code: def test_classify_false():
      labels = numpy.zeros((10, 10), int)
      labels[4:7, 4:7] = 1
      workspace, module = make_workspace({INPUT_OBJECTS: labels})
      module.x_name.value = INPUT_OBJECTS
      module.y_name.value = OUTPUT_OBJECTS
      with make_classifier(
          module, numpy.ones(1, int) * 2, classes=[1, 2]
      ):
          workspace.measurements[INPUT_OBJECTS, TEST_FTR] = numpy.zeros(
              1
          )
          module.run(workspace)
          output_objects = workspace.object_set.get_objects(
              OUTPUT_OBJECTS
          )
          assert output_objects.count == 0
  
imports: import contextlib
  import io
  import os
  import pickle
  import tempfile
  import numpy
  import pytest
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  import cellprofiler_core.modules
  from cellprofiler_core.constants.measurement import FF_PARENT, FF_COUNT, FF_CHILDREN_COUNT, M_LOCATION_CENTER_X, M_LOCATION_CENTER_Y, M_LOCATION_CENTER_Z, M_NUMBER_OBJECT_NUMBER
  import cellprofiler.modules.filterobjects
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.preferences
  import cellprofiler_core.workspace
  import tests.frontend.modules
label_desc: Use image node_id 31 for calling a global function with example usage: test_classify_false() without return types