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Cinematic Urban Night Portrait - Moody Streetwear Aesthetic

{ "scene_setup": { "subject": { "clothing": "wearing a black oversized hoodie, black backwards baseball cap, silver chain neckla…

Role-Based

Prompt

{
  "scene_setup": {
    "subject": {
      "clothing": "wearing a black oversized hoodie, black backwards baseball cap, silver chain necklace",
      "appearance": "male model, beard, intense serious gaze, masculine features",
      "pose": "sitting or leaning forward, looking down at camera, authoritative stance"
    },
    "camera_angle": {
      "type": "Low angle shot",
      "focus": "Sharp focus on face, shallow depth of field (bokeh background)",
      "framing": "Medium close-up portrait"
    },
    "environment": {
      "location": "Urban street at night, under a concrete bridge or overpass",
      "background_elements": "blurred city lights, bokeh skyscrapers, a car with headlights on in the background",
      "ground": "wet asphalt, rain reflections"
    },
    "lighting_and_fx": {
      "style": "Cinematic moody lighting, high contrast",
      "colors": "Teal and orange color grading, warm street lights vs dark blue sky",
      "effects": "Smoke or steam rising in the foreground, volumetric lighting"
    },
    "technical": {
      "quality": "Photorealistic, 8k resolution, raw photo style, highly detailed texture",
      "engine": "Unreal Engine 5 render style or high-end photography"
    }
  }
}
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How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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