class_docstr: Compose transforms and handle all transformations regarding bounding boxes
  
  Args:
      transforms (list): list of transformations to compose.
      bbox_params (BboxParams): Parameters for bounding boxes transforms
      keypoint_params (KeypointParams): Parameters for keypoints transforms
      additional_targets (dict): Dict with keys - new target name, values - old target name. ex: {'image2': 'image'}
      p (float): probability of applying all list of transforms. Default: 1.0.
      is_check_shapes (bool): If True shapes consistency of images/mask/masks would be checked on each call. If you
          would like to disable this check - pass False (do it only if you are sure in your data consistency).
class_docstr_tok: ["Compose","transforms","and","handle","all","transformations","regarding","bounding","boxes","Args",":","transforms","(","list",")",":","list","of","transformations","to","compose",".","bbox_params","(","BboxParams",")",":","Parameters","for","bounding","boxes","transforms","keypoint_params","(","KeypointParams",")",":","Parameters","for","keypoints","transforms","additional_targets","(","dict",")",":","Dict","with","keys","-","new","target","name",",","values","-","old","target","name",".","ex",":","{","'image2","'",":","'image","'","}","p","(","float",")",":","probability","of","applying","all","list","of","transforms",".","Default",":","1.0.","is_check_shapes","(","bool",")",":","If","True","shapes","consistency","of","images\/mask\/masks","would","be","checked","on","each","call",".","If","you","would","like","to","disable","this","check","-","pass","False","(","do","it","only","if","you","are","sure","in","your","data","consistency",")","."]
code: def __init__(
      self,
      transforms: TransformsSeqType,
      bbox_params: typing.Optional[
          typing.Union[dict, "BboxParams"]
      ] = None,
      keypoint_params: typing.Optional[
          typing.Union[dict, "KeypointParams"]
      ] = None,
      additional_targets: typing.Optional[typing.Dict[str, str]] = None,
      p: float = 1.0,
      is_check_shapes: bool = True,
  ):
      super(Compose, self).__init__(transforms, p)
  
      self.processors: typing.Dict[
          str, typing.Union[BboxProcessor, KeypointsProcessor]
      ] = {}
      if bbox_params:
          if isinstance(bbox_params, dict):
              b_params = BboxParams(**bbox_params)
          elif isinstance(bbox_params, BboxParams):
              b_params = bbox_params
          else:
              raise ValueError(
                  "unknown format of bbox_params, please use `dict` or `BboxParams`"
              )
          self.processors["bboxes"] = BboxProcessor(
              b_params, additional_targets
          )
  
      if keypoint_params:
          if isinstance(keypoint_params, dict):
              k_params = KeypointParams(**keypoint_params)
          elif isinstance(keypoint_params, KeypointParams):
              k_params = keypoint_params
          else:
              raise ValueError(
                  "unknown format of keypoint_params, please use `dict` or `KeypointParams`"
              )
          self.processors["keypoints"] = KeypointsProcessor(
              k_params, additional_targets
          )
  
      if additional_targets is None:
          additional_targets = {}
  
      self.additional_targets = additional_targets
  
      for proc in self.processors.values():
          proc.ensure_transforms_valid(self.transforms)
  
      self.add_targets(additional_targets)
  
      self.is_check_args = True
      self._disable_check_args_for_transforms(self.transforms)
  
      self.is_check_shapes = is_check_shapes
  
imports: from __future__ import division
  import random
  import typing
  import warnings
  from collections import defaultdict
  import numpy
  from ..None import random_utils
  from .bbox_utils import BboxParams, BboxProcessor
  from .keypoints_utils import KeypointParams, KeypointsProcessor
  from .serialization import SERIALIZABLE_REGISTRY, Serializable, get_shortest_class_fullname, instantiate_nonserializable
  from .transforms_interface import BasicTransform
  from .utils import format_args, get_shape
label_desc: Use image node_id 1 to create a new Compose object from inherited base classes: BaseCompose with example: obj = Compose(transforms, bbox_params, keypoint_params, additional_targets, p, is_check_shapes)