dacapo.experiments.trainers.gp_augments
Submodules
- dacapo.experiments.trainers.gp_augments.augment_config
- dacapo.experiments.trainers.gp_augments.elastic_config
- dacapo.experiments.trainers.gp_augments.gamma_config
- dacapo.experiments.trainers.gp_augments.intensity_config
- dacapo.experiments.trainers.gp_augments.intensity_scale_shift_config
- dacapo.experiments.trainers.gp_augments.simple_config
Classes
Base class for gunpowder augment configurations. Each subclass of a Augment |
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A class that holds the configuration details for the elastic augmentations. |
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This class is an implementation of AugmentConfig that applies simple augmentations. |
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This class manages the configuration of gamma augmentation for a given dataset. |
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This class is an implementation of AugmentConfig that applies intensity augmentations. |
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This class is an implementation of AugmentConfig that applies intensity scaling and shifting. |
Package Contents
- class dacapo.experiments.trainers.gp_augments.AugmentConfig
Base class for gunpowder augment configurations. Each subclass of a Augment should have a corresponding config class derived from AugmentConfig.
- _raw_key
Key for raw data. Not used in this implementation. Defaults to None.
- _gt_key
Key for ground truth data. Not used in this implementation. Defaults to None.
- _mask_key
Key for mask data. Not used in this implementation. Defaults to None.
- node(_raw_key=None, _gt_key=None, _mask_key=None)
Get a gp.Augment node.
- abstract node(raw_key: gunpowder.ArrayKey, gt_key: gunpowder.ArrayKey, mask_key: gunpowder.ArrayKey) gunpowder.BatchFilter
Get a gunpowder augment node.
- Parameters:
raw_key (gp.ArrayKey) – Key for raw data.
gt_key (gp.ArrayKey) – Key for ground truth data.
mask_key (gp.ArrayKey) – Key for mask data.
- Returns:
Augmentation node which can be incorporated in the pipeline.
- Return type:
gunpowder.BatchFilter
- Raises:
NotImplementedError – This method is not implemented.
Examples
>>> node = augment_config.node(raw_key, gt_key, mask_key)
- class dacapo.experiments.trainers.gp_augments.ElasticAugmentConfig
A class that holds the configuration details for the elastic augmentations.
- control_point_spacing
Distance(in voxels per dimension) between control points for the elastic deformation.
- Type:
List[int]
- control_point_displacement_sigma
Standard deviation of control point displacement distribution, in world coordinates.
- Type:
List[float]
- rotation_interval
An interval to randomly sample rotation angles from (0,2PI).
- Type:
Tuple[float, float]
- subsample
Downsample factor to perform the elastic augmentation on a grid. Default is 1.
- Type:
int
- uniform_3d_rotation
Should 3D rotations be performed uniformly. The ‘rotation_interval’ will be ignored. Default is False.
- Type:
bool
- node(_raw_key=None, _gt_key=None, _mask_key=None)
Returns the object of ElasticAugment with the given configuration details.
- control_point_spacing: List[int]
- control_point_displacement_sigma: List[float]
- rotation_interval: Tuple[float, float]
- subsample: int
- uniform_3d_rotation: bool
- node(_raw_key=None, _gt_key=None, _mask_key=None)
Returns the object of ElasticAugment with the given configuration details.
- Parameters:
_raw_key – Unused variable, kept for future use.
_gt_key – Unused variable, kept for future use.
_mask_key – Unused variable, kept for future use.
- Returns:
- A ElasticAugment object configured with control_point_spacing,
control_point_displacement_sigma, rotation_interval, subsample and uniform_3d_rotation.
- Return type:
- Raises:
NotImplementedError – This method is not implemented.
Examples
>>> node = elastic_augment_config.node()
- class dacapo.experiments.trainers.gp_augments.SimpleAugmentConfig
This class is an implementation of AugmentConfig that applies simple augmentations.
- Parameters:
_raw_key – Key for raw data. Not used in this implementation. Defaults to None.
_gt_key – Key for ground truth data. Not used in this implementation. Defaults to None.
_mask_key – Key for mask data. Not used in this implementation. Defaults to None.
- node(_raw_key=None, _gt_key=None, _mask_key=None)
Get a gp.SimpleAugment node.
Note
This class is a subclass of AugmentConfig.
- node(_raw_key=None, _gt_key=None, _mask_key=None)
Get a gp.SimpleAugment node.
- Parameters:
_raw_key ([type], optional) – Specific key for raw data, not used in this implementation. Defaults to None.
_gt_key ([type], optional) – Specific key for ground truth data, not used in this implementation. Defaults to None.
_mask_key ([type], optional) – Specific key for mask data, not used in this implementation. Defaults to None.
- Returns:
Simple augmentation node which can be incorporated in the pipeline.
- Return type:
gunpowder.SimpleAugment
- Raises:
NotImplementedError – This method is not implemented.
Examples
>>> node = simple_augment_config.node()
- class dacapo.experiments.trainers.gp_augments.GammaAugmentConfig
This class manages the configuration of gamma augmentation for a given dataset.
- gamma_range
A tuple of float values represents the min and max range of gamma noise
- to apply on the raw data.
- node()
Constructs a node in the augmentation pipeline.
- gamma_range: Tuple[float, float]
- node(raw_key: gunpowder.ArrayKey, _gt_key=None, _mask_key=None)
Constructs a node in the augmentation pipeline.
- Parameters:
raw_key (gp.ArrayKey) – Key to an Array (volume) in the pipeline
_gt_key (gp.ArrayKey, optional) – Ground Truth key, not used in this function. Defaults to None.
_mask_key (gp.ArrayKey, optional) – Mask Key, not used in this function. Defaults to None.
- Returns:
The augmentation method to be applied on the source data.
- Return type:
GammaAugment instance
- Raises:
NotImplementedError – This method is not implemented.
Examples
>>> node = gamma_augment_config.node(raw_key)
- class dacapo.experiments.trainers.gp_augments.IntensityAugmentConfig
This class is an implementation of AugmentConfig that applies intensity augmentations.
- scale
A range within which to choose a random scale factor.
- Type:
Tuple[float, float]
- shift
A range within which to choose a random additive shift.
- Type:
Tuple[float, float]
- clip
Set to False if modified values should not be clipped to [0, 1]
- Type:
bool
- node(raw_key, _gt_key=None, _mask_key=None)
Get a gp.IntensityAugment node.
- scale: Tuple[float, float]
- shift: Tuple[float, float]
- clip: bool
- node(raw_key: gunpowder.ArrayKey, _gt_key=None, _mask_key=None)
Get a gp.IntensityAugment node.
- Parameters:
raw_key (gp.ArrayKey) – Key for raw data.
_gt_key ([type], optional) – Specific key for ground truth data, not used in this implementation. Defaults to None.
_mask_key ([type], optional) – Specific key for mask data, not used in this implementation. Defaults to None.
- Returns:
Intensity augmentation node which can be incorporated in the pipeline.
- Return type:
gunpowder.IntensityAugment
- Raises:
NotImplementedError – This method is not implemented.
Examples
>>> node = intensity_augment_config.node(raw_key)
- class dacapo.experiments.trainers.gp_augments.IntensityScaleShiftAugmentConfig
This class is an implementation of AugmentConfig that applies intensity scaling and shifting.
- scale
A constant to scale your intensities.
- Type:
float
- shift
A constant to shift your intensities.
- Type:
float
- node(raw_key, _gt_key=None, _mask_key=None)
Get a gp.IntensityScaleShift node.
Note
This class is a subclass of AugmentConfig.
- scale: float
- shift: float
- node(raw_key: gunpowder.ArrayKey, _gt_key=None, _mask_key=None)
Get a gp.IntensityScaleShift node.
- Parameters:
raw_key (gp.ArrayKey) – Key for raw data.
_gt_key ([type], optional) – Specific key for ground truth data, not used in this implementation. Defaults to None.
_mask_key ([type], optional) – Specific key for mask data, not used in this implementation. Defaults to None.
- Returns:
Intensity scaling and shifting node which can be incorporated in the pipeline.
- Return type:
gunpowder.IntensityScaleShift
- Raises:
NotImplementedError – This method is not implemented.
Examples
>>> node = intensity_scale_shift_augment_config.node(raw_key)