| | import gradio as gr |
| | import spaces |
| | from panna import SD2 |
| |
|
| |
|
| | model = SD2( |
| | base_model_id="stabilityai/stable-diffusion-xl-base-1.0", |
| | refiner_model_id="stabilityai/stable-diffusion-xl-refiner-1.0" |
| | ) |
| | title = ("# Stable Diffusion 2 XL ([base model](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0), [refiner model](https://huggingface.co/stabilityai/stable-diffusion-xl-refiner-1.0))\n" |
| | "The demo is part of [panna](https://github.com/asahi417/panna) project.") |
| | examples = [ |
| | "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k", |
| | "A female model, high quality, fashion, Paris, Vogue, Maison Margiela, 8k", |
| | ] |
| | css = """ |
| | #col-container { |
| | margin: 0 auto; |
| | max-width: 580px; |
| | } |
| | """ |
| |
|
| |
|
| | @spaces.GPU |
| | def infer(prompt, negative_prompt, seed, width, height, guidance_scale, num_inference_steps): |
| | return model.text2image( |
| | prompt=[prompt], |
| | negative_prompt=[negative_prompt], |
| | guidance_scale=guidance_scale, |
| | num_inference_steps=num_inference_steps, |
| | width=width, |
| | height=height, |
| | seed=seed |
| | )[0] |
| |
|
| |
|
| | with gr.Blocks(css=css) as demo: |
| | with gr.Column(elem_id="col-container"): |
| | gr.Markdown(title) |
| | with gr.Row(): |
| | prompt = gr.Text(label="Prompt", show_label=False, max_lines=1, placeholder="Enter your prompt", container=False) |
| | run_button = gr.Button("Run", scale=0) |
| | result = gr.Image(label="Result", show_label=False) |
| | with gr.Accordion("Advanced Settings", open=False): |
| | negative_prompt = gr.Text(label="Negative Prompt", max_lines=1, placeholder="Enter a negative prompt") |
| | seed = gr.Slider(label="Seed", minimum=0, maximum=1_000_000, step=1, value=0) |
| | with gr.Row(): |
| | width = gr.Slider(label="Width", minimum=256, maximum=1344, step=64, value=1024) |
| | height = gr.Slider(label="Height", minimum=256, maximum=1344, step=64, value=1024) |
| | with gr.Row(): |
| | guidance_scale = gr.Slider(label="Guidance scale", minimum=0.0, maximum=10.0, step=0.1, value=7.5) |
| | num_inference_steps = gr.Slider(label="Inference steps", minimum=1, maximum=50, step=1, value=40) |
| | gr.Examples(examples=examples, inputs=[prompt]) |
| | gr.on( |
| | triggers=[run_button.click, prompt.submit, negative_prompt.submit], |
| | fn=infer, |
| | inputs=[prompt, negative_prompt, seed, width, height, guidance_scale, num_inference_steps], |
| | outputs=[result] |
| | ) |
| | demo.launch(server_name="0.0.0.0") |
| |
|