class_docstr: Converts various DensePose predictor outputs to DensePose results.
  Each DensePose predictor output type has to register its convertion strategy.
class_docstr_tok: ["Converts","various","DensePose","predictor","outputs","to","DensePose","results",".","Each","DensePose","predictor","output","type","has","to","register","its","convertion","strategy","."]
docstr: Performs an horizontal flip on DensePose predictor outputs.
  Does recursive lookup for base classes, so there's no need
  for explicit registration for derived classes.
  
  Args:
      predictor_outputs: DensePose predictor output to be converted to BitMasks
      transform_data: Anything useful for the flip
  Return:
      An instance of the same type as predictor_outputs
docstr_tok: ["Performs","an","horizontal","flip","on","DensePose","predictor","outputs",".","Does","recursive","lookup","for","base","classes",",","so","there","'s","no","need","for","explicit","registration","for","derived","classes",".","Args",":","predictor_outputs",":","DensePose","predictor","output","to","be","converted","to","BitMasks","transform_data",":","Anything","useful","for","the","flip","Return",":","An","instance","of","the","same","type","as","predictor_outputs"]
code: def convert(
      cls, predictor_outputs: Any, transform_data: Any, *args, **kwargs
  ):
      """
      Performs an horizontal flip on DensePose predictor outputs.
      Does recursive lookup for base classes, so there's no need
      for explicit registration for derived classes.
  
      Args:
          predictor_outputs: DensePose predictor output to be converted to BitMasks
          transform_data: Anything useful for the flip
      Return:
          An instance of the same type as predictor_outputs
      """
      return super(HFlipConverter, cls).convert(
          predictor_outputs, transform_data, *args, **kwargs
      )
  
imports: from typing import Any
  from .base import BaseConverter
label_desc: Use image node_id 1 for calling the HFlipConverter obj's underlying member method code with example usage: obj.convert(cls, predictor_outputs, transform_data) and returns: super