:py:mod:`anomalib.models.reverse_distillation.anomaly_map`
==========================================================

.. py:module:: anomalib.models.reverse_distillation.anomaly_map

.. autoapi-nested-parse::

   Compute Anomaly map.



Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   anomalib.models.reverse_distillation.anomaly_map.AnomalyMapGenerator




.. py:class:: AnomalyMapGenerator(image_size: Union[omegaconf.ListConfig, Tuple], sigma: int = 4, mode: str = 'multiply')

   Generate Anomaly Heatmap.

   :param image_size: Size of original image used for upscaling the anomaly map.
   :type image_size: Union[ListConfig, Tuple]
   :param sigma: Standard deviation of the gaussian kernel used to smooth anomaly map.
   :type sigma: int
   :param mode: Operation used to generate anomaly map. Options are `add` and `multiply`.
                Defaults to "multiply".
   :type mode: str, optional

   :raises ValueError: In case modes other than multiply and add are passed.

   .. py:method:: __call__(student_features: List[torch.Tensor], teacher_features: List[torch.Tensor]) -> torch.Tensor

      Computes anomaly map given encoder and decoder features.

      :param student_features: List of encoder features
      :type student_features: List[Tensor]
      :param teacher_features: List of decoder features
      :type teacher_features: List[Tensor]

      :returns: Anomaly maps of length batch.
      :rtype: Tensor