aigarmic.model
==============

.. py:module:: aigarmic.model

.. autoapi-nested-parse::

   Implementation of Model classes



Classes
-------

.. autoapisummary::

   aigarmic.model.Model
   aigarmic.model.KerasModel
   aigarmic.model.SoftmaxModel
   aigarmic.model.BinaryModel
   aigarmic.model.BinaryNestedModel


Functions
---------

.. autoapisummary::

   aigarmic.model.convert_cv2_to_keras


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

.. py:function:: convert_cv2_to_keras(image, size_x=160, size_y=160) -> numpy.ndarray

   Convert a cv2 image to a keras image

   :param image: Image loaded using cv2.imread
   :param size_x: Width to resize image to (pixels)
   :param size_y: Height to resize image to (pixels)
   :return: Image as a numpy array


.. py:class:: Model(key: Optional[list[str]])

   Bases: :py:obj:`abc.ABC`


   Helper class that provides a standard way to create an ABC using
   inheritance.


   .. py:method:: get_key() -> list[str]

      Return key to convert model output to human-readable label
      :return:



   .. py:method:: predict(image) -> dict
      :abstractmethod:



.. py:class:: KerasModel(path: str, trained_x: int, trained_y: int, key: Optional[list[str]])

   Bases: :py:obj:`Model`


   Helper class that provides a standard way to create an ABC using
   inheritance.


   .. py:method:: load_model(path: str) -> None

      Load a keras model from file

      :param path: path to saved model



   .. py:method:: predict(image: numpy.ndarray) -> dict
      :abstractmethod:



.. py:class:: SoftmaxModel(path: str, trained_x: int, trained_y: int, key: Optional[list[str]])

   Bases: :py:obj:`KerasModel`


   SoftmaxModel is a one-stop model when more than one growth category is present, e.g.:
   ['No growth', 'Poor growth', 'Good growth']


   .. py:method:: predict(image: numpy.ndarray) -> dict

      Predict growth category from image

      :param image: loaded using cv2.imread
      :return: dictionary with keys 'prediction', 'score', 'growth_code', 'growth', 'accuracy'



.. py:class:: BinaryModel(path: str, trained_x: int, trained_y: int, key: Optional[list[str]], threshold: float = 0.5)

   Bases: :py:obj:`KerasModel`


   Helper class that provides a standard way to create an ABC using
   inheritance.


   .. py:method:: predict(image: numpy.ndarray) -> dict

      Predict growth category from image

      :param image: image loaded using cv2.imread
      :return: dictionary with keys 'prediction', 'score', 'growth_code', 'growth', 'accuracy'



.. py:class:: BinaryNestedModel(first_line_model: BinaryModel, second_line_model: BinaryModel, first_model_accuracy_acceptance: float = 0.9, suppress_first_model_accuracy_check: bool = False)

   Bases: :py:obj:`Model`


   Helper class that provides a standard way to create an ABC using
   inheritance.


   .. py:method:: predict(image: numpy.ndarray) -> dict

      Predict colony growth from image

      :param image: image loaded using cv2.imread
      :return: dictionary with keys 'prediction', 'score', 'growth_code', 'growth', 'accuracy'