Update app.py

app.py

@@ -48,14 +48,9 @@ def infer_full_vol(tensor, model):
 
 def infer_patch_based(tensor, model, patch_size=64, stride_length=32, stride_width=32, stride_depth=16, batch_size=10, num_worker=2):
     test_subject = tio.Subject(img = tio.ScalarImage(tensor=tensor.unsqueeze(0))) # adding channel dim while creating the TorchIO subject
-                
     overlap = np.subtract(patch_size, (stride_length, stride_width, stride_depth))
     
     def normaliser(batch):
-        """
-        Purpose: Normalise pixel intensities of each patch using the max values in the 3D patch
-        :param batch: 5D array (batch_size x channel x width x depth x height)
-        """
         for i in range(batch.shape[0]):
             batch[i] = batch[i] / batch[i].max()
         return batch
@@ -74,7 +69,6 @@ def infer_patch_based(tensor, model, patch_size=64, stride_length=32, stride_wid
             st.text(f"Processing batch {i + 1} of {total_batches}...")
             
             local_batch = normaliser(patches_batch['img'][tio.DATA].float())
-            local_batch = local_batch / local_batch.max()
             locations = patches_batch[tio.LOCATION]
 
             local_batch = torch.movedim(local_batch, -1, -3)