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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)
# Here you would typically use a 3D modeling library or call an external API to process the image
processed_image = image_array # This line simulates processing
def generate_3d_model(image):
# Here, you would replace this code with the logic to generate a 3D model
# For this example, let's assume it saves a dummy 3D model file
output_file = "output_model.obj"
# Write a simple placeholder 3D model file
with open(output_file, "w") as f:
f.write("# This is a placeholder for a real 3D model\n")
f.write("o Cube\n")
f.write("v 0.000000 0.000000 0.000000\n")
f.write("v 0.000000 1.000000 0.000000\n")
f.write("v 1.000000 1.000000 0.000000\n")
f.write("v 1.000000 0.000000 0.000000\n")
f.write("v 0.000000 0.000000 1.000000\n")
f.write("v 0.000000 1.000000 1.000000\n")
f.write("v 1.000000 1.000000 1.000000\n")
f.write("v 1.000000 0.000000 1.000000\n")
f.write("f 1 2 3 4\n")
f.write("f 5 6 7 8\n")
f.write("f 1 5 8 4\n")
f.write("f 2 6 7 3\n")
f.write("f 1 2 6 5\n")
f.write("f 4 3 7 8\n")
return output_file
# Convert back to PIL image for display
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()
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