Update app.py

app.py

@@ -20,6 +20,8 @@ import torch.nn as nn
 from torchvision import transforms,models #, datasets
 SEED = 1234
 
+print("hello world")
+
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 num_classes = 15
 criterion = nn.CrossEntropyLoss()
@@ -33,14 +35,6 @@ model.fc = nn.Linear(num_ftrs, num_classes)
 model = model.to(device)
 
 
-
-# set Detectron2 
-cfg = get_cfg()
-cfg.merge_from_file(model_zoo.get_config_file("COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml"))
-cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5
-cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url("COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml")
-predictor = DefaultPredictor(cfg)
-
 # build Gradio interface 
 def segment_image(image):
     outputs = predictor(image)