class_docstr: Keras layer for applying regression values to boxes.
      
class_docstr_tok: ["Keras","layer","for","applying","regression","values","to","boxes","."]
docstr: Initializer for the RegressBoxes layer.
  
  Args
      mean: The mean value of the regression values which was used for normalization.
      std: The standard value of the regression values which was used for normalization.
docstr_tok: ["Initializer","for","the","RegressBoxes","layer",".","Args","mean",":","The","mean","value","of","the","regression","values","which","was","used","for","normalization",".","std",":","The","standard","value","of","the","regression","values","which","was","used","for","normalization","."]
code: def __init__(self, mean=None, std=None, *args, **kwargs):
      """Initializer for the RegressBoxes layer.
  
      Args
          mean: The mean value of the regression values which was used for normalization.
          std: The standard value of the regression values which was used for normalization.
      """
      if mean is None:
          mean = np.array([0, 0, 0, 0])
      if std is None:
          std = np.array([0.2, 0.2, 0.2, 0.2])
  
      if isinstance(mean, (list, tuple)):
          mean = np.array(mean)
      elif not isinstance(mean, np.ndarray):
          raise ValueError(
              "Expected mean to be a np.ndarray, list or tuple. Received: {}".format(
                  type(mean)
              )
          )
  
      if isinstance(std, (list, tuple)):
          std = np.array(std)
      elif not isinstance(std, np.ndarray):
          raise ValueError(
              "Expected std to be a np.ndarray, list or tuple. Received: {}".format(
                  type(std)
              )
          )
  
      self.mean = mean
      self.std = std
      super(RegressBoxes, self).__init__(*args, **kwargs)
  
imports: import tensorflow
  from tensorflow import keras
  from ..None import backend
  from ..utils import anchors
  import numpy
label_desc: Use image node_id 1 to create a new RegressBoxes object from inherited base classes: keras.layers with example: obj = RegressBoxes(mean, std)