class_docstr: Check if the average of each color channel is the same between the train and test dataset.
class_docstr_tok: ["Check","if","the","average","of","each","color","channel","is","the","same","between","the","train","and","test","dataset","."]
docstr: Initialize the color_averages dict and pixel counter dict.
docstr_tok: ["Initialize","the","color_averages","dict","and","pixel","counter","dict","."]
code: def initialize_run(self, context: Context):
      """Initialize the color_averages dict and pixel counter dict."""
      self._color_averages = init_color_averages_dict()
      self._pixel_count = init_pixel_counts_dict()
  
imports: import typing
  import numpy
  from deepchecks.core.check_result import CheckResult
  from deepchecks.core.checks import DatasetKind
  from deepchecks.core.condition import ConditionCategory
  from deepchecks.vision.base_checks import TrainTestCheck
  from deepchecks.vision.context import Context
  from deepchecks.vision.vision_data.batch_wrapper import BatchWrapper
  from deepchecks.vision.datasets.detection.coco_torch import load_dataset
  import pandas
  import plotly.express
  from deepchecks.core import ConditionResult
label_desc: Use image node_id 2 for calling the ColorAveragesCheck obj's underlying member method code with example usage: obj.initialize_run(context) without return types