parameters: (inputobject, name: str)
return_statement: return l_list
docstring: Returns a list of the specified attributes for the objects in the image.
  
      i: the input LabelImage
      name: the attribute name
docstring_summary: Returns a list of the specified attributes for the objects in the image.
docstring_tokens: Returns a list of the specified attributes for the objects in the image .
function: def attribute_list(inputobject, name: str):
      """Returns a list of the specified attributes for the objects in the image.
  
      i: the input LabelImage
      name: the attribute name
      """
      import itk
  
      img = itk.output(inputobject)
      relabel = itk.StatisticsRelabelLabelMapFilter[img].New(
          img, Attribute=name, ReverseOrdering=True, InPlace=False
      )
      relabel.UpdateLargestPossibleRegion()
      r = relabel.GetOutput()
      l_list: List[Any] = []
      # required because range is overloaded in this module
      import sys
      from builtins import range
  
      for i in range(1, r.GetNumberOfLabelObjects() + 1):
          l_list.append(r.GetLabelObject(i).__getattribute__("Get" + name)())
      return l_list
function_tokens: def attribute_list ( inputobject , name : str ) : import itk img = itk . output ( inputobject ) relabel = itk . StatisticsRelabelLabelMapFilter [ img ] . New ( img , Attribute = name , ReverseOrdering = True , InPlace = False ) relabel . UpdateLargestPossibleRegion ( ) r = relabel . GetOutput ( ) l_list : List [ Any ] = [ ] # required because range is overloaded in this module import sys from builtins import range for i in range ( 1 , r . GetNumberOfLabelObjects ( ) + 1 ) : l_list . append ( r . GetLabelObject ( i ) . __getattribute__ ( "Get" + name ) ( ) ) return l_list