class_docstr: Randomly Drop Channels in the input Image.
  
  Args:
      channel_drop_range (int, int): range from which we choose the number of channels to drop.
      fill_value (int, float): pixel value for the dropped channel.
      p (float): probability of applying the transform. Default: 0.5.
  
  Targets:
      image
  
  Image types:
      uint8, uint16, unit32, float32
class_docstr_tok: ["Randomly","Drop","Channels","in","the","input","Image",".","Args",":","channel_drop_range","(","int",",","int",")",":","range","from","which","we","choose","the","number","of","channels","to","drop",".","fill_value","(","int",",","float",")",":","pixel","value","for","the","dropped","channel",".","p","(","float",")",":","probability","of","applying","the","transform",".","Default",":","0.5",".","Targets",":","image","Image","types",":","uint8",",","uint16",",","unit32",",","float32"]
code: def get_params_dependent_on_targets(self, params: Mapping[str, Any]):
      img = params["image"]
  
      num_channels = img.shape[-1]
  
      if len(img.shape) == 2 or num_channels == 1:
          raise NotImplementedError(
              "Images has one channel. ChannelDropout is not defined."
          )
  
      if self.max_channels >= num_channels:
          raise ValueError(
              "Can not drop all channels in ChannelDropout."
          )
  
      num_drop_channels = random.randint(
          self.min_channels, self.max_channels
      )
  
      channels_to_drop = random.sample(
          range(num_channels), k=num_drop_channels
      )
  
      return {"channels_to_drop": channels_to_drop}
  
file_path: albumentations/albumentations/augmentations/dropout/channel_dropout.py
imports: import random
  from typing import Any, Mapping, Tuple, Union
  import numpy
  from albumentations.core.transforms_interface import ImageOnlyTransform
  from .functional import channel_dropout
label_desc: Use image node_id 3 for calling the ChannelDropout obj's underlying member method code with example usage: obj.get_params_dependent_on_targets(params) and returns: dict