Skip to content

Latest commit

 

History

History
51 lines (40 loc) · 3.74 KB

AUGMENTATION.md

File metadata and controls

51 lines (40 loc) · 3.74 KB

Augmentations

class Augmentation:
    def _augment(self, sample: Sample) -> Sample:
        raise NotImplementedError("Please Implement this method")

    def _set_metadata(self, sample: Sample) -> Sample:
        return sample

    def __call__(self, sample: Sample) -> Sample:
        sample = init_augmentation(sample)
        sample = self._augment(sample)
        sample = self._set_metadata(sample)
        return sample

Base types of augmentations

Interface Description Metadata Changes Code
Augmentation Base Augmentation class from which every Augmentation inherits None here
OODAugmentation Augmentation that transforms ID images into OOD images e.g. artifacts OOD Flag, Augmentation severity if provided here
INAugmentation Augmentation that does not change the OOD flag but keeps the data IN Distribution e.g. cropping or resizing of images None here
AugmentationComposite An Augmentation composite is a combination of multiple augmentations e.g. pick N of a list Dependent of parameters here

Special types of augmentations

Interface Description Metadata Changes Code
SampableAugmentation Sample Augmentation have sampable parameters which makes it possible to run an experiment with augmentations with different parameter values e.g. different scales for artifacts Keeps Changes of base augmentation here
ArtifactAugmentation An Artifact Augmentation is a realization of an OODAugmentation and therefore inherits from it. This interface comes with a method that overlays an artifact on the image like OODAugmentation here

FrOoDos Augmentations

Name Short description Interface Code
DarkSpotsAugmentation Creates a dark spot on the image ArtifactAugmentation, SampableAugmentation, OODAugmentation here
FatAugmentation Creates a fat drop on the image ArtifactAugmentation, SampableAugmentation, OODAugmentation here
SquamousAugmentation Creates a tissue piece on the image ArtifactAugmentation, SampableAugmentation, OODAugmentation here
ThreadAugmentation Creates a thread on the image ArtifactAugmentation, SampableAugmentation, OODAugmentation here
GaussianBlurAugmentation Blures the image SampableAugmentation, OODAugmentation here
ZoomInAugmentation Crops the image and then resizes it back to original size SampableAugmentation, OODAugmentation here
BrightnessAugmentation Changes brightness of image SampableAugmentation, OODAugmentation here
InCrop Crops image INAugmentation here
InResize Resizes image INAugmentation here

References

[1] Schömig-Markiefka, B., Pryalukhin, A., Hulla, W., Bychkov, A., Fukuoka, J., Mad- abhushi, A., Achter, V., Nieroda, L., Büttner, R., Quaas, A., et al.: Quality control stress test for deep learning-based diagnostic model in digital pathology. Modern Pathology (2021)