
Uncanny Thanksgiving Family Dinner
A realistic vintage Thanksgiving dinner scene with anonymized faces, pets, and nostalgic domestic details for creating eerie family-photo imagery.
This is a GPT Image 2 prompt case for Portrait & Character. Use the copy-ready prompt below to generate similar visuals, and review Awesome GPT Image 2 Prompts attribution plus commercial-use rights before reuse.
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Prompt
Copy-ready prompt
Create a chilling and photorealistic 1970s American Thanksgiving family dinner scene, set in a warm, dimly lit dining room, using a documentary-style, candid photography approach with a slightly wide-angle 4:3 composition. The scene should feature 9 people seated around a round table: on the far left is an adult man in a white shirt, next to him is an adult woman, followed by an adult man in a white shirt and tie, in the middle is a middle-aged woman, to the right are two little girls in simple dresses, and there's an elderly man in a dark suit, an elderly woman in a floral dress, and a young boy with his back to the camera in the foreground. Process all visible faces into eerily smoothed, square blurs or featureless obscuring blocks, rather than normal facial features, while maintaining a high degree of realism in bodies, clothing, hairstyles, and the room. The table is covered with a white lace tablecloth and laden with a Thanksgiving feast: a large roast turkey is centered, surrounded by mashed potatoes, green beans, cranberry sauce, basket-filled rolls, stuffing or casserole dishes, gravy, plates, glasses, silver cutlery, and small serving bowls. The scene should include 3 animals: a tabby cat sitting on a small chair in the lower left corner, a German Shepherd lying on the floor in the foreground, and a hound dog standing in the kitchen doorway on the right. The room is decorated with beige floral wallpaper, a window with lace curtains on the left, and a wooden china cabinet in the back filled with plates and glassware, decorated with autumn harvest ornaments, with framed pictures on the walls, a black cross on the right wall, and a glimpse of an old-fashioned wooden kitchen through the doorway. The color palette should be soft browns, creams, and ambers, with realistic film grain, soft incandescent indoor lighting, subtle lens softness, creating an unsettling uncanny valley atmosphere. The image should contain no readable text, no modern items, and no watermarks except for a blurred, pixelated mark in the lower right corner. Optional customizations: set the holiday meal {argument name="holiday meal" default="Thanksgiving dinner"}, set the era {argument name="era" default="1970s"}, change the room style {argument name="room style" default="Old-fashioned American diner"}, adjust the facial processing {argument name="face treatment" default="All visible faces are covered with smooth, square blur blocks"}, and set the atmosphere {argument name="mood" default="Photorealistic but extremely unsettling"}.Prompt variables
Editable argument placeholders found in the prompt, with their default values.
Best for
- - Portrait & Character visual exploration
- - Image generation and reference-image edits
- - Reusable briefs that keep source attribution visible
Change these parts
- - Subject, product, character, or scene
- - Aspect ratio, camera, lighting, and background
- - Brand, text, color, and output constraints
Recommended model and settings
- - Model: gpt-image-2
- - Input mode: Text to Image
- - Aspect ratio: source
- - Commercial status: review original source
How to use this prompt
- 1. Copy the prompt and preserve its structure for the first test.
- 2. Replace the subject, context, and publishing channel.
- 3. Change one camera, lighting, or style variable per iteration.
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Limitations, source, and reuse cautions
- - Generated output is an editable draft, not factual, legal, or rights evidence.
- - Review the linked source, people, brands, logos, text, and third-party media before commercial use.
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Commercial-use status is allowed. Review the original source, license, brand constraints, and legal requirements before paid usage.
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