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import gradio as gr
import torch
from gradio_depth_pred import create_demo as create_depth_pred_demo
css = """
#img-display-container {
max-height: 50vh;
}
#img-display-input {
max-height: 40vh;
}
#img-display-output {
max-height: 40vh;
}
"""
DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'
model = torch.hub.load('isl-org/ZoeDepth', "ZoeD_N", pretrained=True).to(DEVICE).eval()
title = "# ZoeDepth"
description = "Official demo for Ultra Heroes."
with gr.Blocks(css=css) as demo:
gr.Markdown(title)
gr.Markdown(description)
with gr.Tab("Depth Prediction"):
create_depth_pred_demo(model)
# gr.HTML('''<br><br><br><center>You can duplicate this Space to skip the queue:<a href="https://huggingface.co/spaces/shariqfarooq/ZoeDepth?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a></center>''')
if __name__ == '__main__':
demo.queue().launch() |