v0.1.0
======

Initial release of the Natural Robustness Toolkit originally ported from prior work.

Updates / New Features
----------------------

CI/CD

* Added code unit-test and coverage reporting.

* Added code coverage minimum coverage soft check (allows failure).

Documentation

* Added baseline interface and implementation documentation sections.

* Updated and added relevant documents detailing the components of our Open
  Source Strategy.

* Added ability to render documentation on GitLab Pages.

Examples

* Updated and added relevant documents detailing the components of our Open
  Source Strategy.

Examples

* Added an example notebook demonstrating NRTK perturber functionality.

* Added an example notebook demonstrating NRTK generic generator functionality.

* Added an example notebook demonstrating NRTK pybsm generator functionality.

* Added an example notebook demonstrating NRTK ``COCOScorer`` functionality.

Interfaces

* Added a ``GenerateObjectDetectorBlackboxResponse`` interface for generating
  response curves with given perturber factories, detector, and scorer.

* Added a ``PerturbImage`` interface for taking an image stimulus and
  generating a perturbed image.

* Added a ``PerturbImageFactory`` interface for generating ``PerturbImage``
  instances of specified type and configuration while varying one parameter.

* Added a ``ScoreDetection`` interface that takes in ground-truth and predicted
  BBox-label pairs and generates scores based on a given metric.

Implementations

* Add an example ``GenerateObjectDetectorBlackboxResponse`` implementation,
  ``SimpleGenericGenerator`` which takes takes input data directly as Sequences.

* Added several ``PerturbImage`` implementations:

  * From ``opencv``:

    * ``AverageBlurPerturber``: Applies average blurring to the given image
      stimulus.

    * ``GaussianBlurPerturber``: Applies Gaussian blurring to the given image
      stimulus.

    * ``MedianBlurPerturber``: Applies median blurring to the given image
      stimulus.

  * From ``skimage``:

    * ``SaltNoisePerturber``, ``PepperNoisePerturber``,
      ``SaltAndPepperNoisePerturber``: Adds salt and/or pepper noise to given
      image stimulus.

    * ``GaussianNoisePerturber``: Adds Gaussian-distributed additive noise to
      given image stimulus.

    * ``SpeckleNoisePerturber``: Adds multiplicative (Gaussian) noise to given
      image stimulus.

  * From ``PIL``:

    * ``BrightnessPerturber``: Adjusts given image stimulus brightness.

    * ``ColorPerturber``: Adjusts given image stimulus color balance.

    * ``ContrastPerturber``: Adjust given image stimulus contrast.

    * ``SharpnessPerturber``: Adjust given image stimulus sharpness.

  * ``NOPPerturber``: Serves as a pass-through NOP perturber to test interface
    functionality.

  * From ``xaitk-irt``:

    * ``PybsmSensor``: Holds sensor parameters for pyBSM perturbation.

    * ``PybsmScenario``: Holds target and environment parameters for pyBSM
      perturbation.

    * ``PybsmPerturber``: Matches PerturbImage interface and is used by pybsm factories.

    * ``_PybsmPerturbImageFactory``: Base PyBSM perturber factory.

    * ``CustomPybsmPerturbImageFactory``: Original "custom" pybsm perturber factory.

* Added a ``PerturbImageFactory`` implementation, ``StepPerturbImageFactory``,
  which is a simple implementation that varies a chosen parameter from
  ``start`` to ``stop`` by the given ``step`` value.

* Added ``ScoreDetections`` implementations

  * ``NOPScorer``: Serves as a pass-through NOP scorer to test interface
    functionality.

  * ``RandomScorer``: Generates random score values and serves as a test for
    reproducibility.

  * ``COCOScorer``: Generates detection scores for a specific statistic index
    using the converted COCO format data.

  * ``ClassAgnosticPixelwiseIoUScorer``: Generates pixelwise IoU scores in a
    class agnostic way.

Fixes
-----

* Changed the default git client poetry uses from dulwich to system-installed git.