:py:mod:`macrobot.bgt`
======================

.. py:module:: macrobot.bgt


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

Classes
~~~~~~~

.. autoapisummary::

   macrobot.bgt.BgtSegmenter




.. py:class:: BgtSegmenter(image_list, path_source, destination_path, store_leaf_path, experiment, dai, file_results)

   Bases: :py:obj:`macrobot.mb_pipeline.MacrobotPipeline`

   Macrobot analysis for blumeria graminis tritici pathogen.

   .. py:attribute:: NAME
      :annotation: = BGT

      

   .. py:method:: get_frames(self, image_source)

      Segment the white frame on a microtiter plate.
      Algorithm is based on Otsu thresholding of the UVS image.

      :param image_source: The UVS-image (x, y, 1) which is used as source for thresholding.
      :type image_source: numpy array.
      :return: The binary image after Otsu thresholding.
      :rtype: numpy array


   .. py:method:: get_lanes_rgb(self)

      Calls segment_lanes_rgb to extract the RGB lanes within the white frames.


   .. py:method:: get_features(self)

      Feature extraction for Bgt based on Minimum intensity projection (MinIP).
      doi:10.1148/rg.255055044

      :return: A list with the features per lane and it's position sorted left to right.
      :rtype: list with tuple(feature, position)


   .. py:method:: get_prediction_per_lane(self, plate_id, destination_path)

      Predict the Bgt pathogen from the feature extraction method based on thresholding. 255 = pathogen, 0 = background

      :return: A list with the predictions per lane and it's position sorted left to right.
      :rtype: list with tuple(prediction, position)