Source code for sparknlp.base.image_assembler

#  Copyright 2017-2022 John Snow Labs
#
#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
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#     http://www.apache.org/licenses/LICENSE-2.0
#
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#  distributed under the License is distributed on an "AS IS" BASIS,
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"""Contains classes for the ImageAssembler."""

from pyspark import keyword_only
from pyspark.ml.param import TypeConverters, Params, Param

from sparknlp.common import AnnotatorType
from sparknlp.internal import AnnotatorTransformer


[docs]class ImageAssembler(AnnotatorTransformer):
    """Prepares images read by Spark into a format that is processable by Spark NLP.
    This component is needed to process images.

    ====================== ======================
    Input Annotation types Output Annotation type
    ====================== ======================
    ``NONE``               ``IMAGE``
    ====================== ======================

    Parameters
    ----------
    inputCol
        Input column name
    outputCol
        Output column name

    Examples
    --------
    >>> import sparknlp
    >>> from sparknlp.base import *
    >>> from pyspark.ml import Pipeline
    >>> data = spark.read.format("image").load("./tmp/images/").toDF("image")
    >>> imageAssembler = ImageAssembler().setInputCol("image").setOutputCol("image_assembler")
    >>> result = imageAssembler.transform(data)
    >>> result.select("image_assembler").show()
    >>> result.select("image_assembler").printSchema()
    root
     |-- image_assembler: array (nullable = true)
     |    |-- element: struct (containsNull = true)
     |    |    |-- annotatorType: string (nullable = true)
     |    |    |-- origin: string (nullable = true)
     |    |    |-- height: integer (nullable = true)
     |    |    |-- width: integer (nullable = true)
     |    |    |-- nChannels: integer (nullable = true)
     |    |    |-- mode: integer (nullable = true)
     |    |    |-- result: binary (nullable = true)
     |    |    |-- metadata: map (nullable = true)
     |    |    |    |-- key: string
     |    |    |    |-- value: string (valueContainsNull = true)
    """

    outputAnnotatorType = AnnotatorType.IMAGE

    inputCol = Param(Params._dummy(), "inputCol", "input column name", typeConverter=TypeConverters.toString)
    outputCol = Param(Params._dummy(), "outputCol", "output column name", typeConverter=TypeConverters.toString)
    name = 'ImageAssembler'

    @keyword_only
    def __init__(self):
        super(ImageAssembler, self).__init__(classname="com.johnsnowlabs.nlp.ImageAssembler")
        self._setDefault(outputCol="image_assembler", inputCol='image')

    @keyword_only
    def setParams(self):
        kwargs = self._input_kwargs
        return self._set(**kwargs)

[docs]    def setInputCol(self, value):
        """Sets input column name.

        Parameters
        ----------
        value : str
            Name of the input column that has image format loaded via spark.read.format("image").load(PATH)
        """
        return self._set(inputCol=value)

[docs]    def setOutputCol(self, value):
        """Sets output column name.

        Parameters
        ----------
        value : str
            Name of the Output Column
        """
        return self._set(outputCol=value)

[docs]    def getOutputCol(self):
        """Gets output column name of annotations."""
        return self.getOrDefault(self.outputCol)