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| import gradio as gr | |
| from gradio_client import Client, handle_file | |
| def predict_depth(image): | |
| client = Client("prs-eth/marigold") | |
| try: | |
| # Full parameter set assuming all are required | |
| result = client.predict( | |
| handle_file(image), | |
| 1, # Ensemble size | |
| 10, # Number of denoising steps | |
| "0", # Processing resolution | |
| handle_file('https://example.com/sample_file.pdf'), # Placeholder URL for required file inputs | |
| handle_file('https://example.com/sample_file.pdf'), | |
| handle_file('https://example.com/sample_file.pdf'), | |
| 0.5, # Relative near plane position | |
| 0.9, # Relative far plane position | |
| 10, # Embossing level | |
| 2, # Smoothing filter size | |
| -50, # Near plane offset | |
| api_name="/submit_depth_fn" | |
| ) | |
| if result and result[0]: | |
| return result[0] | |
| except Exception as e: | |
| return f"An error occurred: {str(e)}" | |
| return "No depth output available" | |
| # Gradio Interface | |
| iface = gr.Interface( | |
| fn=predict_depth, | |
| inputs=gr.Image(type='filepath', label="Upload your image"), | |
| outputs=gr.File(label="Download Depth Map"), | |
| title="Depth Map Generator", | |
| description="Upload an image to receive a depth map file." | |
| ) | |
| iface.launch() | |