| 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() |