class_docstr: Implemented from https://stackoverflow.com/questions/31400769/bounding-box-of-numpy-array
  Removes all rows/columns/etc composed only of the provided values.
  
  mask_value: int
      Value to be cropped. Currently, only 0 supported.
  lead_data_group: str
      If provided, multiple data groups will be cropped according
      to the bounding box determined in the lead_data_group. Only
      applicable if different data_groups have the same shape. None
      by default, meaning that all data groups are cropped on an
      individual basis.
code: def load(self, kwargs):
      # Naming Parameters
      add_parameter(self, kwargs, "name", "CropValues")
  
      # Dropping Parameters
      add_parameter(self, kwargs, "mask_value", 0)
      add_parameter(self, kwargs, "lead_data_group", None)
  
      assert (
          self.mask_value == 0
      ), "Nonzero mask_value has not yet been implemented."
  
      self.slice_boundaries = []
      self.array_input = True
  
imports: import subprocess
  import os
  import numpy
  import itertools
  from deepneuro.preprocessing.preprocessor import Preprocessor
  from deepneuro.utilities.util import add_parameter, quotes
label_desc: Use image node_id 1 for calling the CropValues obj's underlying member method code with example usage: obj.load(kwargs) without return types