app.py

import gradio as gr
from diffusers import StableDiffusionPanoramaPipeline, DDIMScheduler
import torch

# Load the base pipeline
base_model = "runwayml/stable-diffusion-v1-5"
scheduler = DDIMScheduler.from_pretrained(base_model, subfolder="scheduler")

# Define a function to create a pipeline with the appropriate LoRA weights
def create_pipeline_with_lora():
    pipeline = StableDiffusionPanoramaPipeline.from_pretrained(base_model, scheduler=scheduler, torch_dtype=torch.float32)
    model_id = "RingL/panodiff"
    pipeline.load_lora_weights(model_id)
    return pipeline.to("cpu")

pipeline = create_pipeline_with_lora()

# Define the prompt function
def generate_image(prompt):
    image = pipeline(prompt).images[0]
    return image

# Define the Gradio interface
def gradio_app(prompt_choice, custom_prompt):
    if prompt_choice == "Custom":
        prompt = custom_prompt
    else:
        prompt = prompt_choice
    return generate_image(prompt)

example_prompts = [
    "nighttime cityscape with a blue luxury car and a yellow sports car driving on a brightly lit street",
    "A vibrant metropolitan skyline at dawn, where the first light of day casts a soft glow over towering skyscrapers and bustling streets below. The city's architecture showcases a blend of modern and historic buildings, creating a rich tapestry of styles. The streets are filled with early morning commuters, street vendors setting up their stalls, and the occasional jogger. The sky transitions from deep blue to pink and gold, with the promise of a beautiful day ahead.",
    "A futuristic cityscape at dusk, with sleek, high-tech buildings and neon lights illuminating the city. Hovering vehicles zip through the air, and people walk along elevated walkways, enjoying the evening. The streets below are lined with holographic billboards, cafes, and shops, each adding to the lively atmosphere. The sky is a blend of deep purples and oranges, with stars beginning to twinkle as night falls."
]

with gr.Blocks() as demo:
    gr.Markdown("# Panorama Image Generation with Diffusers")
    prompt_choice = gr.Dropdown(label="Select a Prompt", choices=example_prompts + ["Custom"], value="Custom")
    custom_prompt = gr.Textbox(label="Enter Custom Prompt", placeholder="Enter your own prompt here...")
    generate_button = gr.Button("Generate Image")
    output_image = gr.Image(label="Generated Image", image_mode="RGB")

    generate_button.click(fn=gradio_app, inputs=[prompt_choice, custom_prompt], outputs=output_image)

# Launch the Gradio app
demo.launch()