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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() | |