Python tools for dealing with hyperspectral images.
pip install git+https://github.com/wairas/happy-tools.git
For Docker images, please see docker/README.md.
usage: happy-data-viewer [-h] [--base_folder BASE_FOLDER] [--sample SAMPLE]
[--repeat REPEAT] [-r INT] [-g INT] [-b INT] [-o INT]
[--listbox_selectbackground LISTBOX_SELECTBACKGROUND]
[--listbox_selectforeground LISTBOX_SELECTFOREGROUND]
Viewer for HAPPy data folder structures.
optional arguments:
-h, --help show this help message and exit
--base_folder BASE_FOLDER
Base folder to display (default: None)
--sample SAMPLE The sample to load (default: None)
--repeat REPEAT The repeat to load (default: None)
-r INT, --scale_r INT
the wave length to use for the red channel (default:
None)
-g INT, --scale_g INT
the wave length to use for the green channel (default:
None)
-b INT, --scale_b INT
the wave length to use for the blue channel (default:
None)
-o INT, --opacity INT
the opacity to use (0-100) (default: None)
--listbox_selectbackground LISTBOX_SELECTBACKGROUND
The background color to use for selected items in
listboxes (default: #4a6984)
--listbox_selectforeground LISTBOX_SELECTFOREGROUND
The foreground color to use for selected items in
listboxes (default: #ffffff)
usage: happy-envi-viewer [-h] [-s SCAN] [-f BLACK_REFERENCE]
[-w WHITE_REFERENCE] [-r INT] [-g INT] [-b INT]
[--autodetect_channels] [--keep_aspectratio]
[--check_scan_dimensions] [--export_to_scan_dir]
[--annotation_color HEXCOLOR]
[--predefined_labels LIST] [--redis_host HOST]
[--redis_port PORT] [--redis_pw PASSWORD]
[--redis_in CHANNEL] [--redis_out CHANNEL]
[--redis_connect] [--marker_size INT]
[--marker_color HEXCOLOR] [--min_obj_size INT]
[--black_ref_locator LOCATOR]
[--black_ref_method METHOD]
[--white_ref_locator LOCATOR]
[--white_ref_method METHOD]
[--preprocessing PIPELINE]
[--log_timestamp_format FORMAT] [--zoom PERCENT]
[--normalization PLUGIN]
[-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}]
ENVI Hyperspectral Image Viewer. Offers contour detection using SAM (Segment-
Anything: https://github.com/waikato-datamining/pytorch/tree/master/segment-
anything)
optional arguments:
-h, --help show this help message and exit
-s SCAN, --scan SCAN Path to the scan file (ENVI format) (default: None)
-f BLACK_REFERENCE, --black_reference BLACK_REFERENCE
Path to the black reference file (ENVI format)
(default: None)
-w WHITE_REFERENCE, --white_reference WHITE_REFERENCE
Path to the white reference file (ENVI format)
(default: None)
-r INT, --scale_r INT
the wave length to use for the red channel (default:
None)
-g INT, --scale_g INT
the wave length to use for the green channel (default:
None)
-b INT, --scale_b INT
the wave length to use for the blue channel (default:
None)
--autodetect_channels
whether to determine the channels from the meta-data
(overrides the manually specified channels) (default:
None)
--keep_aspectratio whether to keep the aspect ratio (default: None)
--check_scan_dimensions
whether to compare the dimensions of subsequently
loaded scans and output a warning if they differ
(default: None)
--export_to_scan_dir whether to export images to the scan directory rather
than the last one used (default: None)
--annotation_color HEXCOLOR
the color to use for the annotations like contours
(hex color) (default: None)
--predefined_labels LIST
the comma-separated list of labels to use (default:
None)
--redis_host HOST The Redis host to connect to (IP or hostname)
(default: None)
--redis_port PORT The port the Redis server is listening on (default:
None)
--redis_pw PASSWORD The password to use with the Redis server (default:
None)
--redis_in CHANNEL The channel that SAM is receiving images on (default:
None)
--redis_out CHANNEL The channel that SAM is broadcasting the detections on
(default: None)
--redis_connect whether to immediately connect to the Redis host
(default: None)
--marker_size INT The size in pixels for the SAM points (default: None)
--marker_color HEXCOLOR
the color to use for the SAM points (hex color)
(default: None)
--min_obj_size INT The minimum size that SAM contours need to have (<= 0
for no minimum) (default: None)
--black_ref_locator LOCATOR
the reference locator scheme to use for locating black
references, eg rl-manual (default: None)
--black_ref_method METHOD
the black reference method to use for applying black
references, eg br-same-size (default: None)
--white_ref_locator LOCATOR
the reference locator scheme to use for locating
whites references, eg rl-manual (default: None)
--white_ref_method METHOD
the white reference method to use for applying white
references, eg wr-same-size (default: None)
--preprocessing PIPELINE
the preprocessors to apply to the scan (default: None)
--log_timestamp_format FORMAT
the format string for the logging timestamp, see: http
s://docs.python.org/3/library/datetime.html#strftime-
and-strptime-format-codes (default: [%H:%M:%S.%f])
--zoom PERCENT the initial zoom to use (%) or -1 for automatic fit
(default: -1)
--normalization PLUGIN
the normalization plugin and its options to use
(default: norm-simple)
-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}, --logging_level {DEBUG,INFO,WARNING,ERROR,CRITICAL}
The logging level to use. (default: WARN)
usage: happy-raw-checker [-h] [-d RAW_DIR] [-f {text,text-compact,csv,json}]
Raw data checker interface. For sanity checks of raw capture data.
optional arguments:
-h, --help show this help message and exit
-d RAW_DIR, --raw_dir RAW_DIR
The initial directory (default: None)
-f {text,text-compact,csv,json}, --output_format {text,text-compact,csv,json}
The output format to use in the text box. (default:
text)
usage: happy-generate-image-regions-objects [-h] -i INPUT_DIR -o OUTPUT_DIR
Generate datasets as numpy cubes, to be loaded into deep learning datasets.
optional arguments:
-h, --help show this help message and exit
-i INPUT_DIR, --input_dir INPUT_DIR
Path to source folder containing HDR files (default:
None)
-o OUTPUT_DIR, --output_dir OUTPUT_DIR
Path to output folder (default: None)
usage: happy-hdr-info [-h] -i INPUT_FILE [-f] [-o OUTPUT_FILE]
Load and print information about an HDR file.
optional arguments:
-h, --help show this help message and exit
-i INPUT_FILE, --input_file INPUT_FILE
Path to the HDR file (default: None)
-f, --full Whether to output all fields (default: False)
-o OUTPUT_FILE, --output_file OUTPUT_FILE
Path to output file; prints to stdout if omitted
(default: None)
usage: happy-hsi2rgb [-h] -i INPUT_DIR [INPUT_DIR ...] [-r] [-e EXTENSION]
[--black_ref_locator LOCATOR] [--black_ref_method METHOD]
[--white_ref_locator LOCATOR] [--white_ref_method METHOD]
[-a] [--red INT] [--green INT] [--blue INT]
[-o OUTPUT_DIR] [--width INT] [--height INT] [-n]
[-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}]
Fake RGB image generator for HSI files.
optional arguments:
-h, --help show this help message and exit
-i INPUT_DIR [INPUT_DIR ...], --input_dir INPUT_DIR [INPUT_DIR ...]
Path to the scan file (ENVI format) (default: None)
-r, --recursive whether to traverse the directories recursively
(default: False)
-e EXTENSION, --extension EXTENSION
The file extension to look for (default: .hdr)
--black_ref_locator LOCATOR
the reference locator scheme to use for locating black
references, eg rl-manual (default: None)
--black_ref_method METHOD
the black reference method to use for applying black
references, eg br-same-size (default: None)
--white_ref_locator LOCATOR
the reference locator scheme to use for locating
whites references, eg rl-manual (default: None)
--white_ref_method METHOD
the white reference method to use for applying white
references, eg wr-same-size (default: None)
-a, --autodetect_channels
whether to determine the channels from the meta-data
(overrides the manually specified channels) (default:
False)
--red INT the wave length to use for the red channel (0-based)
(default: 0)
--green INT the wave length to use for the green channel (0-based)
(default: 0)
--blue INT the wave length to use for the blue channel (0-based)
(default: 0)
-o OUTPUT_DIR, --output_dir OUTPUT_DIR
The directory to store the fake RGB PNG images instead
of alongside the HSI images. (default: None)
--width INT the width to scale the images to (<= 0 uses image
dimension) (default: 0)
--height INT the height to scale the images to (<= 0 uses image
dimension) (default: 0)
-n, --dry_run whether to omit saving the PNG images (default: False)
-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}, --logging_level {DEBUG,INFO,WARNING,ERROR,CRITICAL}
The logging level to use. (default: WARN)
usage: happy-mat-info [-h] -i INPUT_FILE [-o OUTPUT_FILE]
Load and display structs from a MATLAB file.
optional arguments:
-h, --help show this help message and exit
-i INPUT_FILE, --input_file INPUT_FILE
Path to the MATLAB file (default: None)
-o OUTPUT_FILE, --output_file OUTPUT_FILE
Path to the output file; outputs to stdout if omitted
(default: None)
usage: happy-ann2happy [-h] -i DIR [DIR ...]
[-c {pixels,polygons,pixels_then_polygons,polygons_then_pixels}]
[-r] [-o DIR] -f {flat,dir-tree,dir-tree-with-data} -l
LABELS [-N] [-u UNLABELLED]
[--black_ref_locator LOCATOR]
[--black_ref_method METHOD]
[--white_ref_locator LOCATOR]
[--white_ref_method METHOD] [--pattern_mask PATTERN]
[--pattern_labels PATTERN] [--pattern_png PATTERN]
[--pattern_opex PATTERN] [--pattern_envi PATTERN] [-I]
[-n] [--resume_from DIR]
[-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}]
Turns annotations (PNG, OPEX JSON, ENVI pixel annotations) into Happy ENVI
format.
optional arguments:
-h, --help show this help message and exit
-i DIR [DIR ...], --input_dir DIR [DIR ...]
Path to the PNG/OPEX/ENVI files (default: None)
-c {pixels,polygons,pixels_then_polygons,polygons_then_pixels}, --conversion {pixels,polygons,pixels_then_polygons,polygons_then_pixels}
What annotations and in what order to apply
(subsequent overlays can overwrite annotations).
(default: pixels_then_polygons)
-r, --recursive whether to look for OPEX/ENVI files recursively
(default: False)
-o DIR, --output_dir DIR
The directory to store the fake RGB PNG images instead
of alongside the HSI images. (default: None)
-f {flat,dir-tree,dir-tree-with-data}, --output_format {flat,dir-tree,dir-tree-with-data}
Defines how to store the data in the output directory.
(default: dir-tree-with-data)
-l LABELS, --labels LABELS
The comma-separated list of object labels to export
('Background' is automatically added). (default: None)
-N, --no_implicit_background
whether to require explicit annotations for the
background rather than assuming all un-annotated
pixels are background (default: False)
-u UNLABELLED, --unlabelled UNLABELLED
The value to use for pixels that do not have an
explicit annotation (label values start after this
value) (default: 0)
--black_ref_locator LOCATOR
the reference locator scheme to use for locating black
references, eg rl-manual; requires: dir-tree-with-data
(default: None)
--black_ref_method METHOD
the black reference method to use for applying black
references, eg br-same-size; requires: dir-tree-with-
data (default: None)
--white_ref_locator LOCATOR
the reference locator scheme to use for locating
whites references, eg rl-manual; requires: dir-tree-
with-data (default: None)
--white_ref_method METHOD
the white reference method to use for applying white
references, eg wr-same-size; requires: dir-tree-with-
data (default: None)
--pattern_mask PATTERN
the pattern to use for saving the mask ENVI file,
available placeholders: {SAMPLEID} (default: mask.hdr)
--pattern_labels PATTERN
the pattern to use for saving the label map for the
mask ENVI file, available placeholders: {SAMPLEID}
(default: mask.json)
--pattern_png PATTERN
the pattern to use for saving the mask PNG file,
available placeholders: {SAMPLEID} (default:
{SAMPLEID}.png)
--pattern_opex PATTERN
the pattern to use for saving the OPEX JSON annotation
file, available placeholders: {SAMPLEID} (default:
{SAMPLEID}.json)
--pattern_envi PATTERN
the pattern to use for saving the ENVI mask annotation
file, available placeholders: {SAMPLEID} (default:
MASK_{SAMPLEID}.hdr)
-I, --include_input whether to copy the PNG/JSON file across to the output
dir (default: False)
-n, --dry_run whether to omit generating any data or creating
directories (default: False)
--resume_from DIR The directory to restart the processing with (all
determined dirs preceding this one get skipped)
(default: None)
-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}, --logging_level {DEBUG,INFO,WARNING,ERROR,CRITICAL}
The logging level to use. (default: WARN)
usage: happy-opex-labels [-h] -i INPUT [-r]
[-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}]
{list-labels,update-labels,delete-labels} ...
Performs actions on OPEX JSON files that it locates.
positional arguments:
{list-labels,update-labels,delete-labels}
sub-command help
list-labels Lists the labels in the located files
update-labels Updates the labels using the specified label mapping
delete-labels Deletes the specified labels
optional arguments:
-h, --help show this help message and exit
-i INPUT, --input INPUT
The dir with the OPEX JSON files (default: None)
-r, --recursive Whether to search the directory recursively (default:
False)
-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}, --logging_level {DEBUG,INFO,WARNING,ERROR,CRITICAL}
The logging level to use. (default: WARN)
usage: happy-plot-preproc [-h] -i INPUT_DIR [-f FROM_INDEX] [-t TO_INDEX]
[-P PREPROCESSORS] [-S PIXEL_SELECTORS]
[-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}]
Plot set of pixels with various pre-processing setups.
optional arguments:
-h, --help show this help message and exit
-i INPUT_DIR, --input_dir INPUT_DIR
Folder containing HAPPy data files (default: None)
-f FROM_INDEX, --from_index FROM_INDEX
The first wavelength index to include (0-based)
(default: 60)
-t TO_INDEX, --to_index TO_INDEX
The last wavelength index to include (0-based)
(default: 189)
-P PREPROCESSORS, --preprocessors PREPROCESSORS
The preprocessors to apply to the data separately; use
"multi-pp" if you need to combine multiple steps.
Either preprocessor command-line(s) or file with one
preprocessor command-line per line. (default: pass-
through multi-pp -p 'derivative -w 15 -d 0 snv'
derivative -w 15 -d 0 sni)
-S PIXEL_SELECTORS, --pixel_selectors PIXEL_SELECTORS
The pixel selectors to use. Either pixel selector
command-line(s) or file with one pixel selector
command-line per line. (default: ps-simple -n 100 -b)
-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}, --logging_level {DEBUG,INFO,WARNING,ERROR,CRITICAL}
The logging level to use. (default: WARN)
usage: happy-process-data reader [preprocessor(s)] writer [-h|--help|--help-all|--help-plugin NAME]
[-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}]
Processes data using the specified pipeline.
readers: happy-reader, matlab-reader
preprocessors: crop, derivative, down-sample, extract-regions, multi-pp, pca, pad, pass-through, snv, sni, std-scaler, subtract, wavelength-subset
writers: happy-writer, matlab-writer, png-writer
optional arguments:
-h, --help show this help message and exit
--help-all show the help for all plugins and exit
--help-plugin NAME show the help for plugin NAME and exit
-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}, --logging_level {DEBUG,INFO,WARNING,ERROR,CRITICAL}
The logging level to use. (default: WARN)
usage: happy-raw-check [-h] -i INPUT [INPUT ...] [-r] [-o OUTPUT]
[-f {text,text-compact,csv,json}]
[-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}]
Performs sanity checks on raw capture folders.
optional arguments:
-h, --help show this help message and exit
-i INPUT [INPUT ...], --input INPUT [INPUT ...]
The dir(s) with the raw capture folders (default:
None)
-r, --recursive Whether to search the directory recursively (default:
False)
-o OUTPUT, --output OUTPUT
The file to store the results in; uses stdout if
omitted (default: None)
-f {text,text-compact,csv,json}, --output_format {text,text-compact,csv,json}
The format to use for the output (default: text)
-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}, --logging_level {DEBUG,INFO,WARNING,ERROR,CRITICAL}
The logging level to use. (default: WARN)
usage: happy-scikit-regression-build [-h] -d HAPPY_DATA_BASE_DIR
[-P PREPROCESSORS] [-S PIXEL_SELECTORS]
[-m REGRESSION_METHOD]
[-p REGRESSION_PARAMS] -t TARGET_VALUE -s
HAPPY_SPLITTER_FILE -o OUTPUT_FOLDER
[-r REPEAT_NUM]
[-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}]
Evaluate regression model on Happy Data using specified splits and pixel
selector.
optional arguments:
-h, --help show this help message and exit
-d HAPPY_DATA_BASE_DIR, --happy_data_base_dir HAPPY_DATA_BASE_DIR
Directory containing the Happy Data files (default:
None)
-P PREPROCESSORS, --preprocessors PREPROCESSORS
The preprocessors to apply to the data. Either
preprocessor command-line(s) or file with one
preprocessor command-line per line. (default:
wavelength-subset -f 60 -t 189 sni snv derivative -w
15 pad -W 128 -H 128 -v 0)
-S PIXEL_SELECTORS, --pixel_selectors PIXEL_SELECTORS
The pixel selectors to use. Either pixel selector
command-line(s) or file with one pixel selector
command-line per line. (default: ps-simple -n 64)
-m REGRESSION_METHOD, --regression_method REGRESSION_METHOD
Regression method name (e.g., linearregression,ridge,l
ars,plsregression,plsneighbourregression,lasso,elastic
net,decisiontreeregressor,randomforestregressor,svr or
full class name) (default: linearregression)
-p REGRESSION_PARAMS, --regression_params REGRESSION_PARAMS
JSON string containing regression parameters (default:
{})
-t TARGET_VALUE, --target_value TARGET_VALUE
Target value column name (default: None)
-s HAPPY_SPLITTER_FILE, --happy_splitter_file HAPPY_SPLITTER_FILE
Happy Splitter file (default: None)
-o OUTPUT_FOLDER, --output_folder OUTPUT_FOLDER
Output JSON file to store the predictions (default:
None)
-r REPEAT_NUM, --repeat_num REPEAT_NUM
Repeat number (default: 0) (default: 0)
-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}, --logging_level {DEBUG,INFO,WARNING,ERROR,CRITICAL}
The logging level to use. (default: WARN)
usage: happy-scikit-segmentation-build [-h] -d HAPPY_DATA_BASE_DIR
[-P PREPROCESSORS] [-S PIXEL_SELECTORS]
[-m SEGMENTATION_METHOD]
[-p SEGMENTATION_PARAMS] -t
TARGET_VALUE -s HAPPY_SPLITTER_FILE -o
OUTPUT_FOLDER [-r REPEAT_NUM]
[-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}]
Evaluate segmentation model on Happy Data using specified splits and pixel
selector.
optional arguments:
-h, --help show this help message and exit
-d HAPPY_DATA_BASE_DIR, --happy_data_base_dir HAPPY_DATA_BASE_DIR
Directory containing the Happy Data files (default:
None)
-P PREPROCESSORS, --preprocessors PREPROCESSORS
The preprocessors to apply to the data (default: )
-S PIXEL_SELECTORS, --pixel_selectors PIXEL_SELECTORS
The pixel selectors to use. (default: ps-simple -n
32767)
-m SEGMENTATION_METHOD, --segmentation_method SEGMENTATION_METHOD
Segmentation method name (e.g., randomforestclassifier
,gradientboostingclassifier,adaboostclassifier,kneighb
orsclassifier,decisiontreeclassifier,gaussiannb,logist
icregression,mlpclassifier,svm,random_forest,knn,decis
ion_tree,gradient_boosting,naive_bayes,logistic_regres
sion,neural_network,adaboost,extra_trees or full class
name) (default: svm)
-p SEGMENTATION_PARAMS, --segmentation_params SEGMENTATION_PARAMS
JSON string containing segmentation parameters
(default: {})
-t TARGET_VALUE, --target_value TARGET_VALUE
Target value column name (default: None)
-s HAPPY_SPLITTER_FILE, --happy_splitter_file HAPPY_SPLITTER_FILE
Happy Splitter file (default: None)
-o OUTPUT_FOLDER, --output_folder OUTPUT_FOLDER
Output JSON file to store the predictions (default:
None)
-r REPEAT_NUM, --repeat_num REPEAT_NUM
Repeat number (default: 0) (default: 0)
-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}, --logging_level {DEBUG,INFO,WARNING,ERROR,CRITICAL}
The logging level to use. (default: WARN)
usage: happy-scikit-unsupervised-build [-h] -d DATA_FOLDER [-P PREPROCESSORS]
[-S PIXEL_SELECTORS]
[-m CLUSTERER_METHOD]
[-p CLUSTERER_PARAMS] -s
HAPPY_SPLITTER_FILE -o OUTPUT_FOLDER
[-r REPEAT_NUM]
[-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}]
Evaluate clustering on hyperspectral data using specified clusterer and pixel
selector.
optional arguments:
-h, --help show this help message and exit
-d DATA_FOLDER, --data_folder DATA_FOLDER
Directory containing the hyperspectral data (default:
None)
-P PREPROCESSORS, --preprocessors PREPROCESSORS
The preprocessors to apply to the data. Either
preprocessor command-line(s) or file with one
preprocessor command-line per line. (default:
wavelength-subset -f 60 -t 189 snv derivative pca -n 5
-p 20)
-S PIXEL_SELECTORS, --pixel_selectors PIXEL_SELECTORS
The pixel selectors to use. Either pixel selector
command-line(s) or file with one pixel selector
command-line per line. (default: ps-simple -n 32 -b)
-m CLUSTERER_METHOD, --clusterer_method CLUSTERER_METHOD
Clusterer name (e.g.,
kmeans,agglomerative,spectral,dbscan,meanshift) or
full class name (default: kmeans)
-p CLUSTERER_PARAMS, --clusterer_params CLUSTERER_PARAMS
JSON string containing clusterer parameters (default:
{})
-s HAPPY_SPLITTER_FILE, --happy_splitter_file HAPPY_SPLITTER_FILE
Happy Splitter file (default: None)
-o OUTPUT_FOLDER, --output_folder OUTPUT_FOLDER
Output JSON file to store the predictions (default:
None)
-r REPEAT_NUM, --repeat_num REPEAT_NUM
Repeat number (default: 0) (default: 0)
-V {DEBUG,INFO,WARNING,ERROR,CRITICAL}, --logging_level {DEBUG,INFO,WARNING,ERROR,CRITICAL}
The logging level to use. (default: WARN)
usage: happy-splitter [-h] -b BASE_FOLDER [-r NUM_REPEATS] [-f NUM_FOLDS]
[-t TRAIN_PERCENT] [-v VALIDATION_PERCENT] [-R]
[-H HOLDOUT_PERCENT] -o OUTPUT_FILE [-S SEED]
Generate train/validation/test splits for Happy data.
optional arguments:
-h, --help show this help message and exit
-b BASE_FOLDER, --base_folder BASE_FOLDER
Path to the Happy base folder (default: None)
-r NUM_REPEATS, --num_repeats NUM_REPEATS
Number of repeats (default: 1)
-f NUM_FOLDS, --num_folds NUM_FOLDS
Number of folds (default: 1)
-t TRAIN_PERCENT, --train_percent TRAIN_PERCENT
Percentage of data in the training set (default: 70.0)
-v VALIDATION_PERCENT, --validation_percent VALIDATION_PERCENT
Percentage of data in the validation set (default:
10.0)
-R, --use_regions Use regions in generating splits (default: False)
-H HOLDOUT_PERCENT, --holdout_percent HOLDOUT_PERCENT
Percentage of data to hold out as a holdout set
(default: None)
-o OUTPUT_FILE, --output_file OUTPUT_FILE
Path to the output split file (default:
output_split.json)
-S SEED, --seed SEED The seed to use for reproducible results (default:
None)
See here for a list of plugins and their documentation.