class_docstr: Dictionary-based wrapper of :py:class:`monai.apps.pathology.transforms.post.array.GenerateSuccinctContour`.
  Converts SciPy-style contours (generated by skimage.measure.find_contours) to a more succinct version which
  only includes the pixels to which lines need to be drawn (i.e. not the intervening pixels along each line).
  
  Args:
      keys: keys of the corresponding items to be transformed.
      height: height of bounding box, used to detect direction of line segment.
      width: width of bounding box, used to detect direction of line segment.
      allow_missing_keys: don't raise exception if key is missing.
code: def __init__(
      self,
      keys: KeysCollection,
      height: int,
      width: int,
      allow_missing_keys: bool = False,
  ) -> None:
      super().__init__(keys, allow_missing_keys)
      self.converter = GenerateSuccinctContour(
          height=height, width=width
      )
  
imports: from __future__ import annotations
  from collections.abc import Callable, Hashable, Mapping
  import numpy
  import torch
  from monai.apps.pathology.transforms.post.array import GenerateDistanceMap, GenerateInstanceBorder, GenerateInstanceCentroid, GenerateInstanceContour, GenerateInstanceType, GenerateSuccinctContour, GenerateWatershedMarkers, GenerateWatershedMask, HoVerNetInstanceMapPostProcessing, HoVerNetNuclearTypePostProcessing, Watershed
  from monai.config.type_definitions import DtypeLike, KeysCollection, NdarrayOrTensor
  from monai.transforms.transform import MapTransform, Transform
  from monai.utils import optional_import
  from monai.utils.enums import HoVerNetBranch
label_desc: Use image node_id 1 to create a new GenerateSuccinctContourd object from inherited base classes: MapTransform with example: obj = GenerateSuccinctContourd(keys, height, width, allow_missing_keys)