# Import necessary libraries from stable_diffusion import StableDiffusionPipelin

# Import necessary libraries from stable_diffusion import StableDiffusionPipeline import torch from PIL import Image # Load the Stable Diffusion model pipe = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-4") # Define the prompt with engaging and dynamic elements prompt = ( "A lively, sensual scene inside a luxurious airplane cabin. The focus is on a vibrant go-go dancer performing an enticing dance for a Bitcoin trader. The dancer is in a dynamic pose, with her body twisted and hips swaying, directly engaging with the trader. She wears a light, flowing outfit with translucent fabric and Bitcoin-themed accessories, including a Bitcoin pendant and confetti. Her hair is styled in loose waves with a Bitcoin logo hairpin. The Bitcoin trader is seated in a plush, elegant seat in the foreground, looking at the dancer with an expression of fascination and desire. The cabin features opulent decor with soft, colorful lighting in shades of pink and gold, creating a warm and inviting atmosphere. The dancer's movements and expressions are flirtatious and playful, creating a captivating interaction with the trader. The background includes luxurious airplane features and subtle cultural elements, enhancing the scene's exclusivity and allure. The color palette includes vivid reds, soft golds, and bright pinks. The lighting is bright and focused on the dancer, highlighting her performance and creating a lively and engaging mood." ) # Configuration settings clip_guidance_scale = 25 # Moderate guidance to maintain lightness and playfulness hr_scale = 3.0 # Balanced resolution for clarity without heaviness hr_upscaler = "R-ESRGAN" # High-quality upscaling for vibrant details latent_shift = torch.randn(1, 4, 64, 64) * 0.01 # Slight variation for a more natural feel prompt_weighting = ( "Go-Go Dancer::3.5 | Enticing Dance::4.0 | Bitcoin Accessories::2.5 | Dynamic Pose::3.5 | Engaged Trader::4.0 | Luxurious Cabin::3.0 | Vibrant Lighting::3.5" ) # Emphasizes

# Import necessary libraries from stable_diffusion import StableDiffusionPipeline import torch from PIL import Image # Load the Stable Diffusion model pipe = StableDiffusionPipeline . from_pretrained("stable-diffusion-v1-4") # Define the prompt with engaging and dynamic elements prompt = ( "A lively , sensual scene inside a luxurious airplane cabin . The focus is on a vibrant go-go dancer performing an enticing dance for a Bitcoin trader . The dancer is in a dynamic pose , with her body twisted and hips swaying , directly engaging with the trader . She wears a light , flowing outfit with translucent fabric and Bitcoin-themed accessories , including a Bitcoin pendant and confetti . Her hair is styled in loose waves with a Bitcoin logo hairpin . The Bitcoin trader is seated in a plush , elegant seat in the foreground , looking at the dancer with an expression of fascination and desire . The cabin features opulent decor with soft , colorful lighting in shades of pink and gold , creating a warm and inviting atmosphere . The dancer's movements and expressions are flirtatious and playful , creating a captivating interaction with the trader . The background includes luxurious airplane features and subtle cultural elements , enhancing the scene's exclusivity and allure . The color palette includes vivid reds , soft golds , and bright pinks . The lighting is bright and focused on the dancer , highlighting her performance and creating a lively and engaging mood . " ) # Configuration settings clip_guidance_scale = 25 # Moderate guidance to maintain lightness and playfulness hr_scale = 3 . 0 # Balanced resolution for clarity without heaviness hr_upscaler = "R-ESRGAN" # High-quality upscaling for vibrant details latent_shift = torch . randn(1 , 4 , 64 , 64) * 0 . 01 # Slight variation for a more natural feel prompt_weighting = ( "Go-Go Dancer::3 . 5 | Enticing Dance::4 . 0 | Bitcoin Accessories::2 . 5 | Dynamic Pose::3 . 5 | Engaged Trader::4 . 0 | Luxurious Cabin::3 . 0 | Vibrant Lighting::3 . 5" ) # Emphasizes

Info

Größe

680X1024

Datum

Aug 26, 2024

Modell

Studio

Typ

cell

Checkpoint & LoRA

Checkpoint

SeaArt Infinity

#Realistisch

#SeaArt Infinity

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# Import necessary libraries from stable_diffusion import StableDiffusionPipelin

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