anchor.diff:          print("Input format: <filepath> <minimum size of detected shape in pixels> <threshold between 0 and 1>")
           return
   
  -    filepath = sys.argv[1]
  +      filepath = sys.argv[1]
       minimum_pixel_size = int(sys.argv[2])
       threshold = float(sys.argv[3])
   
  
positive.code:     total_pixels_in_shape = sum(segmented == i)
  
      if total_pixels_in_shape > minimum_pixel_size:
          convex_hull = convex_hull_image(segmented == i)
          area = sum(convex_hull)
  ----
  
  Next we iterate over each shape value, count the pixels and filter out shapes that don't have enough
  
  
  == Final code
  
  
negative.code: 
  == Input data and some restrictions
  
  We assume that the images we will be processing are scans of white A4 sheets of paper. 
  
  Another assumption we make is that shapes will be convex. What does that mean for us? 
  It means that we will be able to use convex hulls to compute areas of the found shapes and the shapes won't be too complicated.
  