Uses of Package
org.anchoranalysis.core.functional.checked

Package
Description
A pairing of objects from two collections (bipartite matching).
Caching (memozing) calls to a method so an operation does not need to be repeated.
Collection-related classes with general applicability that don't belong elsewhere.
Utilities and interfaces for applying functional-programming.
A collection of named-elements, a NamedProvider and related operations.
Recording the execution-time of operations for profiling.
A feature-list (custom list type for features) and associated providers.
Defines the key data object, Stack, and related classes.
A collection of Stacks, each with a unique identifier as a name.
Inference of machine learning models on images.
Non-bean classes for reading a Stack from the filesystem.
Base classes for generators that ultimately write a Stack to the filesystem.
The fundamental data class that is an ObjectMask and related structures.
Specifying how many CPUs and GPUs can be allocated for some purpose.
Base-classes and utilities for generators, which write different types of objects to the file system.
Writing a sequence of elements using a generator.
Classes relating to creating inputs for an experiment / task.
Beans to find a subset of files that match a particular conditions on their paths.
Non-bean classes to help with org.anchoranalysis.io.input.bean.path.matcher.
A centralized location for all command-line options used by the launcher.
Adding/removing/changing the arguments (input and output) from the experiment via command-line-options.
Implementations of FeatureSingleObject.
Implementations of FeatureSingleObject that determine if an object lies at the border of an image.
Implementations of FeatureSingleObject that reference a particular Channel in the associated EnergyStack.
Combining multiple images together into a single image.
Tasks that involved stacks (usually each channel from an image) that are somehow grouped-together.
Task(s) to export histograms of intensity values.
Non-bean classes pertaining to Features as used in tasks.
Non-bean classes about grouping channels or other inputs.
Non-bean classes pertaining to combining stacks into a single stack.
Non-bean classes for running an inference model with the ONNX Runtime.
Non-bean classes pertaining to segmentation.
CalculationPart related to fitting ellipsoids to points by least-squares.
Axis-aligned bounding-boxes and related operations.
A mocked feature internally using a feature-calculation.