`macrobot.bgt`¶

Module Contents¶

Classes¶

Macrobot analysis for blumeria graminis tritici pathogen.

class macrobot.bgt.BgtSegmenter(image_list, path_source, destination_path, store_leaf_path, experiment, dai, file_results)¶

Bases: macrobot.mb_pipeline.MacrobotPipeline

Macrobot analysis for blumeria graminis tritici pathogen.

NAME = 'BGT'¶

get_frames(image_source)¶

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

Parameters: image_source (numpy array.) – The UVS-image (x, y, 1) which is used as source for thresholding.
Returns: The binary image after Otsu thresholding.
Return type: numpy array

get_lanes_rgb()¶: Calls segment_lanes_rgb to extract the RGB lanes within the white frames.

get_features()¶

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

Returns: A list with the features per lane and it’s position sorted left to right.
Return type: list with tuple(feature, position)

get_prediction_per_lane(plate_id, destination_path)¶

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

Returns: A list with the predictions per lane and it’s position sorted left to right.
Return type: list with tuple(prediction, position)