:py:mod:`anomalib.models.stfpm.torch_model`
===========================================

.. py:module:: anomalib.models.stfpm.torch_model

.. autoapi-nested-parse::

   PyTorch model for the STFPM model implementation.



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

Classes
~~~~~~~

.. autoapisummary::

   anomalib.models.stfpm.torch_model.STFPMModel




.. py:class:: STFPMModel(layers: List[str], input_size: Tuple[int, int], backbone: str = 'resnet18')

   Bases: :py:obj:`torch.nn.Module`

   STFPM: Student-Teacher Feature Pyramid Matching for Unsupervised Anomaly Detection.

   :param layers: Layers used for feature extraction
   :type layers: List[str]
   :param input_size: Input size for the model.
   :type input_size: Tuple[int, int]
   :param backbone: Pre-trained model backbone. Defaults to "resnet18".
   :type backbone: str, optional

   .. py:method:: forward(images)

      Forward-pass images into the network.

      During the training mode the model extracts the features from the teacher and student networks.
      During the evaluation mode, it returns the predicted anomaly map.

      :param images: Batch of images.
      :type images: Tensor

      :returns: Teacher and student features when in training mode, otherwise the predicted anomaly maps.