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import random
import spaces
import gradio as gr
import torch
from diffusers import StableDiffusionXLPipeline
from scheduling_tcd import TCDScheduler
css = """
h1 {
text-align: center;
display:block;
}
h3 {
text-align: center;
display:block;
}
"""
device = "cuda"
base_model_id = "stabilityai/stable-diffusion-xl-base-1.0"
tcd_lora_id = "h1t/TCD-SDXL-LoRA"
pipe = StableDiffusionXLPipeline.from_pretrained(
base_model_id,
torch_dtype=torch.float16,
variant="fp16"
).to(device)
pipe.scheduler = TCDScheduler.from_config(pipe.scheduler.config)
pipe.load_lora_weights(tcd_lora_id)
pipe.fuse_lora()
@spaces.GPU
def inference(prompt, num_inference_steps=4, seed=-1, eta=0.3):
if seed is None or seed == '' or seed == -1:
seed = int(random.randrange(4294967294))
generator = torch.Generator(device=device).manual_seed(int(seed))
image = pipe(
prompt=prompt,
num_inference_steps=num_inference_steps,
guidance_scale=0,
eta=eta,
generator=generator,
).images[0]
return image
# Define style
title = "<h1>Trajectory Consistency Distillation</h1>"
description = "<h3>Official 🤗 Gradio demo for Trajectory Consistency Distillation</h3>"
article = "<p style='text-align: center'><a href='https://arxiv.org/abs/' target='_blank'>Trajectory Consistency Distillation</a> | <a href='https://github.com/jabir-zheng/TCD' target='_blank'>Github Repo</a></p>"
default_prompt = " "
examples = [
[
"Beautiful woman, bubblegum pink, lemon yellow, minty blue, futuristic, high-detail, epic composition, watercolor.",
4
],
[
"Beautiful man, bubblegum pink, lemon yellow, minty blue, futuristic, high-detail, epic composition, watercolor.",
8
],
[
"Painting of the orange cat Otto von Garfield, Count of Bismarck-Schönhausen, Duke of Lauenburg, Minister-President of Prussia. Depicted wearing a Prussian Pickelhaube and eating his favorite meal - lasagna.",
16
],
[
"closeup portrait of 1 Persian princess, royal clothing, makeup, jewelry, wind-blown long hair, symmetric, desert, sands, dusty and foggy, sand storm, winds bokeh, depth of field, centered.",
16
],
]
outputs = gr.Label(label='Generated Images')
with gr.Blocks(css=css) as demo:
gr.Markdown(f'# {title}\n### {description}')
with gr.Row():
with gr.Column():
prompt = gr.Textbox(label='Prompt', value=default_prompt)
num_inference_steps = gr.Slider(
label='Inference steps',
minimum=4,
maximum=16,
value=8,
step=1,
)
with gr.Accordion("Advanced Options", open=False):
with gr.Row():
with gr.Column():
seed = gr.Number(label="Random Seed", value=-1)
with gr.Column():
eta = gr.Slider(
label='Gamma',
minimum=0.,
maximum=1.,
value=0.3,
step=0.1,
)
with gr.Row():
clear = gr.ClearButton(
components=[prompt, num_inference_steps, seed, eta])
submit = gr.Button(value='Submit')
examples = gr.Examples(
label="Quick Examples",
examples=examples,
inputs=[prompt, num_inference_steps, 0, 0.3],
outputs="outputs",
cache_examples=False
)
with gr.Column():
outputs = gr.Image(label='Generated Images')
gr.Markdown(f'{article}')
submit.click(
fn=inference,
inputs=[prompt, num_inference_steps, seed, eta],
outputs=outputs,
)
demo.launch()
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