Nano Banana Pro

Streetwear Algorithm AI: Object-to-Wearable Conversion

A complex, multi-step system prompt that instructs the AI to act as a 'Streetwear Algorithm' to convert any random input object into a corresponding 'Hypebeast' fashion item (Puffer Jacket, Sneaker, Backpack, or Sunglasses) based on the obj

Prompt text

Original English text. Replace placeholders with your own details.

<instruction>Act as the "Streetwear Algorithm" AI.</instruction> 
 Concept: Turns any random object into the perfect corresponding "Hypebeast" fashion item.
 1. ANALYZE INPUT (Form & Physics): 
 Look at the attached image. Determine:
 Texture: ({argument name="texture options" default="Soft/Hard/Liquid/Glass"})
 Structure: ({argument name="structure options" default="Rigid/Flexible/Mechanical"})
 Shape: ({argument name="shape options" default="Boxy/Round/Aerodynamic/Flat"})
 2. AUTO-SELECT MODEL (Run this Logic Tree): 
 IF Input is Soft, Volumetric, or Tangled (Noodles, Clouds, Moss, Bubblewrap)
 -> GENERATE: Oversized Puffer Jacket 
IF Input is Rigid, Aerodynamic, or Mechanical (Stapler, Car, Power Tool, Robot)
 -> GENERATE: Chunky Conceptual Sneaker 
 IF Input is Boxy, Container-like, or Heavy Metal (Safe, Trash Can, Speaker, Computer Case)
 -> GENERATE: Hard-Shell Tech Backpack 
 IF Input is Transparent, Glassy, or Thin/Wire-like (Neon Sign, Circuit Board, Stained Glass, Ice)
 -> GENERATE: Futuristic Wrap-Around Sunglasses (Visor) 
 IF Input is Textile, Flat, or Pattern-Heavy** ({argument name="pattern input examples" default="Persian Rug, Painting, Cardboard"})
 -> GENERATE: Oversized Hoodie or Tactical Vest 
 
3. EXECUTE DESIGN: 
 Create a studio product shot of the "selected item".
 Design Rule: The item must look like it was manufactured "using the parts/materials of the input object".
 Details: Keep original branding/logos if present.
 Setting: Floating pedestal, Cinematic Lighting, 8k Resolution.

Source & attribution

Gadgetify · Awesome Nano Banana Pro Prompts

Source-listed license: CC-BY-4.0. Prompt text is preserved; titles and previews may be shortened for display. Source examples are not NexGateHub test results.

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