class_docstr: Activation generator for a basic image model
class_docstr_tok: ["Activation","generator","for","a","basic","image","model"]
docstr: Initialize ImageActivationGenerator class."
  
  Args:
    normalize_image: A boolean indicating whether image pixels should be
      normalized to between 0 and 1.
docstr_tok: ["Initialize","ImageActivationGenerator","class",".","''","Args",":","normalize_image",":","A","boolean","indicating","whether","image","pixels","should","be","normalized","to","between","0","and","1","."]
code: def __init__(
      self,
      model,
      source_dir,
      acts_dir,
      max_examples=10,
      normalize_image=True,
  ):
      """Initialize ImageActivationGenerator class."
  
      Args:
        normalize_image: A boolean indicating whether image pixels should be
          normalized to between 0 and 1.
      """
      self.source_dir = source_dir
      self.normalize_image = normalize_image
      super(ImageActivationGenerator, self).__init__(
          model, acts_dir, max_examples
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from abc import ABCMeta
  from abc import abstractmethod
  from multiprocessing import dummy
  import os
  import os.path
  import numpy
  import PIL.Image
  import six
  import tensorflow
label_desc: Use image node_id 1 to create a new ImageActivationGenerator object from inherited base classes: ActivationGeneratorBase with example: obj = ImageActivationGenerator(model, source_dir, acts_dir, max_examples, normalize_image)