Update app.py

app.py

@@ -99,28 +99,19 @@ class model:
             
             
         nucleus_image = image['image'].convert('L')
-        #protein_image = image['mask'].split()[3]
         protein_image = image['mask'].convert('L')
 
         to_tensor = T.ToTensor()
         nucleus_image = to_tensor(nucleus_image)
         protein_image = to_tensor(protein_image)
-        #stacked_images = torch.stack([nucleus_image, protein_image], dim=0)
-        #processed_images = process_image(stacked_images, dataset)
+        stacked_images = torch.stack([nucleus_image, protein_image], dim=0)
+        processed_images = process_image(stacked_images, dataset)
 
-        #nucleus_image = processed_images[0].unsqueeze(0)
-        #protein_image = processed_images[1].unsqueeze(0)
-        #protein_image = protein_image/torch.max(protein_image)
-        #protein_image = 1 - protein_image  
+        nucleus_image = processed_images[0].unsqueeze(0)
+        protein_image = processed_images[1].unsqueeze(0)
+        protein_image = protein_image/torch.max(protein_image)
+        protein_image = 1 - protein_image  
         
-        nucleus_image = nucleus_image.unsqueeze(0)
-        nucleus_image = process_image(nucleus_image, dataset, 'nucleus')
-        protein_image = protein_image.unsqueeze(0)
-        print(nucleus.shape)
-        print(protein_image.shape)
-        #protein_image = 1.0*(protein_image > .01)
-        
-        print('test1')
         formatted_predicted_sequence = run_sequence_prediction(
             sequence_input=sequence_input,
             nucleus_image=nucleus_image,