Create app.py

app.py

@@ -0,0 +1,34 @@
+import gradio as gr
+from gradio_client import Client, file
+
+def predict_depth(image):
+    client = Client("prs-eth/marigold")  # Adjust the username/modelname as needed
+
+    # Assuming 'image' is the input image file from the user
+    response = client.predict(
+        file(image),  # Image file path
+        1,  # Ensemble size (example value)
+        10,  # Number of denoising steps (example value)
+        "0",  # Processing resolution (example value)
+        file('path_to_sample_file_1.pdf'),  # Sample file path for depth (16-bit)
+        file('path_to_sample_file_2.pdf'),  # Sample file path for depth (32-bit)
+        file('path_to_sample_file_3.pdf'),  # Sample file path for depth (color)
+        0.5,  # Relative position of the near plane
+        0.9,  # Relative position of the far plane
+        10,  # Embossing level
+        2,  # Smoothing filter size
+        -50,  # Frame's near plane offset
+        api_name="/submit_depth_fn"
+    )
+    return response['image']  # Adjust according to the actual key in the response
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=predict_depth,
+    inputs=gr.Image(type='filepath', label="Upload your image"),
+    outputs=gr.Image(type='auto', label="Depth Map Image"),
+    title="Depth Map Generator",
+    description="Upload an image to receive a depth map."
+)
+
+iface.launch()