dgs.models.similarity.pose_similarity.ObjectKeypointSimilarity¶

class dgs.models.similarity.pose_similarity.ObjectKeypointSimilarity(*args: Any, **kwargs: Any)[source]¶

Compute the object key-point similarity (OKS) between two batches of poses / States.

Params¶

format (str):: The key point format, e.g., ‘coco’, ‘coco-whole’, … has to be in OKS_SIGMAS.keys().

keypoint_dim (int, optional):: The dimensionality of the key points. So whether 2D or 3D is expected. Default DEF_VAL.similarity.oks.kp_dim.

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

Methods

`configure_torch_module`(module[, train])	Set compute mode and send model to the device or multiple parallel devices if applicable.
`forward`(data, target)	Compute the object key-point similarity between a ground truth label and detected key points.
`get_area`(ds)	Given a `State`, compute the area of the bounding box.
`get_data`(ds)	Given a `State`, compute the detected / predicted key points with shape `[B1 x J x 2\|3]` and the areas of the respective ground-truth bounding-boxes with shape `[B1]`.
`get_target`(ds)	Given a `State` obtain the ground truth key points and the key-point-visibility.
`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`