app.py

import gradio as gr
from inference_code import generate_images


def generate_image_predictions(prompt):
    images = generate_images(prompt)
    return images


iface = gr.Interface(
    gr.Markdown(
        """
    # Map Diffuser 🌍
    Examples table:
    | Prompt | Output |
    | --- | --- |
    | Satellite image of amsterdam with industrial area and highways | <img src="https://i.imgur.com/vrGpk45.png" width="300" /> |
    | Watercolor style map of Amsterdam with residential area and highways | <img src="https://i.imgur.com/AQS34dk.png" width="300" /> |
    | Toner style map of Amsterdam with residential area and highways | <img src="https://i.imgur.com/X8VcezT.png" width="300" /> |
    | Satellite image with forests and residential, no water | <img src="https://i.imgur.com/MEccHdM.png" width="300" /> |
    """
    ),
    fn=generate_image_predictions,
    inputs=gr.components.Textbox(label="Enter a text prompt here"),
    outputs=gr.components.Image(label="Output Image"),

    title="🌍 Map Diffuser",
    description="""
        🌏 Generates images from a given text prompt. The prompts are in the format:
        `{style} map of {city} with {features}` or
        `satellite image of {city} with {features}` or
        `satellite image with {features}` or
        `satellite image of {city} with {features} and no {features}`
        and so on...

        So for example:
        - "Satellite image of amsterdam with industrial area and highways"
        - "Watercolor style map of Amsterdam with residential area and highways"
        - "Toner style map of Amsterdam with residential area and highways"
        - "Satellite image with forests and residential, no water"
    """
)

iface.launch()