import gradio as gr
import numpy as np
# Import your 3D image processing model here

def process_3d_image(input_image):
    # Your model processing logic here
    # This is a placeholder function
    output_mask = np.random.randint(0, 2, input_image.shape).astype(bool)
    return output_mask

demo = gr.Interface(
    fn=process_3d_image,
    inputs=gr.Model3D(label="Input 3D Image"),
    outputs=gr.Model3D(label="Output 3D Binary Mask"),
    title="3D Image to Binary Mask",
    description="Upload a 3D image (x,y,z) and get a 3D binary mask as output."
)

if __name__ == "__main__":
    demo.launch()