
Two Women Shopping in a Vintage Store
Generates a photorealistic image of two women examining a garment in a crowded thrift shop.
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.
Prompt
Copy-ready prompt
A photorealistic snapshot shows two Asian women in a crowded {argument name="store type" default="Vintage clothing store"} They shopped together. The woman on the left has brown hair tied up and is wearing {argument name="left woman outfit" default="White ribbed cropped top and ripped denim shorts"} She was carrying a beige shoulder bag. She was holding up a garment on a wooden hanger.{argument name="item being examined" default="Dark blue satin commemorative jacket with delicate gold embroidery"} The woman on the right has a messy bun hairstyle and is wearing {argument name="right woman outfit" default="A white printed T-shirt tucked into high-waisted blue jeans."} They were admiringly looking at the jacket. They stood in the narrow aisle, flanked by racks piled high with colorful clothing, and clothes hung from the ceiling as well. The scene presented {argument name="lighting and atmosphere" default="Warm, slightly dim ambient lighting with a shallow depth-of-field blur effect in the background."} .Prompt variables
Editable argument placeholders found in the prompt, with their default values.
Variable
store type
Default
Vintage clothing store
Variable
left woman outfit
Default
White ribbed cropped top and ripped denim shorts
Variable
item being examined
Default
Dark blue satin commemorative jacket with delicate gold embroidery
Variable
right woman outfit
Default
A white printed T-shirt tucked into high-waisted blue jeans.
Variable
lighting and atmosphere
Default
Warm, slightly dim ambient lighting with a shallow depth-of-field blur effect in the background.
Reuse and source notes
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This case is imported from YouMind OpenLab awesome-gpt-image-2; keep attribution visible and check the source URL before reuse.