aagoluoglu commited on
Commit
3834b22
·
1 Parent(s): c54d968

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +4 -2
app.py CHANGED
@@ -116,6 +116,7 @@ def server(input: Inputs, output: Outputs, session: Session):
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  def uploaded_image_path() -> str:
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  """Returns the path to the uploaded image"""
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  if input.tile_image() is not None:
 
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  return input.tile_image()[0]['datapath'] # Assuming multiple=False
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  else:
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  return "" # No image uploaded
@@ -126,6 +127,7 @@ def server(input: Inputs, output: Outputs, session: Session):
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  img_src = uploaded_image_path()
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  if img_src:
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  img: ImgData = {"src": str(dir / uploaded_image_path()), "width": "100px"}
 
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  return img
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  else:
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  return None # Return an empty string if no image is uploaded
@@ -232,12 +234,12 @@ def server(input: Inputs, output: Outputs, session: Session):
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  if image is None or prob is None or prediction is None:
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  # Return a placeholder plot or message
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  fig, ax = plt.subplots()
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- ax.text(0.5, 0.5, "Upload a square image to see predictions. If the image is not a square, the image will be cropped to a square, taking the top left portion of the image. Predictions will take a few moments to load.", fontsize=12, ha="center")
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  ax.axis("off") # Hide axis
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  plt.tight_layout()
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  return fig
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- fig, axes = plt.subplots(1, 4, figsize=(15, 5))
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  # Extract the image data
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  #image_data = image.cpu().detach().numpy()
 
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  def uploaded_image_path() -> str:
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  """Returns the path to the uploaded image"""
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  if input.tile_image() is not None:
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+ print ("IMAGE PATH!!!!!!", input.tile_image()[0]['datapath'])
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  return input.tile_image()[0]['datapath'] # Assuming multiple=False
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  else:
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  return "" # No image uploaded
 
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  img_src = uploaded_image_path()
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  if img_src:
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  img: ImgData = {"src": str(dir / uploaded_image_path()), "width": "100px"}
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+ print("IMAGE", img)
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  return img
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  else:
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  return None # Return an empty string if no image is uploaded
 
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  if image is None or prob is None or prediction is None:
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  # Return a placeholder plot or message
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  fig, ax = plt.subplots()
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+ ax.text(0.5, 0.5, "Upload a square image to see predictions. Predictions will take a few moments to load.", fontsize=12, ha="center")
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  ax.axis("off") # Hide axis
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  plt.tight_layout()
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  return fig
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+ fig, axes = plt.subplots(1, 4, figsize=(15, 15))
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  # Extract the image data
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  #image_data = image.cpu().detach().numpy()