update app.py

app.py

@@ -21,7 +21,7 @@ model = SegResNet(
 )
 
 model.load_state_dict(
-    torch.load("model.pt", map_location=torch.device('cpu'))
+    torch.load("weights/model.pt", map_location=torch.device('cpu'))
 )
 
 # define inference method
@@ -68,7 +68,7 @@ import torchvision
 def load_sample(index):
     #sample_index = index
 
-    sample = torch.load(f"val{index-1}.pt")
+    sample = torch.load(f"samples/val{index-1}.pt")
     imgs = []
     for i in range(4):
         imgs.append(sample["image"][i, :, :, 70])
@@ -91,7 +91,7 @@ def load_sample(index):
 
 def predict(sample_index):
     print(sample_index)
-    sample = torch.load(f"val{sample_index-1}.pt")
+    sample = torch.load(f"samples/val{sample_index-1}.pt")
     model.eval()
     with torch.no_grad():
         # select one image to evaluate and visualize the model output