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,