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Generate Your Own Carols by Candlelight Images

Create your own heartwarming 'Carols by Candlelight' images with our AI image generator. It's free and easy!

Carols by Candlelight: Hyperdetailed Christmas Scene
Carols by Candlelight: Hyperdetailed Christmas Scene
3 years ago

Carols by Candlelight

Created 3 years ago · 0 comments· 0 likes

Stable Diffusion 1.5

Vincent's Avatar
Creation Summary by Vincent

Carols by Candlelight: Hyperdetailed Christmas Scene

This image shows a crowd of people in Santa hats singing carols at an outdoor Christmas event. The scene is depicted with dynamic lighting and intricate detail, in a modern fantasy art style.

Created by RandomlyGeneratedName on Dec 24, 2022 using the Stable Diffusion 1.5 AI image generator model.


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Creation Settings

Text Prompts
Vision Australia's Carols by Candlelight, photography, intricate and hyperdetailed painting by Ismail Inceoglu Huang Guangjian and Dan Witz CGSociety ZBrush Central fantasy art album cover art 4K 64 megapixels 8K resolution HDR" Australian Performers at Christmas
Weight: 2.5
A crowd of people wearing santa hats singing carols, head and shoulders portraits, 8k resolution concept art portrait by Greg Rutkowski, Artgerm, WLOP, Alphonse Mucha dynamic lighting hyperdetailed intricately detailed Splash art trending on Artstation triadic colors Unreal Engine 5 volumetric lighting, ...
Weight: 1.1
At the Sindey Myer Music Bowl in Melbourne Australia 8k resolution concept art by Greg Rutkowski dynamic lighting hyperdetailed intricately detailed Splash art trending on Artstation triadic colors Unreal Engine 5 volumetric lighting Alphonse Mucha WLOP Jordan Grimmer orange and teal
Weight: 0.6
ugly, tiling, poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, blurry, bad anatomy, blurred, watermark, grainy, signature, cut off, draft, red suit, Santa suit
Weight: -0.3
Model
Stable Diffusion 1.5
CKPT

Stable Diffusion 1.5

Initial Resolution

Thumb

Aspect Ratio

16:9

Runtime

Short

Overall Prompt Weight

90%

Sampling method

K_LMS


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