dacapo.experiments.datasplits.datasets

Subpackages

Submodules

Package Contents

Classes

Dataset

A class to represent a dataset.

DatasetConfig

A class used to define configuration for datasets. This provides the

DummyDataset

DummyDataset is a child class of the Dataset. This class has property 'raw' of Array type and a name.

DummyDatasetConfig

A dummy configuration class for test datasets.

RawGTDataset

A class to represent a dataset.

RawGTDatasetConfig

This is a configuration class for the standard dataset with both raw and GT Array.

class dacapo.experiments.datasplits.datasets.Dataset

A class to represent a dataset.

name

The name of the dataset.

Type:

str

raw

The raw dataset.

Type:

Array

gt

The ground truth data.

Type:

Array, optional

mask

The mask for the data.

Type:

Array, optional

weight

The weight of the dataset.

Type:

int, optional

sample_points

The list of sample points in the dataset.

Type:

list[Coordinate], optional

name: str
raw: dacapo.experiments.datasplits.datasets.arrays.Array
gt: dacapo.experiments.datasplits.datasets.arrays.Array | None
mask: dacapo.experiments.datasplits.datasets.arrays.Array | None
weight: int | None
sample_points: List[funlib.geometry.Coordinate] | None
class dacapo.experiments.datasplits.datasets.DatasetConfig

A class used to define configuration for datasets. This provides the framework to create a Dataset instance.

name

str (eg: “sample_dataset”). A unique identifier to name the dataset. It aids in easy identification and reusability of this dataset. Advised to keep it short and refrain from using special characters.

weight

int (default=1). A numeric value that indicates how frequently this dataset should be sampled in comparison to others. Higher the weight, more frequently it gets sampled.

verify()

Checks and validates the dataset configuration. The specific rules for validation need to be defined by the user.

name: str
weight: int
verify() Tuple[bool, str]

Method to verify the dataset configuration.

Since there is no specific validation logic defined for this DataSet, this method will always return True as default reaction and a message stating the lack of validation.

Returns:

A tuple of boolean value indicating the check (True or False) and message specifying result of validation.

Return type:

tuple

class dacapo.experiments.datasplits.datasets.DummyDataset(dataset_config)

DummyDataset is a child class of the Dataset. This class has property ‘raw’ of Array type and a name.

Parameters:

dataset_config (object) – an instance of a configuration class.

raw: dacapo.experiments.datasplits.datasets.arrays.Array
class dacapo.experiments.datasplits.datasets.DummyDatasetConfig

A dummy configuration class for test datasets.

dataset_type

Clearly mentions the type of dataset

raw_config

This attribute holds the configurations related to dataset arrays.

verify()

A dummy verification method for testing purposes, always returns False and a message.

dataset_type
raw_config: dacapo.experiments.datasplits.datasets.arrays.ArrayConfig
verify() Tuple[bool, str]

A dummy method that always indicates the dataset config is not valid.

Returns:

A tuple of False and a message indicating the invalidity.

class dacapo.experiments.datasplits.datasets.RawGTDataset(dataset_config)

A class to represent a dataset.

name

The name of the dataset.

Type:

str

raw

The raw dataset.

Type:

Array

gt

The ground truth data.

Type:

Array, optional

mask

The mask for the data.

Type:

Array, optional

weight

The weight of the dataset.

Type:

int, optional

sample_points

The list of sample points in the dataset.

Type:

list[Coordinate], optional

raw: dacapo.experiments.datasplits.datasets.arrays.Array
gt: dacapo.experiments.datasplits.datasets.arrays.Array
mask: dacapo.experiments.datasplits.datasets.arrays.Array | None
sample_points: List[funlib.geometry.Coordinate] | None
class dacapo.experiments.datasplits.datasets.RawGTDatasetConfig

This is a configuration class for the standard dataset with both raw and GT Array.

The configuration includes array configurations for raw data, ground truth data and mask data. The configuration for ground truth (GT) data is mandatory, whereas configurations for raw and mask data are optional. It also includes an optional list of points around which training samples will be extracted.

dataset_type

The type of dataset that is being configured.

Type:

class

raw_config

Configuration for the raw data associated with this dataset.

Type:

Optional[ArrayConfig]

gt_config

Configuration for the ground truth data associated with this dataset.

Type:

Optional[ArrayConfig]

mask_config

An optional mask configuration that sets the loss equal to zero on voxels where the mask is 1.

Type:

Optional[ArrayConfig]

sample_points

An optional list of points around which training samples will be extracted.

Type:

Optional[List[Coordinate]]

dataset_type
raw_config: dacapo.experiments.datasplits.datasets.arrays.ArrayConfig | None
gt_config: dacapo.experiments.datasplits.datasets.arrays.ArrayConfig | None
mask_config: dacapo.experiments.datasplits.datasets.arrays.ArrayConfig | None
sample_points: List[funlib.geometry.Coordinate] | None