class_docstr: Internal class for `pyspark.ml.image.ImageSchema` attribute. Meant to be private and
  not to be instantized. Use `pyspark.ml.image.ImageSchema` attribute to access the
  APIs of this class.
class_docstr_tok: ["Internal","class","for","`","pyspark.ml.image.ImageSchema","`","attribute",".","Meant","to","be","private","and","not","to","be","instantized",".","Use","`","pyspark.ml.image.ImageSchema","`","attribute","to","access","the","APIs","of","this","class","."]
docstr: Returns the OpenCV type mapping supported.
  
  Returns
  -------
  dict
      a dictionary containing the OpenCV type mapping supported.
  
  .. versionadded:: 2.3.0
docstr_tok: ["Returns","the","OpenCV","type","mapping","supported",".","Returns","--","--","--","-","dict","a","dictionary","containing","the","OpenCV","type","mapping","supported",".","..","versionadded",":",":","2.3.0"]
code: def ocvTypes(self) -> Dict[str, int]:
      """
      Returns the OpenCV type mapping supported.
  
      Returns
      -------
      dict
          a dictionary containing the OpenCV type mapping supported.
  
      .. versionadded:: 2.3.0
      """
  
      if self._ocvTypes is None:
          ctx = SparkContext._active_spark_context
          assert ctx is not None and ctx._jvm is not None
          self._ocvTypes = dict(
              ctx._jvm.org.apache.spark.ml.image.ImageSchema.javaOcvTypes()
          )
      return self._ocvTypes
  
file_path: spark/python/pyspark/ml/image.py
imports: import sys
  from typing import Any, Dict, List, NoReturn, Optional, cast
  import numpy
  from pyspark import SparkContext
  from pyspark.sql.types import Row, StructType, _create_row, _parse_datatype_json_string
  from pyspark.sql import SparkSession
label_desc: Use image node_id 3 for calling the _ImageSchema obj's underlying member method code with example usage: obj.ocvTypes() and returns: self