luxonis_ml.data.augmentations.custom.TransposeSymmetricKeypoints

class documentation

class TransposeSymmetricKeypoints(A.DualTransform):

Transpose images and symmetric keypoints.

Method	`__init__`	Transpose an image and symmetric keypoints.
Method	`apply`	Transpose an image.
Method	`apply_to_bboxes`	Transpose bounding boxes.
Method	`apply_to_keypoints`	Transpose keypoints and swap symmetric pairs.
Method	`apply_to_mask`	Transpose a segmentation mask.
Method	`get_params_dependent_on_data`	Get parameters dependent on the targets.
Instance Variable	`keypoint_pairs`	Pairs of keypoint indices swapped after transposition.
Instance Variable	`n_keypoints`	Number of unique keypoints described by `keypoint_pairs`.
Property	`targets`	Undocumented

def __init__(self, keypoint_pairs: list[tuple[int, int]], p: float = 0.5): ¶

Transpose an image and symmetric keypoints.

Equivalent to 90 degree rotation followed by horizontal flip.

Parameters
keypoint_pairs:`list[tuple[int, int]]`	Pairs of keypoint indices to swap after the transpose.
p:`float`	Probability of applying the augmentation.

@override

def apply(self, img: np.ndarray, **params) -> np.ndarray: ¶

Transpose an image.

Parameters
img:`np.ndarray`	Image to transpose.
**params	Additional transform parameters.

Returns
`np.ndarray`	Transposed image.

@override

def apply_to_bboxes(self, bboxes: np.ndarray, **params) -> np.ndarray: ¶

Transpose bounding boxes.

Parameters
bboxes:`np.ndarray`	Bounding boxes to transpose.
**params	Additional transform parameters.

Returns
`np.ndarray`	Transposed bounding boxes.

@override

def apply_to_keypoints(self, keypoints: np.ndarray, **params) -> np.ndarray: ¶

Transpose keypoints and swap symmetric pairs.

Parameters
keypoints:`np.ndarray`	Keypoints to transpose.
**params	Additional transform parameters.

Returns
`np.ndarray`	Transposed keypoints.

Raises
`ValueError`	If the total number of keypoints is not a multiple of `n_keypoints`.

@override

def apply_to_mask(self, mask: np.ndarray, **params) -> np.ndarray: ¶

Transpose a segmentation mask.

Parameters
mask:`np.ndarray`	Segmentation mask to transpose.
**params	Additional transform parameters.

Returns
`np.ndarray`	Transposed segmentation mask.

@override

def get_params_dependent_on_data(self, params: dict[str, Any], data: dict[str, Any]) -> dict[str, Any]: ¶

Get parameters dependent on the targets.

Parameters
params:`dict[str, Any]`	Existing augmentation parameters.
data:`dict[str, Any]`	Input data.

Returns
`dict[str, Any]`	Parameters derived from the input targets.

keypoint_pairs = ¶

Pairs of keypoint indices swapped after transposition.

n_keypoints = ¶

Number of unique keypoints described by keypoint_pairs.

@property
@override

targets: dict[str, Any] = ¶

Undocumented