class_docstr: This class is intended for the EVAC+ model.
class_docstr_tok: ["This","class","is","intended","for","the","EVAC+","model","."]
docstr: The model was pre-trained for usage on
  brain extraction of T1 images.
  
  This model is designed to take as input
  a T1 weighted image.
  
  Parameters
  ----------
  verbose : bool (optional)
      Whether to show information about the processing.
      Default: False
  
  References
  ----------
  ..  [1] Park, J.S., Fadnavis, S., & Garyfallidis, E. (2022).
          EVAC+: Multi-scale V-net with Deep Feature
          CRF Layers for Brain Extraction.
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code: def __init__(self, verbose=False):
      r"""
      The model was pre-trained for usage on
      brain extraction of T1 images.
  
      This model is designed to take as input
      a T1 weighted image.
  
      Parameters
      ----------
      verbose : bool (optional)
          Whether to show information about the processing.
          Default: False
  
      References
      ----------
      ..  [1] Park, J.S., Fadnavis, S., & Garyfallidis, E. (2022).
              EVAC+: Multi-scale V-net with Deep Feature
              CRF Layers for Brain Extraction.
      """
  
      if not have_tf:
          raise tf()
  
      log_level = "INFO" if verbose else "CRITICAL"
      set_logger_level(log_level, logger)
  
      # EVAC+ network load
  
      self.model = init_model()
      self.fetch_default_weights()
  
imports: import logging
  import numpy
  from dipy.data import get_fnames
  from dipy.testing.decorators import doctest_skip_parser
  from dipy.utils.optpkg import optional_package
  from dipy.align.reslice import reslice
  from dipy.nn.utils import normalize, set_logger_level, transform_img
  from dipy.nn.utils import recover_img, correct_minor_errors
label_desc: Use image node_id 1 to create a new EVACPlus object  with example: obj = EVACPlus(verbose)