text: """
  Copyright (c) 2019 Intel Corporation
  
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at
  
        http://www.apache.org/licenses/LICENSE-2.0
  
  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License.
  """
  
  import numpy as np
  from .postprocessor import PostprocessorWithSpecificTargets
  from ..representation import BrainTumorSegmentationAnnotation, BrainTumorSegmentationPrediction
  from ..config import NumberField, ConfigError
  
  
  class ClipSegmentationMask(PostprocessorWithSpecificTargets):
      __provider__ = 'clip_segmentation_mask'
  
      annotation_types = (BrainTumorSegmentationAnnotation, )
      prediction_types = (BrainTumorSegmentationPrediction, )
  
      @classmethod
      def parameters(cls):
          parameters = super().parameters()
          parameters.update({
              'min_value': NumberField(value_type=int, min_value=0, optional=True, default=0, description="Min value"),
              'max_value': NumberField(value_type=int, description="Max value")
          })
          return parameters
  
      def configure(self):
          self.min_value = self.get_value_from_config('min_value')
          self.max_value = self.get_value_from_config('max_value')
          if self.max_value < self.min_value:
              raise ConfigError('max_value should be greater than min_value')
  
      def process_image(self, annotation, prediction):
          for target in annotation:
              target.mask = np.clip(target.mask, a_min=self.min_value, a_max=self.max_value)
  
          for target in prediction:
              target.mask = np.clip(target.mask, a_min=self.min_value, a_max=self.max_value)
  
          return annotation, prediction
  