Update app.py

app.py

@@ -32,6 +32,8 @@ if not torch.cuda.is_available():
     cfg.MODEL.DEVICE='cpu'
 
 predictor = DefaultPredictor(cfg)
+my_metadata = MetadataCatalog.get("car_dataset_val")
+my_metadata.thing_classes = ["damage"]
 
 def inference(image):
     print(image.height)
@@ -41,7 +43,7 @@ def inference(image):
     img = np.array(image.resize((500, height)))
     outputs = predictor(img)
     v = Visualizer(img[:, :, ::-1],
-                   #metadata=val_metadata_dicts, 
+                   metadata=my_metadata, 
                    scale=0.5, 
                    instance_mode=ColorMode.SEGMENTATION   # remove the colors of unsegmented pixels. This option is only available for segmentation models
     )