dacapo.experiments.tasks.hot_distance_task_config
Classes
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