dgs.models.similarity.pose_similarity.IntersectionOverUnion

class dgs.models.similarity.pose_similarity.IntersectionOverUnion(*args: Any, **kwargs: Any)

Use the bounding-box based intersection-over-union as a similarity metric.

Params

__init__(config: dict[str, any], path: list[str])

Methods

configure_torch_module(module[, train])	Set compute mode and send model to the device or multiple parallel devices if applicable.
forward(data, target)	Given two states containing bounding-boxes, compute the intersection over union between each pair.
get_data(ds)	Given a State obtain the ground-truth bounding-boxes as torchvision.tv_tensors.BoundingBoxes object of size [N x 4].
get_target(ds)	Given a State obtain the ground-truth bounding-boxes as torchvision.tv_tensors.BoundingBoxes object of size [T x 4].
get_train_data(ds)	A custom function to get special data for training purposes.
terminate()	Terminate this module and all of its submodules.
validate_params(validations[, attrib_name])	Given per key validations, validate this module's parameters.

Attributes

device	Get the device of this module.
is_training	Get whether this module is set to training-mode.
module_name	Get the name of the module.
module_type
name	Get the name of the module.
name_safe	Get the escaped name of the module usable in filepaths by replacing spaces and underscores.
precision	Get the (floating point) precision used in multiple parts of this module.
softmax