "curved LED screen", "detail": "above yellow arrow for Hershey's store" } ], "right_side": { "subject_position": "near curb", "traffic": { "vehicles": "city taxis and cars", "details": "brake lights forming a slow line" } } }, "environment": { "ground": "wet asphalt", "reflection_colors": ["neon magenta", "icy blue"], "puddles": { "reflecting_lights": true, "object_details": ["scattered takeaway cups"] }, "atmosphere": ["electric", "intimate"] } }, "subject": { "identity": "Uploaded subject", "face_requirement": "Do not change facial features. Must look 1000% identical.", "pose": "Relaxed, facing camera", "holding": "Folded black umbrella by handle", "outfit": { "jacket": { "material": "black faux-leather varsity", "design": { "cobalt_panel": true, "cream_stripe": true, "embroidery": "Vintage script", "lettering": "Block OF", "patch": "1987 stitched on sleeve", "reflective_piping": true, "highlight_color": "purple reflection" } } } }, "background": { "elements": ["cars", "scaffolding", "stacked storefront signs"] }, "style": { "resolution": "HD", "aesthetic": ["realistic", "natural", "authentic"], "camera": "iPhone" } }

How to use this prompt

  1. 1

    Copy the full prompt above.

  2. 2

    Open a platform that supports GPT Image 1.5, such as YouMind, and paste the prompt in.

  3. 3

    Swap the subject, style, or details to fit your idea, then generate.

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