class_docstr: Dictionary-based wrapper of :py:class:`monai.apps.pathology.transforms.ExtractHEStains`.
  Class to extract a target stain from an image, using stain deconvolution.
  
  Args:
      keys: keys of the corresponding items to be transformed.
          See also: :py:class:`monai.transforms.compose.MapTransform`
      tli: transmitted light intensity. Defaults to 240.
      alpha: tolerance in percentile for the pseudo-min (alpha percentile)
          and pseudo-max (100 - alpha percentile). Defaults to 1.
      beta: absorbance threshold for transparent pixels. Defaults to 0.15
      max_cref: reference maximum stain concentrations for Hematoxylin & Eosin (H&E).
          Defaults to (1.9705, 1.0308).
      allow_missing_keys: don't raise exception if key is missing.
code: def __init__(
      self,
      keys: KeysCollection,
      tli: float = 240,
      alpha: float = 1,
      beta: float = 0.15,
      max_cref: tuple | np.ndarray = (1.9705, 1.0308),
      allow_missing_keys: bool = False,
  ) -> None:
      super().__init__(keys, allow_missing_keys)
      self.extractor = ExtractHEStains(
          tli=tli, alpha=alpha, beta=beta, max_cref=max_cref
      )
  
file_path: MONAI/monai/apps/pathology/transforms/stain/dictionary.py
imports: from __future__ import annotations
  from collections.abc import Hashable, Mapping
  import numpy
  from monai.config import KeysCollection
  from monai.transforms.transform import MapTransform
  from .array import ExtractHEStains, NormalizeHEStains
label_desc: Use image node_id 1 to create a new ExtractHEStainsd object from inherited base classes: MapTransform with example: obj = ExtractHEStainsd(keys, tli, alpha, beta, max_cref, allow_missing_keys)