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()