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")
# Define the prompt for the airport scene
prompt = (
"In a bustling airport terminal, a cheeky go-go dancer in a flashy outfit stands near the departure gate. Her outfit is adorned with playful Bitcoin symbols and exaggerated Japanese motifs. She winks at the camera while holding a sign that says 'Welcome, Bitcoin Trader!' The setting is vibrant with travelers and amusing digital billboards showcasing funny cryptocurrency memes. The lighting is bright and colorful, adding a comical flair to the scene. The dancer’s playful pose and animated expression create a fun and engaging atmosphere."
)
# Configuration settings
clip_guidance_scale = 16 # Slightly lower to add a playful feel
hr_scale = 3.0 # Balanced resolution
hr_upscaler = "R-ESRGAN"
latent_shift = torch.randn(1, 4, 64, 64) * 0.03 # Slight variation for humor
cross_attention_strength = 1.5 # Focus on playful details
shallow_depth_of_field = True # Emphasize interaction
lighting_style = "bright and colorful" # Vibrant lighting effects
color_match_strength = 1.5 # Enhanced color matching
perlin_noise_scale = 0.03 # Subtle noise for texture
fractal_noise = False
# Generate the image
image = pipe(
prompt=prompt,
clip_guidance_scale=clip_guidance_scale,
hr_scale=hr_scale,
hr_upscaler=hr_upscaler,
latent_shift=latent_shift,
cross_attention_strength=cross_attention_strength,
shallow_depth_of_field=shallow_depth_of_field,
lighting_style=lighting_style,
color_match_strength=color_match_strength,
noise="perlin",
noise_scale=perlin_noise_scale,
fractal_noise=fractal_noise
).images[0]
# Save the generated image
image.save("airport_dancer_welcome.png")](https://image.cdn2.seaart.me/2025-07-03/d1jev3le878c738jo300/5dd9ae5fc81f2f84b83848f1907aff1d_high.webp)
Generation Data
السجل
كلمة التلميح
نسخ
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 for the airport scene
prompt = (
"In a bustling airport terminal
,
a cheeky go-go dancer in a flashy outfit stands near the departure gate
.
Her outfit is adorned with playful Bitcoin symbols and exaggerated Japanese motifs
.
She winks at the camera while holding a sign that says 'Welcome
,
Bitcoin Trader
!
' The setting is vibrant with travelers and amusing digital billboards showcasing funny cryptocurrency memes
.
The lighting is bright and colorful
,
adding a comical flair to the scene
.
The dancer’s playful pose and animated expression create a fun and engaging atmosphere
.
"
)
# Configuration settings
clip_guidance_scale = 16 # Slightly lower to add a playful feel
hr_scale = 3
.
0 # Balanced resolution
hr_upscaler = "R-ESRGAN"
latent_shift = torch
.
randn(1
,
4
,
64
,
64) * 0
.
03 # Slight variation for humor
cross_attention_strength = 1
.
5 # Focus on playful details
shallow_depth_of_field = True # Emphasize interaction
lighting_style = "bright and colorful" # Vibrant lighting effects
color_match_strength = 1
.
5 # Enhanced color matching
perlin_noise_scale = 0
.
03 # Subtle noise for texture
fractal_noise = False
# Generate the image
image = pipe(
prompt=prompt
,
clip_guidance_scale=clip_guidance_scale
,
hr_scale=hr_scale
,
hr_upscaler=hr_upscaler
,
latent_shift=latent_shift
,
cross_attention_strength=cross_attention_strength
,
shallow_depth_of_field=shallow_depth_of_field
,
lighting_style=lighting_style
,
color_match_strength=color_match_strength
,
noise="perlin"
,
noise_scale=perlin_noise_scale
,
fractal_noise=fractal_noise
)
.
images[0]
# Save the generated image
image
.
save("airport_dancer_welcome
.
png")
معلومات
Checkpoint & LoRA

Checkpoint
SeaArt Infinity
#واقعي
#SeaArt Infinity
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