Update app.py

app.py

@@ -11,7 +11,7 @@ feature_extractor = DPTFeatureExtractor.from_pretrained("Intel/dpt-large")
 model = DPTForDepthEstimation.from_pretrained("Intel/dpt-large")
 
 
-def process_image(image_path, experiment_id):
+def process_image(image_path):
     image_path = Path(image_path)
     image_raw = Image.open(image_path)
     image = image_raw.resize(
@@ -106,19 +106,7 @@ description = "This demo shows the effectiveness of LIVE <a href='' target='_bla
 examples = [["examples/" + img] for img in os.listdir("examples/")]
 
 iface = gr.Interface(fn=process_image,
-                     inputs=[gr.inputs.Image(type="filepath", label="Input Image"),
-                             gr.inputs.Radio(
-                                 [
-                                     'add 5 paths one by one',
-                                     'add 8 paths one by one',
-                                     'add [1,3,5,7] paths',
-                                     'add [1,2,4,8,16,32,32,32...] total 128 paths',
-                                     'add [1,2,4,8,16,32,32,32...] total 256 paths',
-                                 ],
-                                 type="value",
-                                 default='add 5 paths one by one',
-                                 label='experiment id'
-                            )
+                     inputs=[gr.inputs.Image(type="filepath", label="Input Image")
                      ],
                      outputs=[gr.outputs.Image(label="predicted depth", type="pil"),
                               gr.outputs.Image3D(label="3d mesh reconstruction", clear_color=[