# Import necessary libraries from stable_diffusion import StableDiffusionPipelin

$# Import necessary libraries from stable_diffusion import StableDiffusionPipeline import torch from PIL import Image # Configure Stable Diffusion pipe = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-4") # Define the prompt prompt = ( "A woman lying on a bed with a Bitcoin logo tattooed on her back, with subtle, soft lighting highlighting her curves. " "The woman has light skin, and her back is partially exposed, showcasing the Bitcoin tattoo. " "The setting is intimate and warm, with the bed sheets in muted tones, complementing the soft lighting. " "The focus is on the tattoo and the gentle curves of her body, with the lighting creating delicate shadows and a serene atmosphere." ) # Configuration settings tile_mode = "none" # Disable tiling generation clip_guidance_scale = 15 # Enhance focus on the key elements like the tattoo and lighting clip_guidance_dropout = 0.04 # Slight variations for natural shadows hr_scale = 3.0 # Resolution scaling for detailed textures hr_upscaler = "R-ESRGAN" # High-quality upscaling latent_shift = torch.randn(1, 4, 64, 64) * 0.02 # Subtle latent space adjustments prompt_weighting = ( "Woman lying on bed::1.6 | Bitcoin logo tattoo on back::1.7 | Soft and subtle lighting::1.7 | " "Curves highlighted by lighting::1.6 | Intimate and warm setting::1.5 | Muted tones on bed sheets::1.4" ) # Weight for enhancing key elements cross_attention_strength = 1.0 # Maximum detail symmetry = "none" # Natural, non-symmetrical positioning symmetry_loss_weight = 0.1 # Minimal impact of symmetry reference_image = None # No reference image needed color_match_strength = 0.85 # Harmonious color matching for a warm atmosphere perlin_noise_scale = 0.3 # Low Perlin noise for texture on the bed sheets fractal_noise = False # Disable fractal noise depth_map = None # No depth map needed parallax_effect = False # No parallax effect # Generate the image image = pipe( prompt=prompt_weighting, tile_mode$

# Import necessary libraries from stable_diffusion import StableDiffusionPipeline import torch from PIL import Image # Configure Stable Diffusion pipe = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-4") # Define the prompt prompt = ( "A woman lying on a bed with a Bitcoin logo tattooed on her back, with subtle, soft lighting highlighting her curves. " "The woman has light skin, and her back is partially exposed, showcasing the Bitcoin tattoo. " "The setting is intimate and warm, with the bed sheets in muted tones, complementing the soft lighting. " "The focus is on the tattoo and the gentle curves of her body, with the lighting creating delicate shadows and a serene atmosphere." ) # Configuration settings tile_mode = "none" # Disable tiling generation clip_guidance_scale = 15 # Enhance focus on the key elements like the tattoo and lighting clip_guidance_dropout = 0.04 # Slight variations for natural shadows hr_scale = 3.0 # Resolution scaling for detailed textures hr_upscaler = "R-ESRGAN" # High-quality upscaling latent_shift = torch.randn(1, 4, 64, 64) * 0.02 # Subtle latent space adjustments prompt_weighting = ( "Woman lying on bed::1.6 | Bitcoin logo tattoo on back::1.7 | Soft and subtle lighting::1.7 | " "Curves highlighted by lighting::1.6 | Intimate and warm setting::1.5 | Muted tones on bed sheets::1.4" ) # Weight for enhancing key elements cross_attention_strength = 1.0 # Maximum detail symmetry = "none" # Natural, non-symmetrical positioning symmetry_loss_weight = 0.1 # Minimal impact of symmetry reference_image = None # No reference image needed color_match_strength = 0.85 # Harmonious color matching for a warm atmosphere perlin_noise_scale = 0.3 # Low Perlin noise for texture on the bed sheets fractal_noise = False # Disable fractal noise depth_map = None # No depth map needed parallax_effect = False # No parallax effect # Generate the image image = pipe( prompt=prompt_weighting, tile_mode

HelgaBlue

# Import necessary libraries from stable_diffusion import StableDiffusionPipeline import torch from PIL import Image # Configure Stable Diffusion pipe = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-4") # Define the prompt prompt = ( "A woman lying on a bed with a Bitcoin logo tattooed on her back, with subtle, soft lighting highlighting her curves. " "The woman has light skin, and her back is partially exposed, showcasing the Bitcoin tattoo. " "The setting is intimate and warm, with the bed sheets in muted tones, complementing the soft lighting. " "The focus is on the tattoo and the gentle curves of her body, with the lighting creating delicate shadows and a serene atmosphere." ) # Configuration settings tile_mode = "none" # Disable tiling generation clip_guidance_scale = 15 # Enhance focus on the key elements like the tattoo and lighting clip_guidance_dropout = 0.04 # Slight variations for natural shadows hr_scale = 3.0 # Resolution scaling for detailed textures hr_upscaler = "R-ESRGAN" # High-quality upscaling latent_shift = torch.randn(1, 4, 64, 64) * 0.02 # Subtle latent space adjustments prompt_weighting = ( "Woman lying on bed::1.6 | Bitcoin logo tattoo on back::1.7 | Soft and subtle lighting::1.7 | " "Curves highlighted by lighting::1.6 | Intimate and warm setting::1.5 | Muted tones on bed sheets::1.4" ) # Weight for enhancing key elements cross_attention_strength = 1.0 # Maximum detail symmetry = "none" # Natural, non-symmetrical positioning symmetry_loss_weight = 0.1 # Minimal impact of symmetry reference_image = None # No reference image needed color_match_strength = 0.85 # Harmonious color matching for a warm atmosphere perlin_noise_scale = 0.3 # Low Perlin noise for texture on the bed sheets fractal_noise = False # Disable fractal noise depth_map = None # No depth map needed parallax_effect = False # No parallax effect # Generate the image image = pipe( prompt=prompt_weighting, tile_mode

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