code: def find_objects(input, max_label=0):
      """
      Find objects in a labeled array.
  
      Parameters
      ----------
      input : ndarray of ints
          Array containing objects defined by different labels. Labels with
          value 0 are ignored.
      max_label : int, optional
          Maximum label to be searched for in `input`. If max_label is not
          given, the positions of all objects are returned.
  
      Returns
      -------
      object_slices : list of tuples
          A list of tuples, with each tuple containing N slices (with N the
          dimension of the input array).  Slices correspond to the minimal
          parallelepiped that contains the object. If a number is missing,
          None is returned instead of a slice.
  
      See Also
      --------
      label, center_of_mass
  
      Notes
      -----
      This function is very useful for isolating a volume of interest inside
      a 3-D array, that cannot be "seen through".
  
      Examples
      --------
      >>> from scipy import ndimage
      >>> a = np.zeros((6,6), dtype=int)
      >>> a[2:4, 2:4] = 1
      >>> a[4, 4] = 1
      >>> a[:2, :3] = 2
      >>> a[0, 5] = 3
      >>> a
      array([[2, 2, 2, 0, 0, 3],
             [2, 2, 2, 0, 0, 0],
             [0, 0, 1, 1, 0, 0],
             [0, 0, 1, 1, 0, 0],
             [0, 0, 0, 0, 1, 0],
             [0, 0, 0, 0, 0, 0]])
      >>> ndimage.find_objects(a)
      [(slice(2, 5, None), slice(2, 5, None)), (slice(0, 2, None), slice(0, 3, None)), (slice(0, 1, None), slice(5, 6, None))]
      >>> ndimage.find_objects(a, max_label=2)
      [(slice(2, 5, None), slice(2, 5, None)), (slice(0, 2, None), slice(0, 3, None))]
      >>> ndimage.find_objects(a == 1, max_label=2)
      [(slice(2, 5, None), slice(2, 5, None)), None]
  
      >>> loc = ndimage.find_objects(a)[0]
      >>> a[loc]
      array([[1, 1, 0],
             [1, 1, 0],
             [0, 0, 1]])
  
      """
      input = numpy.asarray(input)
      if numpy.iscomplexobj(input):
          raise TypeError("Complex type not supported")
  
      if max_label < 1:
          max_label = input.max()
  
      return _nd_image.find_objects(input, max_label)
  
imports: from __future__ import division, print_function, absolute_import
  import numpy
  import numpy
  from .None import _ni_support
  from .None import _ni_label
  from .None import _nd_image
  from .None import morphology
label_desc: Use image node_id 2 for calling a global function with example usage: find_objects(input, max_label) and returns: _nd_image