baby.training.training.BabyTrainer¶

class baby.training.training.BabyTrainer(save_dir, base_dir=None, params=None, max_cnns=3)¶

Bases: object

Manager to set up and train BABY models

Parameters

save_dir – directory in which to save parameters and logs (and from which to auto-load parameters and logs)
train_val_images – either a dict with keys ‘training’ and ‘validation’ and values specifying lists of file name pairs, or the name of a json file containing such a dict. The file name pairs should correspond to image-label pairs suitable for input to baby.generator.ImageLabel.
flattener – either a baby.preprocessing.SegmentationFlattening object, or the name of a json file that is a saved SegmentationFlattening object.

Attributes

Methods

`fit_bud_model`(**kwargs)
`fit_seg_params`([njobs, scoring])
`generate_bud_stats`()
`refit_filter_seg_params`([lazy, bootstrap, ...])
`validate_seg_params`([iou_thresh, save])

fit_cnn
fit_flattener
fit_smoothing_model
generate_flattener_stats
generate_smoothing_sigma_stats
plot_fitted_smoothing_sigma_model
plot_flattener_stats
plot_gen_sample
plot_histories

Methods

`__init__`(save_dir[, base_dir, params, max_cnns])
`fit_bud_model`(**kwargs)
`fit_cnn`(**kwargs)
`fit_flattener`(**kwargs)
`fit_seg_params`([njobs, scoring])
`fit_smoothing_model`([filt])
`generate_bud_stats`()
`generate_flattener_stats`([max_erode])
`generate_smoothing_sigma_stats`()
`plot_fitted_smoothing_sigma_model`()
`plot_flattener_stats`(**kwargs)
`plot_gen_sample`([validation])
`plot_histories`(**kwargs)
`refit_filter_seg_params`([lazy, bootstrap, ...])
`validate_seg_params`([iou_thresh, save])

Attributes

aliby