app.py

import gradio as gr
from PIL import Image
import numpy as np

# Placeholder function to simulate 3D model generation
def generate_3d_model(image):
    # Convert the uploaded image to a numpy array for processing
    image_array = np.array(image)

    # Placeholder logic: simply return the same image (you can replace this with actual processing)
    processed_image = image_array  # This line simulates processing

    # Convert numpy array back to PIL image for Gradio output
    result_image = Image.fromarray(processed_image)

    return result_image

# Define the Gradio interface using the updated syntax
iface = gr.Interface(
    fn=generate_3d_model,
    inputs=gr.Image(type="pil", label="Upload Jewelry Image"),
    outputs=gr.Image(type="pil", label="Generated 3D Model"),
    title="3D Jewelry Model Generator",
    description="Upload an image of jewelry to generate a 3D model. This is a placeholder for the actual 3D generation functionality.",
    theme="compact"
)

# Launch the interface
if __name__ == "__main__":
    iface.launch()