macrobot.puccinia¶
Module Contents¶
Classes¶
Macrobot analysis for Puccinia plant pathogen. |
- class macrobot.puccinia.RustSegmenter(image_list, path_source, destination_path, store_leaf_path, experiment, dai, file_results)¶
Bases:
macrobot.mb_pipeline.MacrobotPipelineMacrobot analysis for Puccinia plant pathogen. Currently works for leaf and stripe rust.
- NAME = 'RUST'¶
- get_frames(image_source)¶
Segment the white frame on a microtiter plate. Algorithm is based on Triangle thresholding of the green channel image. Different from IPK Macrobot!
- Parameters
image_source (numpy array.) – The green channel image (x, y, 1) which is used as source for thresholding.
- Returns
The binary image after 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 Rust based on thresholding the saturation channel.
- 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 Rust 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)