From stable_diffusion import StableDiffusionPipeline import torch from PIL impor

$from stable_diffusion import StableDiffusionPipeline import torch from PIL import Image # Load the Stable Diffusion model pipe = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-4") pipe = pipe.to("cuda") # Use GPU if available # Define the prompt for Mezo Honey Badger prompt_honey_badger = ( "A humorous depiction of a honey badger representing Bitcoin's strength, resilience, and toughness in the world of Mezo. " "The honey badger is wearing Bitcoin-themed sunglasses and sitting on a throne of Bitcoin coins, with a playful smirk. " "The background features dynamic DeFi elements and Bitcoin symbols." ) # Configuration settings clip_guidance_scale = 20 # Strong guidance for focus hr_scale = 4.0 # High-resolution scaling hr_upscaler = "R-ESRGAN" # High-quality upscaling latent_shift = torch.randn(1, 4, 64, 64) * 0.02 # Subtle variation for dynamic effect shallow_depth_of_field = True # Shallow depth of field for subject focus lighting_style = "modern and bright" # Modern lighting effects color_match_strength = 1.5 # Balanced color matching noise_scale = 0.02 # Noise level for texture fractal_noise = True # Adds fractal noise for enhanced texture # Generate the image for Mezo Honey Badger image_honey_badger = pipe( prompt=prompt_honey_badger, clip_guidance_scale=clip_guidance_scale, hr_scale=hr_scale, hr_upscaler=hr_upscaler, latent_shift=latent_shift, shallow_depth_of_field=shallow_depth_of_field, lighting_style=lighting_style, color_match_strength=color_match_strength, noise="perlin", noise_scale=noise_scale, fractal_noise=fractal_noise ).images[0] # Save the generated image filename_honey_badger = "mezo_honey_badger.png" image_honey_badger.save(filename_honey_badger) print(f"Saved image: {filename_honey_badger}")$