dacapo.experiments.tasks.hot_distance_task_config

Classes

HotDistanceTaskConfig

Class for generating TaskConfigs for the HotDistanceTask, which predicts one hot encodings of classes, as well as signed distance transforms of those classes.

Module Contents

class dacapo.experiments.tasks.hot_distance_task_config.HotDistanceTaskConfig

Class for generating TaskConfigs for the HotDistanceTask, which predicts one hot encodings of classes, as well as signed distance transforms of those classes.

task_type

A reference to the Hot Distance Task class.

channels

A list of channel names.

Type:

List[str]

clip_distance

Maximum distance to consider for false positive/negatives.

Type:

float

tol_distance

Tolerance distance for counting false positives/negatives.

Type:

float

scale_factor

The amount by which to scale distances before applying a tanh normalization. Defaults to 1.

Type:

float

mask_distances

Whether or not to mask out regions where the true distance to object boundary cannot be known. Defaults to False

Type:

bool

verify(self) Tuple[bool, str]

This method verifies the HotDistanceTaskConfig object.

Note

Generating distance transforms over regular affinities provides you with a denser signal, i.e., one misclassified pixel in an affinity prediction can merge 2 otherwise very distinct objects, a situation that cannot happen with distances.

task_type
channels: List[str]
clip_distance: float
tol_distance: float
scale_factor: float
mask_distances: bool
kernel_size: int | None