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import gradio as gr
import spaces
from ominicontrol import generate_image, generate_image_with_prompt
import os
from huggingface_hub import login
USE_ZERO_GPU = os.environ.get("USE_ZERO_GPU", "0") == "1"
HF_TOKEN = os.environ.get("HF_TOKEN")
if HF_TOKEN:
login(token=HF_TOKEN)
css = """
.inputPanel {
width: 320px;
display: flex;
align-items: center;
}
.outputPanel {
display: flex;
align-items: center;
}
.hint {
font-size: 14px;
color: #777;
# border: 1px solid #ccc;
padding: 4px;
border-radius: 5px;
# background-color: #efefef;
}
"""
header = """
# 🎨 OminiControl Art
<div style="text-align: center; display: flex; justify-content: left; gap: 5px;">
<a href="https://arxiv.org/abs/2411.15098"><img src="https://img.shields.io/badge/ariXv-Paper-A42C25.svg" alt="arXiv"></a>
<a href="https://huggingface.co/spaces/Yuanshi/OminiControl"><img src="https://img.shields.io/badge/🤗OminiControl-Demo-ffbd45.svg" alt="HuggingFace"></a>
<a href="https://github.com/Yuanshi9815/OminiControl"><img src="https://img.shields.io/badge/GitHub-Code-blue.svg?logo=github&" alt="GitHub"></a>
</div>
***OminiControl Art*** distills the artistic style of [GPT-4o](https://openai.com/index/introducing-4o-image-generation/) into the [FLUX.1](https://blackforestlabs.ai/) model, building on the foundation of [OminiControl](https://github.com/Yuanshi9815/OminiControl)✨.
Enjoy playing around! 🌈
"""
def style_transfer(image, style):
return image
styles = [
"Studio Ghibli",
"Irasutoya Illustration",
"The Simpsons",
"Snoopy",
]
def gradio_interface():
with gr.Blocks(css=css) as demo:
gr.Markdown(header)
with gr.Row(equal_height=False):
with gr.Column(variant="panel", elem_classes="inputPanel"):
original_image = gr.Image(
type="pil",
label="Condition Image",
width=400,
height=400,
)
style = gr.Radio(
styles,
label="🎨 Select Style",
value=styles[0],
)
# Advanced settings
with gr.Accordion(
"⚙️ Advanced Settings", open=False
) as advanced_settings:
inference_mode = gr.Radio(
["High Quality", "Fast"],
value="High Quality",
label="Generating Mode",
)
image_ratio = gr.Radio(
["Auto", "Square(1:1)", "Portrait(2:3)", "Landscape(3:2)"],
label="Image Ratio",
value="Auto",
)
use_random_seed = gr.Checkbox(label="Use Random Seed", value=True)
seed = gr.Number(
label="Seed",
value=42,
visible=(not use_random_seed.value),
)
use_random_seed.change(
lambda x: gr.update(visible=(not x)),
use_random_seed,
seed,
show_progress="hidden",
)
image_guidance = gr.Slider(
label="Image Guidance",
minimum=1.1,
maximum=5,
value=1.5,
step=0.1,
)
steps = gr.Slider(
label="Steps",
minimum=10,
maximum=50,
value=20,
step=1,
)
inference_mode.change(
lambda x: gr.update(interactive=(x == "High Quality")),
inference_mode,
image_guidance,
show_progress="hidden",
)
btn = gr.Button("Generate Image", variant="primary")
with gr.Column(elem_classes="outputPanel"):
output_image = gr.Image(
type="pil",
width=600,
height=600,
label="Output Image",
interactive=False,
sources=None,
)
hint = gr.Markdown(
"""
<div style="text-align: center; width: 100%;">
<b>Note: The selected style is in beta testing.</b> Feel free to try a few more times to get a the better result.
</div>
""",
visible=False,
)
style.change(
lambda x: gr.update(visible=x in styles[1:]),
style,
hint,
)
# with gr.Row():
btn.click(
fn=infer,
inputs=[
style,
original_image,
inference_mode,
image_guidance,
image_ratio,
use_random_seed,
seed,
steps,
],
outputs=[
output_image,
],
)
return demo
def infer(
style,
original_image,
inference_mode,
image_guidance,
image_ratio,
use_random_seed,
seed,
steps,
):
print(
f"Style: {style}, Inference Mode: {inference_mode}, Image Guidance: {image_guidance}, Image Ratio: {image_ratio}, Use Random Seed: {use_random_seed}, Seed: {seed}"
)
result_image = generate_image(
image=original_image,
style=style,
inference_mode=inference_mode,
image_guidance=image_guidance,
image_ratio=image_ratio,
use_random_seed=use_random_seed,
seed=seed,
steps=steps,
)
return result_image
def prompt_gradio_interface():
with gr.Blocks(css=css) as demo:
with gr.Row(equal_height=False):
with gr.Column(variant="panel", elem_classes="inputPanel"):
original_image = gr.Image(
type="pil",
label="Condition Image",
width=400,
height=400,
)
prompt = gr.Textbox(
label="Prompt",
)
# Advanced settings
with gr.Accordion(
"⚙️ Advanced Settings", open=False
) as advanced_settings:
inference_mode = gr.Radio(
["High Quality", "Fast"],
value="High Quality",
label="Generating Mode",
)
image_ratio = gr.Radio(
["Auto", "Square(1:1)", "Portrait(2:3)", "Landscape(3:2)"],
label="Image Ratio",
value="Auto",
)
use_random_seed = gr.Checkbox(label="Use Random Seed", value=True)
seed = gr.Number(
label="Seed",
value=42,
visible=(not use_random_seed.value),
)
use_random_seed.change(
lambda x: gr.update(visible=(not x)),
use_random_seed,
seed,
show_progress="hidden",
)
image_guidance = gr.Slider(
label="Image Guidance",
minimum=1.1,
maximum=5,
value=1.5,
step=0.1,
)
steps = gr.Slider(
label="Steps",
minimum=10,
maximum=50,
value=20,
step=1,
)
inference_mode.change(
lambda x: gr.update(interactive=(x == "High Quality")),
inference_mode,
image_guidance,
show_progress="hidden",
)
btn = gr.Button("Generate Image", variant="primary")
with gr.Column(elem_classes="outputPanel"):
output_image = gr.Image(
type="pil",
width=600,
height=600,
label="Output Image",
interactive=False,
sources=None,
)
# with gr.Row():
btn.click(
fn=prompt_infer,
inputs=[
original_image,
prompt,
inference_mode,
image_guidance,
image_ratio,
use_random_seed,
seed,
steps,
],
outputs=[
output_image,
],
)
return demo
def prompt_infer(
original_image,
prompt,
inference_mode,
image_guidance,
image_ratio,
use_random_seed,
seed,
steps,
):
result_image = generate_image_with_prompt(
image=original_image,
prompt=prompt,
inference_mode=inference_mode,
image_guidance=image_guidance,
image_ratio=image_ratio,
use_random_seed=use_random_seed,
seed=seed,
steps=steps,
)
return result_image
def multi_gradio_interface():
with gr.Blocks(css="style.css") as demo:
with gr.Tabs():
with gr.Tab(label="Style"):
gradio_interface()
with gr.Tab(label="Prompt"):
prompt_gradio_interface()
return demo
if USE_ZERO_GPU:
infer = spaces.GPU(infer)
prompt_infer = spaces.GPU(prompt_infer)
if __name__ == "__main__":
demo = multi_gradio_interface()
demo.launch(server_name="0.0.0.0", ssr_mode=False)
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