app.py

import gradio as gr
from optimum.intel import OVStableDiffusionPipeline

model_id = "helenai/eimiss-EimisAnimeDiffusion_1.0v-ov"

batch_size = 1
num_images_per_prompt = 1
height = 512
width = 512

pipeline = OVStableDiffusionPipeline.from_pretrained(model_id, compile=False)
pipeline.sampler = "dpm++2s_a"
pipeline.to("CPU")
pipeline.reshape( batch_size=batch_size, height=height, width=width, num_images_per_prompt=num_images_per_prompt)
pipeline.compile()



def infer(prompt):
    image = pipeline(
        prompt=prompt,
        width=width,
        height=height,
        num_inference_steps=28,
        num_images_per_prompt=num_images_per_prompt,
    ).images[0]
    return image

examples = [
    "Sailor Chibi Moon, Katsura Masakazu style",
    "1girl, silver hair, symbol-shaped pupils, yellow eyes, smiling, light particles, light rays, wallpaper, star guardian, serious face, red inner hair, power aura, grandmaster1, golden and white clothes",
    "A cute kitten, Tinkle style.",
    "(illustration, 8k CG, extremely detailed),(whimsical),catgirl,teenage girl,playing in the snow,winter wonderland,snow-covered trees,soft pastel colors,gentle lighting,sparkling snow,joyful,magical atmosphere,highly detailed,fluffy cat ears and tail,intricate winter clothing,shallow depth of field,watercolor techniques,close-up shot,slightly tilted angle,fairy tale architecture,nostalgic,playful,winter magic,(masterpiece:2),best quality,ultra highres,original,extremely detailed,perfect lighting,",
]

css = """
#col-container {
    margin: 0 auto;
    max-width: 520px;
}
"""

with gr.Blocks(css=css) as demo:
    with gr.Column(elem_id="col-container"):
        gr.Markdown("# Demo : helenai/eimiss-EimisAnimeDiffusion_1.0v-ov ⚡")
        with gr.Row():
            prompt = gr.Text(
                label="Prompt",
                show_label=False,
                placeholder="Enter your prompt",
                container=False,
            )
            
            run_button = gr.Button("Run", scale=0)
        result = gr.Image(label="Result", show_label=False)

        gr.Examples(
            examples = examples,
            fn = infer,
            inputs = [prompt],
            outputs = [result]
        )

    run_button.click(
        fn=infer,
        inputs=[prompt],
        outputs=[result]
    )

demo.queue().launch(share=True)