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from contextlib import nullcontext
import gradio as gr
import torch
from torch import autocast
from diffusers import StableDiffusionPipeline
device = "cuda" if torch.cuda.is_available() else "cpu"
context = autocast if device == "cuda" else nullcontext
dtype = torch.float16 if device == "cuda" else torch.float32
model_id = 'lambdalabs/dreambooth-avatar'
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=dtype)
pipe = pipe.to(device)
def infer(prompt, n_samples, steps, scale):
with context("cuda"):
images = pipe(n_samples*[prompt], guidance_scale=scale, num_inference_steps=steps).images
return images
css = """
a {
color: inherit;
text-decoration: underline;
}
.gradio-container {
font-family: 'IBM Plex Sans', sans-serif;
}
.gr-button {
color: white;
border-color: #9d66e5;
background: #9d66e5;
}
input[type='range'] {
accent-color: #9d66e5;
}
.dark input[type='range'] {
accent-color: #dfdfdf;
}
.container {
max-width: 730px;
margin: auto;
padding-top: 1.5rem;
}
#gallery {
min-height: 22rem;
margin-bottom: 15px;
margin-left: auto;
margin-right: auto;
border-bottom-right-radius: .5rem !important;
border-bottom-left-radius: .5rem !important;
}
#gallery>div>.h-full {
min-height: 20rem;
}
.details:hover {
text-decoration: underline;
}
.gr-button {
white-space: nowrap;
}
.gr-button:focus {
border-color: rgb(147 197 253 / var(--tw-border-opacity));
outline: none;
box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
--tw-border-opacity: 1;
--tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
--tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
--tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
--tw-ring-opacity: .5;
}
#advanced-options {
margin-bottom: 20px;
}
.footer {
margin-bottom: 45px;
margin-top: 35px;
text-align: center;
border-bottom: 1px solid #e5e5e5;
}
.footer>p {
font-size: .8rem;
display: inline-block;
padding: 0 10px;
transform: translateY(10px);
background: white;
}
.dark .logo{ filter: invert(1); }
.dark .footer {
border-color: #303030;
}
.dark .footer>p {
background: #0b0f19;
}
.acknowledgments h4{
margin: 1.25em 0 .25em 0;
font-weight: bold;
font-size: 115%;
}
"""
block = gr.Blocks(css=css)
examples = [
[
'Jeff Bezos, avatarart style',
2,
7.5,
],
[
'Elon Musk, avatarart style',
2,
7.5,
],
[
'Bill Gates, avatarart style',
2,
7,
],
]
with block:
gr.HTML(
"""
<div style="text-align: center; max-width: 650px; margin: 0 auto;">
<div>
<img class="logo" src="https://lambdalabs.com/hubfs/logos/lambda-logo.svg" alt="Lambda Logo"
style="margin: auto; max-width: 7rem;">
<h1 style="font-weight: 900; font-size: 3rem;">
Avatar text to image
</h1>
</div>
</div>
"""
)
with gr.Group():
with gr.Box():
with gr.Row().style(mobile_collapse=False, equal_height=True):
text = gr.Textbox(
label="Enter your prompt",
show_label=False,
max_lines=1,
placeholder="Enter your prompt",
).style(
border=(True, False, True, True),
rounded=(True, False, False, True),
container=False,
)
btn = gr.Button("Generate image").style(
margin=False,
rounded=(False, True, True, False),
)
gallery = gr.Gallery(
label="Generated images", show_label=False, elem_id="gallery"
).style(grid=[2], height="auto")
with gr.Row(elem_id="advanced-options"):
samples = gr.Slider(label="Images", minimum=1, maximum=4, value=2, step=1)
steps = gr.Slider(label="Steps", minimum=5, maximum=50, value=50, step=5)
scale = gr.Slider(
label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1
)
ex = gr.Examples(examples=examples, fn=infer, inputs=[text, samples, scale], outputs=gallery, cache_examples=False)
ex.dataset.headers = [""]
text.submit(infer, inputs=[text, samples, steps, scale], outputs=gallery)
btn.click(infer, inputs=[text, samples, steps, scale], outputs=gallery)
gr.HTML(
"""
<div class="footer">
<p> Gradio Demo by 🤗 Hugging Face and Lambda Labs
</p>
</div>
<div class="acknowledgments">
<p> Put in a text prompt and generate your own Avatar art style image!
<p>Trained by Eole Cervenka at <a href="https://lambdalabs.com/">Lambda Labs</a>.</p>
</div>
"""
)
block.launch() |