# Import necessary libraries from stable_diffusion import StableDiffusionPipelin

$# Import necessary libraries from stable_diffusion import StableDiffusionPipeline import torch from PIL import Image # Configure Stable Diffusion pipe = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-4") # Define the prompt prompt = ( "A close-up of a woman's lips biting a Bitcoin coin, with a provocative look in her eyes. " "The image focuses on the lips and the Bitcoin coin, capturing the texture of the lips and the metallic sheen of the coin. " "The woman's eyes are slightly visible above the lips, showing a seductive, intense gaze. " "The lighting is soft but focused, highlighting the curves of the lips and the reflective surface of the Bitcoin. " "The background is blurred, ensuring the attention remains on the lips, coin, and eyes." ) # Configuration settings tile_mode = "none" # Disable tiling generation clip_guidance_scale = 15 # Enhance adherence to the prompt details clip_guidance_dropout = 0.05 # Subtle variations for realism hr_scale = 3.0 # High-resolution scaling for detailed textures hr_upscaler = "R-ESRGAN" # High-quality upscaling latent_shift = torch.randn(1, 4, 64, 64) * 0.02 # Subtle latent space adjustments prompt_weighting = ( "Close-up of lips::1.7 | Biting a Bitcoin coin::1.6 | Provocative look in eyes::1.7 | Soft but focused lighting::1.5 | Metallic sheen on Bitcoin::1.6 | " "Blurred background::1.5 | Seductive, intense gaze::1.7" ) # Weight for enhancing key elements cross_attention_strength = 1.0 # Maximum detail for lips, coin, and eyes symmetry = "none" # No symmetry to maintain a natural expression symmetry_loss_weight = 0.1 # Minimal impact of symmetry reference_image = None # No reference image needed color_match_strength = 0.85 # Harmonious blending perlin_noise_scale = 0.1 # Low Perlin noise for subtle texture fractal_noise = False # Disable fractal noise depth_map = None # No depth map needed parallax_effect = False # No parallax effect # Generate the image image = pipe($

# 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 close-up of a woman's lips biting a Bitcoin coin, with a provocative look in her eyes. " "The image focuses on the lips and the Bitcoin coin, capturing the texture of the lips and the metallic sheen of the coin. " "The woman's eyes are slightly visible above the lips, showing a seductive, intense gaze. " "The lighting is soft but focused, highlighting the curves of the lips and the reflective surface of the Bitcoin. " "The background is blurred, ensuring the attention remains on the lips, coin, and eyes." ) # Configuration settings tile_mode = "none" # Disable tiling generation clip_guidance_scale = 15 # Enhance adherence to the prompt details clip_guidance_dropout = 0.05 # Subtle variations for realism hr_scale = 3.0 # High-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 = ( "Close-up of lips::1.7 | Biting a Bitcoin coin::1.6 | Provocative look in eyes::1.7 | Soft but focused lighting::1.5 | Metallic sheen on Bitcoin::1.6 | " "Blurred background::1.5 | Seductive, intense gaze::1.7" ) # Weight for enhancing key elements cross_attention_strength = 1.0 # Maximum detail for lips, coin, and eyes symmetry = "none" # No symmetry to maintain a natural expression symmetry_loss_weight = 0.1 # Minimal impact of symmetry reference_image = None # No reference image needed color_match_strength = 0.85 # Harmonious blending perlin_noise_scale = 0.1 # Low Perlin noise for subtle texture fractal_noise = False # Disable fractal noise depth_map = None # No depth map needed parallax_effect = False # No parallax effect # Generate the image image = pipe(

Generation Data

履歴

# 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 close-up of a woman's lips biting a Bitcoin coin , with a provocative look in her eyes . " "The image focuses on the lips and the Bitcoin coin , capturing the texture of the lips and the metallic sheen of the coin . " "The woman's eyes are slightly visible above the lips , showing a seductive , intense gaze . " "The lighting is soft but focused , highlighting the curves of the lips and the reflective surface of the Bitcoin . " "The background is blurred , ensuring the attention remains on the lips , coin , and eyes . " ) # Configuration settings tile_mode = "none" # Disable tiling generation clip_guidance_scale = 15 # Enhance adherence to the prompt details clip_guidance_dropout = 0 . 05 # Subtle variations for realism hr_scale = 3 . 0 # High-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 = ( "Close-up of lips::1 . 7 | Biting a Bitcoin coin::1 . 6 | Provocative look in eyes::1 . 7 | Soft but focused lighting::1 . 5 | Metallic sheen on Bitcoin::1 . 6 | " "Blurred background::1 . 5 | Seductive , intense gaze::1 . 7" ) # Weight for enhancing key elements cross_attention_strength = 1 . 0 # Maximum detail for lips , coin , and eyes symmetry = "none" # No symmetry to maintain a natural expression symmetry_loss_weight = 0 . 1 # Minimal impact of symmetry reference_image = None # No reference image needed color_match_strength = 0 . 85 # Harmonious blending perlin_noise_scale = 0 . 1 # Low Perlin noise for subtle texture fractal_noise = False # Disable fractal noise depth_map = None # No depth map needed parallax_effect = False # No parallax effect # Generate the image image = pipe(

情報

サイズ

688X1024

日付

Aug 23, 2024

モード

スタジオ

タイプ

cell

Checkpoint & LoRA

SeaArt Infinity

SeaArt Infinity

#SeaArt Infinity

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