Spaces:
Running
Running
File size: 2,123 Bytes
12aadac 8933eda 12aadac 8933eda 12aadac 22f10ca 12aadac 22f10ca 12aadac 22f10ca 12aadac 22f10ca 12aadac 22f10ca 12aadac |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
import gradio as gr
import spaces
from panna import SDXLTurboImg2Img
model = SDXLTurboImg2Img(device_name="cpu")
title = "# Stable Diffusion 2 XL Turbo Image2Image"
examples = [
"A female model, high quality, fashion, Paris, Vogue, Maison Margiela, 8k",
]
css = """
#col-container {
margin: 0 auto;
max-width: 580px;
}
"""
@spaces.GPU
def infer(prompt, negative_prompt, image, noise_scale_latent_image, noise_scale_latent_prompt):
return model(
image=image,
prompt=prompt,
noise_scale_latent_image=noise_scale_latent_image,
noise_scale_latent_prompt=noise_scale_latent_prompt,
negative_prompt=negative_prompt,
seed=42
)
with gr.Blocks(css=css) as demo:
with gr.Column(elem_id="col-container"):
gr.Markdown(title)
with gr.Row():
prompt = gr.Text(
label="Prompt", show_label=False, max_lines=1, placeholder="Enter your prompt", container=False
)
with gr.Row():
negative_prompt = gr.Text(
label="Negative Prompt", show_label=False, max_lines=1, placeholder="Enter a negative prompt", container=False, value="low quality, blurr",
)
with gr.Row():
noise_scale_latent_image = gr.Slider(
minimum=0, maximum=5, step=0.05, value=0, label='noise scale (latent image)'
)
with gr.Row():
noise_scale_latent_prompt = gr.Slider(
minimum=0, maximum=5, step=0.05, value=0, label='noise scale (latent prompt)'
)
with gr.Row():
run_button = gr.Button("Run", scale=0)
with gr.Row():
image = gr.Image(label="Input Image", type='pil')
result = gr.Image(label="Result", show_label=False)
gr.Examples(examples=examples, inputs=[prompt])
gr.on(
triggers=[run_button.click, prompt.submit, negative_prompt.submit],
fn=infer,
inputs=[prompt, negative_prompt, image, noise_scale_latent_image, noise_scale_latent_prompt],
outputs=[result]
)
demo.launch(server_name="0.0.0.0")
|