Update app.py

app.py

@@ -13,8 +13,8 @@ device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 # Load the image processor and the model
 # The model is loaded once and cached for all subsequent inference calls
 print("Loading model...")
-processor = AutoImageProcessor.from_pretrained("./mask2former_model")
-model = Mask2FormerForUniversalSegmentation.from_pretrained("./mask2former_model").to(device)
+processor = AutoImageProcessor.from_pretrained("facebook/mask2former-swin-tiny-coco-instance")
+model = Mask2FormerForUniversalSegmentation.from_pretrained("facebook/mask2former-swin-tiny-coco-instance").to(device)
 print("Model loaded successfully.")
 
 # Define the classes we are interested in.