Update app.py

app.py

@@ -1,7 +1,43 @@
 import gradio as gr
+import torch
 
-def greet(name):
-    return "Hello " + name + "!!"
+from gradio_depth_pred import create_demo as create_depth_pred_demo
+from gradio_im_to_3d import create_demo as create_im_to_3d_demo
+from gradio_pano_to_3d import create_demo as create_pano_to_3d_demo
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+
+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 **ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth**.
+ZoeDepth is a deep learning model for metric depth estimation from a single image.
+Please refer to our [paper](https://arxiv.org/abs/2302.12288) or [github](https://github.com/isl-org/ZoeDepth) for more details."""
+
+with gr.Blocks(css=css) as demo:
+    gr.Markdown(title)
+    gr.Markdown(description)
+    with gr.Tab("Depth Prediction"):
+        create_depth_pred_demo(model)
+    with gr.Tab("Image to 3D"):
+        create_im_to_3d_demo(model)
+    with gr.Tab("360 Panorama to 3D"):
+        create_pano_to_3d_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><br>
+        <p><img src="https://visitor-badge.glitch.me/badge?page_id=shariqfarooq.zoedepth_demo_hf" alt="visitors"></p></center>''')
+
+if __name__ == '__main__':
+    demo.queue().launch()