All Classes and Interfaces

Class	Description
DecodeInstanceSegmentation<T>	Decodes inference output into segmented-objects.
DualScale<T>	Stores two versions of the same object, representing two different scales.
ImageInferenceContext	Attributes describing the situation in which inference on images is occurring.
ImageInferenceModel<T>	A model used for inference that accepts an image as an input.
LabelledWithConfidence<T>	Like WithConfidence but additionally adds a label.
MultiScaleObject	An ObjectMask that exists at multiple scales.
ObjectForReduction	An object that can be reduced.
ObjectForReductionFactory	Utility functions for creating one or more ObjectForReductions.
ReduceElements<T>	Reduces the number or spatial-extent of elements by favoring higher-confidence elements over lower-confidence elements.
ReduceElementsGreedy	Reduces the number or spatial-extent of elements by favouring higher-confidence elements over lower-confidence elements.
ReduceObjectsGraph	Combines a PriorityQueue (ordering by highest confidence) and a graph-structure indicating which objects overlap with each other.
ReductionOutcome<T>	The result of a reduction operation.
RemoveOverlappingObjects	Intersecting objects are removed if they have sufficient overlap.
ScaleAndThresholdVoxels	Scales the size of a Voxels<FloatBuffer> and then thresholds it.
SegmentedBackground	The background to a segmentation.
SegmentedObjects	Objects that are a result of an instance-segmentation.
SegmentedObjectsAtScale	Exposes a particular set of segmented-objects at a particular scale.
SegmentStackIntoObjectsPooled<T>	A base class for algorithms to segment a stack into one or more objects - using a pool of models
SegmentStackIntoObjectsScaleDecode<T,S>	A SegmentStackIntoObjectsScaleDecode that scales the input image, before performing inference, and then decodes the output.
SuppressNonMaximum<T>	Applies a segmentation procedure followed by non-maximum suppression.
WithConfidence<T>	Wraps an element with a confidence-score.