Feature Generator
Aydin use a set of well-engineered feature generators to implement image translators internally. Aydin also provides a public API on feature generators to enable developers who might want to use same feature:
- StandardFeatureGenerator
- ExtensibleFeatureGenerator
Extensible Feature Generator class
Adds a feature to this feature generator.
ExtensibleFeatureGenerator.compute
(image[, ...])Computes the features given an image.
Creates a feature array of the right size and possibly in a 'lazy' way using memory mapping.
Clears the features group list
Returns the number of features when considering translations
Returns the receptive field radius in pixels
Returns a 'all-batteries-inlcuded' feature generator from a given path (folder)
Saves a 'all-batteries-inlcuded' feature generator at a given path (folder)
- FeatureGeneratorBase
Feature Generator base class
FeatureGeneratorBase.compute
(image[, ...])Computes the features given an image.
Creates a feature array of the right size and possibly in a 'lazy' way using memory mapping.
Returns the receptive field radius in pixels
Returns a 'all-batteries-inlcuded' feature generator from a given path (folder)
Saves a 'all-batteries-inlcuded' feature generator at a given path (folder)
StandardFeatureGenerator
ExtensibleFeatureGenerator
- class aydin.features.extensible_features.ExtensibleFeatureGenerator[source]
Extensible Feature Generator class
- add_feature_group(feature_group: aydin.features.groups.base.FeatureGroupBase, *args, **kwargs)[source]
Adds a feature to this feature generator.
- Parameters
- feature_groupFeatureGroupBase
feature group
- args
additional arguments for function
- kwargs
additional keyword arguments for function
- compute(image, exclude_center_feature=False, exclude_center_value=False, features=None, feature_last_dim=True, passthrough_channels=None, num_reserved_features=0, excluded_voxels=None, spatial_feature_offset=None, spatial_feature_scale=None)[source]
Computes the features given an image. If the input image is of shape (d,h,w), resulting features are of shape (n,d,h,w) where n is the number of features.
- Parameters
- imagenumpy.ndarray
- image for which features are computed
- exclude_center_featurebool
- exclude_center_valuebool
- features
- feature_last_dimbool
- passthrough_channels
- num_reserved_featuresint
- excluded_voxels
- spatial_feature_offset
- spatial_feature_scale
- Returns
- feature arraynumpy.ndarray
- create_feature_array(image, nb_features)
Creates a feature array of the right size and possibly in a ‘lazy’ way using memory mapping.
- Parameters
- imagenumpy.ndarray
image for which features are created
- nb_featuresint
- Returns
- feature arraynumpy.ndarray
- get_num_features(ndim: int) int [source]
Returns the number of features when considering translations
- Parameters
- ndimint
number of dimensions
- Returns
- nb_featuresint
- get_receptive_field_radius() int [source]
Returns the receptive field radius in pixels
- Returns
- resultint
receptive field radius in pixels
- static load(path: str)
Returns a ‘all-batteries-inlcuded’ feature generator from a given path (folder)
- Parameters
- pathstr
path to load from
- Returns
- thawed
- save(path: str)
Saves a ‘all-batteries-inlcuded’ feature generator at a given path (folder)
- Parameters
- pathstr
path to save to
- Returns
- frozen
FeatureGeneratorBase
- class aydin.features.base.FeatureGeneratorBase[source]
Feature Generator base class
- abstract compute(image, exclude_center_feature=False, exclude_center_value=False, features=None, feature_last_dim=True, passthrough_channels=None, num_reserved_features=0, excluded_voxels=None, spatial_feature_offset=None, spatial_feature_scale=None)[source]
Computes the features given an image. If the input image is of shape (d,h,w), resulting features are of shape (n,d,h,w) where n is the number of features.
- Parameters
- imagenumpy.ndarray
image for which features are computed
- exclude_center_featurebool
- exclude_center_valuebool
- features
- feature_last_dimbool
- passthrough_channels
- num_reserved_featuresint
- excluded_voxels
- spatial_feature_offset
- spatial_feature_scale
- Returns
- feature arraynumpy.ndarray
- create_feature_array(image, nb_features)[source]
Creates a feature array of the right size and possibly in a ‘lazy’ way using memory mapping.
- Parameters
- imagenumpy.ndarray
image for which features are created
- nb_featuresint
- Returns
- feature arraynumpy.ndarray