Refactor model initialization and demo launch in app.py

app.py

@@ -85,26 +85,6 @@ def infer(
           temperature,
           ):
     
-    score_thresholds = [0.1, 0.2, 0.3, 0.4, 0.5]
-
-    device = "cuda" if torch.cuda.is_available() else "cpu"
-    
-    parser = main_mcc.get_args_parser()
-    parser.set_defaults(eval=True)
-
-    args = parser.parse_args()
-    
-    model = mcc_model.get_mcc_model(
-        occupancy_weight=1.0,
-        rgb_weight=0.01,
-        args=args,
-    )
-    
-    if device == "cuda":
-        model = model.cuda()
-
-    misc.load_model(args=args, model_without_ddp=model, optimizer=None, loss_scaler=None)
-
     rgb = image
     obj = load_obj(point_cloud.name)
 
@@ -178,15 +158,33 @@ def infer(
 
     return temp_file_name
 
+if __name__ == '__main__':
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    
+    parser = main_mcc.get_args_parser()
+    parser.set_defaults(eval=True)
+
+    args = parser.parse_args()
+    
+    model = mcc_model.get_mcc_model(
+        occupancy_weight=1.0,
+        rgb_weight=0.01,
+        args=args,
+    )
+    
+    if device == "cuda":
+        model = model.cuda()
+
+    misc.load_model(args=args, model_without_ddp=model, optimizer=None, loss_scaler=None)
 
-demo = gr.Interface(fn=infer, 
-                    inputs=[gr.Image(label="Input Image"),
-                            gr.File(label="Pointcloud File"),
-                            gr.File(label="Segmentation File"),
-                            gr.Slider(minimum=0.05, maximum=0.5, step=0.05, value=0.2, label="Granularity"),
-                            gr.Slider(minimum=0, maximum=1.0, step=0.1, value=0.1, label="Temperature")
-                            ], 
-                    outputs=[gr.outputs.File(label="Point Cloud Json")],
-                    examples=[["demo/quest2.jpg", "demo/quest2.obj", "demo/quest2_seg.png", 0.2, 0.1]],
-                    cache_examples=True)
-demo.launch(server_name="0.0.0.0", server_port=7860)
+    demo = gr.Interface(fn=infer, 
+                        inputs=[gr.Image(label="Input Image"),
+                                gr.File(label="Pointcloud File"),
+                                gr.File(label="Segmentation File"),
+                                gr.Slider(minimum=0.05, maximum=0.5, step=0.05, value=0.2, label="Granularity"),
+                                gr.Slider(minimum=0, maximum=1.0, step=0.1, value=0.1, label="Temperature")
+                                ], 
+                        outputs=[gr.outputs.File(label="Point Cloud")],
+                        examples=[["demo/quest2.jpg", "demo/quest2.obj", "demo/quest2_seg.png", 0.2, 0.1]],
+                        cache_examples=True)
+    demo.launch(server_name="0.0.0.0", server_port=7860)