# 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 prompt = ( "A dynamic and sensitive scene in a cozy home: A woman in a white oversized men's shirt, barely covering her hips, with one shoulder exposed. " "Her hair is braided into a single braid, with a Bitcoin-shaped hairpin. She is barefoot, relaxed, with a slightly worn appearance, " "playing bowling at home with a bowling ball featuring a Bitcoin symbol. Her eyes are blue, her nose is large, and her lips are narrow. " "Her nipples are visible through the shirt. On the table, there is spilled milk, and some milk is left on her lips. " "The setting is warm and intimate, with soft natural light coming through the windows, reflecting the emotional and physical warmth of the moment. " "The overall atmosphere is lively, with a touch of playful spontaneity." ) # Configuration settings clip_guidance_scale = 20 # Stronger adherence to the description for dynamic and emotional elements hr_scale = 2.5 # High resolution for detailed output hr_upscaler = "R-ESRGAN" # High-quality upscaling method latent_shift = torch.randn(1, 4, ??, ??) * 0.015 # Slightly more variation in the latent space for a natural, lively look prompt_weighting = ( "Woman in oversized shirt::2.2 | Bitcoin hairpin::1.9 | Relaxed and lively atmosphere::2.0 | Bowling at home with Bitcoin symbol::1.9 | " "Blue eyes, large nose, narrow lips::1.7 | Spilled milk::1.6 | Cozy home with natural light::2.1" ) # Enhanced focus on key elements to create a dynamic and sensitive scene cross_attention_strength = 1.2 # Enhanced focus on dynamic elements symmetry = "none" # No symmetry for a natural composition symmetry_loss_weight = 0.05 # Minimal influence of symmetry color_match_strength = 0.9 # Harmonious color blending to enhance war