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Cinematic Surveillance Interface Aesthetic preview image
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Cinematic Surveillance Interface Aesthetic

Generates a monochrome CCTV-style surveillance shot of a person of interest in a crowd, complete with digital UI overlays and motion blur.

This is a gpt-image-2 prompt case for Portrait & Character. 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.

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Prompt

Copy-ready prompt

A CCTV-style surveillance video, taken from above.{argument name="location" default="Crowded street scene"} The person in the center of the picture{argument name="subject" default="young man"} She is walking forward and looking up at the camera, giving a warm and friendly smile, while the surrounding pedestrians are blurred.{argument name="color tone" default="Black and white monochrome"} The surrounding crowd exhibits strong motion blur, while the main subject remains clearly in focus, creating a dramatic contrast. A top-down perspective is used, and an AI facial recognition interface overlay is employed. The woman is surrounded by a green border labeled "PERSON OF INTEREST." A sidebar displays an enlarged facial portrait and data text: "SUBJECT ID: 01," "STATUS: TRACKED," "GAZE: UP," and "CONFIDENCE: 86%." A connecting line exists between the facial panel and the main subject. A timestamp is overlaid in the corner, along with a "REC" indicator light. The design features grainy textures, digital noise, compression artifacts, subtle scan lines, cinematic surveillance aesthetics, a documentary style, slightly distorted perspective, an urban environment, and dynamic composition.

Prompt variables

Editable argument placeholders found in the prompt, with their default values.

3
Variable
location
Default
Crowded street scene
Variable
subject
Default
young man
Variable
color tone
Default
Black and white monochrome

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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.