IoUEncode

class hybrid_learning.datasets.transforms.image_transforms.IoUEncode(kernel_size, *, proto_shape=None, smooth=None, **thresh_args)

Bases: ConvOpWrapper

IoU encode a single mask. This is a wrapper around BatchIoUEncode2D.

Public Data Attributes:

Inherited from : py: class:ConvOpWrapper

proto_shape	Wrap the proto_shape.
kernel_size	Wrap the kernel_size.
settings	Settings; essentially merged from wrapped encoder and super.

Inherited from : py: class:WithThresh

settings

Settings; essentially merged from wrapped encoder and super.

Inherited from : py: class:BatchWiseImageTransform

settings

Settings; essentially merged from wrapped encoder and super.

Inherited from : py: class:Transform

IDENTITY_CLASS	The identity class or classes for composition / addition.
settings	Settings; essentially merged from wrapped encoder and super.

Public Methods:

Inherited from : py: class:WithThresh

apply_to_batch(masks)

Forward method in which to apply the trafo and thresholding.

Inherited from : py: class:BatchWiseImageTransform

apply_to(mask)	Apply trafo to the mask (either considered as batch of mask or single mask).
apply_to_batch(masks)	Forward method in which to apply the trafo and thresholding.

Inherited from : py: class:ImageTransform

apply_to(mask)

Apply trafo to the mask (either considered as batch of mask or single mask).

Inherited from : py: class:Transform

apply_to(mask)

Apply trafo to the mask (either considered as batch of mask or single mask).

Special Methods:

__init__(kernel_size, *[, proto_shape, smooth])

Init.

Inherited from : py: class:ConvOpWrapper

__init__(kernel_size, *[, proto_shape, smooth])

Init.

Inherited from : py: class:WithThresh

__init__(kernel_size, *[, proto_shape, smooth])

Init.

Inherited from : py: class:BatchWiseImageTransform

__init__(kernel_size, *[, proto_shape, smooth])

Init.

Inherited from : py: class:ImageTransform

__call__(img)

Application of transformation.

Inherited from : py: class:Transform

__repr__()	Return repr(self).
__eq__(other)	Return self==value.
__copy__()	Return a shallow copy of self using settings.
__add__(other)	Return a flat composition of self with other.
__radd__(other)	Return a flat composition of other and self.
__call__(img)	Application of transformation.

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Parameters

• kernel_size (Tuple[int, int]) –

• proto_shape (ndarray) –

• smooth (float) –

__init__(kernel_size, *, proto_shape=None, smooth=None, **thresh_args)

Init.

Parameters

• thresh_args – thresholding arguments; see WithThresh

• kernel_size (Tuple[int, int]) –

• proto_shape (Optional[ndarray]) –

• smooth (Optional[float]) –

batch_wise: bool

Whether to assume a batch of masks is given (True) or a single mask (False).

post_thresholder: Optional[Binarize]

Binarizing transformation applied to targets after IoU encoding if not None.

pre_thresholder: Optional[Binarize]

Binarizing transformation applied to targets before IoU encoding if not None.

trafo: BatchConvOp

Modifier (en- or decoder) module that is used for modifications.