Spaces:
Running
on
Zero
Running
on
Zero
File size: 2,879 Bytes
0fe1449 30bf7bc 0fe1449 b1b860e 0fe1449 b1b860e 48df6f9 0fe1449 acb6168 0fe1449 b1b860e 0fe1449 c4f32a7 0fe1449 477a209 0fe1449 48df6f9 0fe1449 |
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 63 64 65 66 67 68 69 70 71 72 |
import gradio as gr
from diffusers import StableDiffusionXLPipeline
import numpy as np
import math
import spaces
import torch
import sys
import random
from gradio_imageslider import ImageSlider
theme = gr.themes.Base(
font=[gr.themes.GoogleFont('Libre Franklin'), gr.themes.GoogleFont('Public Sans'), 'system-ui', 'sans-serif'],
)
pipe = StableDiffusionXLPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
custom_pipeline="multimodalart/sdxl_perturbed_attention_guidance",
torch_dtype=torch.float16
)
device="cuda"
pipe = pipe.to(device)
@spaces.GPU
def run(prompt, negative_prompt="", guidance_scale=7.0, pag_scale=3.0, randomize_seed=True, seed=42, progress=gr.Progress(track_tqdm=True)):
prompt = prompt.strip()
if(randomize_seed):
seed = random.randint(0, sys.maxsize)
if(prompt == ""):
guidance_scale = 0.0
generator = torch.Generator(device="cuda").manual_seed(seed)
image_pag = pipe(prompt, guidance_scale=guidance_scale, pag_scale=3.0, pag_applied_layers=['mid'], generator=generator, num_inference_steps=25).images[0]
generator = torch.Generator(device="cuda").manual_seed(seed)
image_normal = pipe(prompt, guidance_scale=guidance_scale, generator=generator, num_inference_steps=25).images[0]
return (image_pag, image_normal), seed
css = '''
.gradio-container{
max-width: 768px !important;
margin: 0 auto;
}
'''
with gr.Blocks(css=css, theme=theme) as demo:
gr.Markdown('''# Perturbed Attention Guidance SDXL
SDXL 🧨 [diffusers implementation](https://huggingface.co/multimodalart/sdxl_perturbed_attention_guidance) of [Perturbed-Attenton Guidance](https://ku-cvlab.github.io/Perturbed-Attention-Guidance/)
''')
with gr.Group():
with gr.Row():
prompt = gr.Textbox(show_label=False, scale=4, placeholder="Your prompt", info="Leave blank to test unconditional generation")
button = gr.Button("Generate", min_width=120)
output = ImageSlider(label="Left: PAG, Right: No PAG", interactive=False)
with gr.Accordion("Advanced Settings", open=False):
guidance_scale = gr.Number(label="Guidance Scale", value=7.0)
pag_scale = gr.Number(label="Pag Scale", value=3.0)
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
seed = gr.Slider(minimum=1, maximum=18446744073709551615, step=1, randomize=True)
gr.Examples(fn=run, examples=[" ", "an insect robot preparing a delicious meal, anime style", "a photo of a group of friends at an amusement park"], inputs=prompt, outputs=[output, seed], cache_examples=True)
gr.on(
triggers=[
button.click,
prompt.submit
],
fn=run,
inputs=[prompt, guidance_scale, pag_scale, seed],
outputs=[output, seed],
)
if __name__ == "__main__":
demo.launch(share=True) |