class_docstr: A segmentation of a space into labeled objects
  
  Supports overlapping objects and cacheing. Retrieval can be as a
  single plane (legacy), as multiple planes and as sparse ijv.
class_docstr_tok: ["A","segmentation","of","a","space","into","labeled","objects","Supports","overlapping","objects","and","cacheing",".","Retrieval","can","be","as","a","single","plane","(","legacy",")",",","as","multiple","planes","and","as","sparse","ijv","."]
code: def has_dense(self):
      return self.__dense is not None
  
file_path: CellProfiler/src/subpackages/core/cellprofiler_core/object/_segmentation.py
imports: from cellprofiler_library.functions.segmentation import convert_dense_to_sparse
  from cellprofiler_library.functions.segmentation import convert_sparse_to_dense
  from cellprofiler_library.functions.segmentation import indices_from_dense
  from cellprofiler_library.functions.segmentation import dense_shape_from_sparse
  from cellprofiler_library.functions.segmentation import _validate_dense
  from cellprofiler_library.functions.segmentation import _validate_sparse
  from cellprofiler_library.functions.segmentation import _validate_dense_shape
label_desc: Use image node_id 4 for calling the Segmentation obj's underlying member method code with example usage: obj.has_dense() and returns: unknown