app.py

import gradio as gr
from ominicontrol import generate_image

import spaces

USE_ZERO_GPU = True

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;
}
"""


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("# 🌍 OminiControl (Image Stylization)")
        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")

            with gr.Column(elem_classes="outputPanel"):
                output_images = gr.Image(
                    type="pil",
                    width=640,
                    height=640,
                    label="Output Image",
                )

        btn.click(
            fn=infer,
            inputs=[
                style,
                original_image,
                inference_mode,
                image_guidance,
                image_ratio,
                use_random_seed,
                seed,
                steps,
            ],
            outputs=output_images,
        )

    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


if USE_ZERO_GPU:
    infer = spaces.GPU(infer, duration=360)

if __name__ == "__main__":
    demo = gradio_interface()
    demo.launch(
        debug=True,
        server_name="0.0.0.0",
    )