:py:mod:`anomalib.post_processing.visualizer`
=============================================

.. py:module:: anomalib.post_processing.visualizer

.. autoapi-nested-parse::

   Anomaly Visualization.



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

Classes
~~~~~~~

.. autoapisummary::

   anomalib.post_processing.visualizer.ImageResult
   anomalib.post_processing.visualizer.Visualizer
   anomalib.post_processing.visualizer.ImageGrid




.. py:class:: ImageResult

   Collection of data needed to visualize the predictions for an image.

   .. py:attribute:: image
      :annotation: :numpy.ndarray

      

   .. py:attribute:: pred_score
      :annotation: :float

      

   .. py:attribute:: pred_label
      :annotation: :str

      

   .. py:attribute:: anomaly_map
      :annotation: :numpy.ndarray

      

   .. py:attribute:: gt_mask
      :annotation: :Optional[numpy.ndarray]

      

   .. py:attribute:: pred_mask
      :annotation: :Optional[numpy.ndarray]

      

   .. py:attribute:: heat_map
      :annotation: :numpy.ndarray

      

   .. py:attribute:: segmentations
      :annotation: :numpy.ndarray

      

   .. py:method:: __post_init__(self)

      Generate heatmap overlay and segmentations, convert masks to images.



.. py:class:: Visualizer(mode: str, task: str)

   Class that handles the logic of composing the visualizations.

   :param mode: visualization mode, either "full" or "simple"
   :type mode: str
   :param task: task type, either "segmentation" or "classification"
   :type task: str

   .. py:method:: visualize_batch(self, batch: Dict) -> Iterator[numpy.ndarray]

      Generator that yields a visualization result for each item in the batch.

      :param batch: Dictionary containing the ground truth and predictions of a batch of images.
      :type batch: Dict

      :returns: Generator that yields a display-ready visualization for each image.


   .. py:method:: visualize_image(self, image_result: ImageResult) -> numpy.ndarray

      Generate the visualization for an image.

      :param image_result: GT and Prediction data for a single image.
      :type image_result: ImageResult

      :returns: The full or simple visualization for the image, depending on the specified mode.


   .. py:method:: _visualize_full(self, image_result: ImageResult)

      Generate the full set of visualization for an image.

      The full visualization mode shows a grid with subplots that contain the original image, the GT mask (if
      available), the predicted heat map, the predicted segmentation mask (if available), and the predicted
      segmentations (if available).

      :param image_result: GT and Prediction data for a single image.
      :type image_result: ImageResult

      :returns: An image showing the full set of visualizations for the input image.


   .. py:method:: _visualize_simple(self, image_result)

      Generate a simple visualization for an image.

      The simple visualization mode only shows the model's predictions in a single image.

      :param image_result: GT and Prediction data for a single image.
      :type image_result: ImageResult

      :returns: An image showing the simple visualization for the input image.


   .. py:method:: show(title: str, image: numpy.ndarray, delay: int = 0)
      :staticmethod:

      Show an image on the screen.

      :param title: Title that will be given to the window showing the image.
      :type title: str
      :param image: Image that will be shown in the window.
      :type image: np.ndarray
      :param delay: Delay in milliseconds to wait for keystroke. 0 for infinite.
      :type delay: int


   .. py:method:: save(file_path: pathlib.Path, image: numpy.ndarray)
      :staticmethod:

      Save an image to the file system.

      :param file_path: Path to which the image will be saved.
      :type file_path: Path
      :param image: Image that will be saved to the file system.
      :type image: np.ndarray



.. py:class:: ImageGrid

   Helper class that compiles multiple images into a grid using subplots.

   Individual images can be added with the `add_image` method. When all images have been added, the `generate` method
   must be called to compile the image grid and obtain the final visualization.

   .. py:method:: add_image(self, image: numpy.ndarray, title: Optional[str] = None, color_map: Optional[str] = None)

      Add an image to the grid.

      :param image: Image which should be added to the figure.
      :type image: np.ndarray
      :param title: Image title shown on the plot.
      :type title: str
      :param color_map: Name of matplotlib color map used to map scalar data to colours. Defaults to None.
      :type color_map: Optional[str]


   .. py:method:: generate(self) -> numpy.ndarray

      Generate the image.

      :returns: Image consisting of a grid of added images and their title.