graphics / app.py
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import gradio as gr
import spaces
import numpy as np
import random
import torch
from diffusers import StableDiffusion3Pipeline
# Set device and data type
device = "cuda" if torch.cuda.is_available() else "cpu"
dtype = torch.float16
# Load the Stable Diffusion model
repo = "stabilityai/stable-diffusion-3-medium-diffusers"
pipe = StableDiffusion3Pipeline.from_pretrained(repo, torch_dtype=dtype).to(device)
# Constants
MAX_SEED = np.iinfo(np.int32).max
MAX_IMAGE_SIZE = 1344
@spaces.GPU
def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, progress=gr.Progress(track_tqdm=True)):
if randomize_seed:
seed = random.randint(0, MAX_SEED)
generator = torch.Generator().manual_seed(seed)
try:
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
guidance_scale=guidance_scale,
num_inference_steps=num_inference_steps,
width=width,
height=height,
generator=generator
).images[0]
return image, seed
except Exception as e:
return str(e), seed # Return error message if any
# Example prompts
examples = [
"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
"An astronaut riding a green horse",
"A delicious ceviche cheesecake slice",
]
css = """
#col-container {
margin: 0 auto;
max-width: 580px;
}
"""
# Create Gradio interface
with gr.Blocks(css=css) as demo:
with gr.Column(elem_id="col-container"):
gr.Markdown(f"""
# Demo [Stable Diffusion 3 Medium](https://huggingface.co/stabilityai/stable-diffusion-3-medium)
Learn more about the [Stable Diffusion 3 series](https://stability.ai/news/stable-diffusion-3). Try on [Stability AI API](https://platform.stability.ai/docs/api-reference#tag/Generate/paths/~1v2beta~1stable-image~1generate~1sd3/post), [Stable Assistant](https://stability.ai/stable-assistant), or on Discord via [Stable Artisan](https://stability.ai/stable-artisan). Run locally with [ComfyUI](https://github.com/comfyanonymous/ComfyUI) or [diffusers](https://github.com/huggingface/diffusers)
""")
with gr.Row():
prompt = gr.Text(
label="Prompt",
show_label=False,
max_lines=1,
placeholder="Enter your prompt",
container=False,
)
run_button = gr.Button("Run", scale=0)
result = gr.Image(label="Result", show_label=False)
with gr.Accordion("Advanced Settings", open=False):
negative_prompt = gr.Text(
label="Negative prompt",
max_lines=1,
placeholder="Enter a negative prompt",
)
seed = gr.Slider(
label="Seed",
minimum=0,
maximum=MAX_SEED,
step=1,
value=0,
)
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
with gr.Row():
width = gr.Slider(
label="Width",
minimum=256,
maximum=MAX_IMAGE_SIZE,
step=64,
value=1024,
)
height = gr.Slider(
label="Height",
minimum=256,
maximum=MAX_IMAGE_SIZE,
step=64,
value=1024,
)
with gr.Row():
guidance_scale = gr.Slider(
label="Guidance scale",
minimum=0.0,
maximum=10.0,
step=0.1,
value=5.0,
)
num_inference_steps = gr.Slider(
label="Number of inference steps",
minimum=1,
maximum=50,
step=1,
value=28,
)
gr.Examples(
examples=examples,
inputs=[prompt]
)
gr.on(
triggers=[run_button.click, prompt.submit, negative_prompt.submit],
fn=infer,
inputs=[prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
outputs=[result, seed]
)
# Launch the app
demo.launch(timeout=10) # Increase timeout if needed