baby.seg_trainer.SegFilterParamOptim

class baby.seg_trainer.SegFilterParamOptim(flattener, basic_params={}, IoU_thresh=0.5, scoring='F0_5', nbootstraps=10, bootstrap_frac=0.9)

Bases: object

# TODO What does this class do

  • What are the parameters and what do they mean

  • What are the defaults, what are the ranges/admissible options?

Parameters

  • flattener –

  • basic_params –

  • IoU_thresh –

  • scoring –

  • nbootstraps –

  • bootstrap_frac –

Attributes
basic_params
opt_params
opt_score
scoring

The scoring method used during evaluation of the segmentation.

segrps
stat_table
stat_table_bootstraps
truth
truth_bootstraps

Methods

filter_trial

fit_filter_params

generate_stat_table
__init__(flattener, basic_params={}, IoU_thresh=0.5, scoring='F0_5', nbootstraps=10, bootstrap_frac=0.9)

Methods

__init__(flattener[, basic_params, ...])

filter_trial(pedge_thresh, ...[, bootstrap, ...])

fit_filter_params([lazy, bootstrap])

generate_stat_table(example_gen)

Attributes

basic_params

opt_params

opt_score

scoring

The scoring method used during evaluation of the segmentation.

segrps

stat_table

stat_table_bootstraps

truth

truth_bootstraps

property scoring

The scoring method used during evaluation of the segmentation. Accepted values are: # TODO define the scoring metrics * precision: * recall: * F1: * F0_5: * F2: * meanIoU: :return: str scoring method