app.py

import gradio as gr
from PIL import Image
from diffusers import DiffusionPipeline

# Load model and scheduler
ldm = DiffusionPipeline.from_pretrained("CompVis/ldm-text2im-large-256")

def generate_image(prompt, negative_prompt="Low quality", width=512, height=512, num_steps=50, eta=0.3, guidance_scale=6):
    # Run pipeline in inference (sample random noise and denoise)
    images = ldm([prompt], num_inference_steps=num_steps, eta=eta, guidance_scale=guidance_scale, negative_prompts=[negative_prompt]).images
    # Resize image to desired width and height
    resized_images = [image.resize((width, height)) for image in images]
    # Save images
    for idx, image in enumerate(resized_images):
        image.save(f"squirrel-{idx}.png")
    return "Images generated successfully!"

# Define the interface
iface = gr.Interface(
    fn=generate_image,
    inputs=[
        gr.inputs.Textbox(label="Prompt", lines=2),
        gr.inputs.Textbox(label="Negative Prompt (optional)", lines=2),
        gr.inputs.Number(label="Width (optional)", default=512),
        gr.inputs.Number(label="Height (optional)", default=512),
        gr.inputs.Number(label="Number of Inference Steps (optional)", default=50),
        gr.inputs.Number(label="Eta (optional)", default=0.3),
        gr.inputs.Number(label="Guidance Scale (optional)", default=6),
    ],
    outputs="text",
    layout="vertical",
    title="Image Generation",
    description="Generate images based on prompts. Adjust the optional parameters for customization. The generated images will be resized to the specified width and height.",
    article="Check out the documentation for more information: [link](https://docs.gradio.app/)",
    examples=[
        ["A painting of a squirrel eating a burger", "Low quality", 512, 512, 50, 0.3, 6],
        ["A breathtaking landscape with mountains", "Blurry", 800, 600, 30, 0.5, 8],
        ["An abstract artwork with vibrant colors", "Dull", 1024, 768, 70, 0.2, 10],
    ],
)

# Configure styling options
iface.configure(
    label_font="Arial",
    label_font_size=18,
    border_width=2,
    border_color="blue",
    button_bg_color="lightblue",
    button_text_color="black",
)

# Launch the interface
iface.launch()