dgs.models.dataset.dataset.BBoxDataset

class dgs.models.dataset.dataset.BBoxDataset(*args: Any, **kwargs: Any)

A dataset using the bounding boxes as indices. See BaseDataset for more information.

__init__(config: dict[str, any], path: list[str]) → None

Methods

arbitrary_to_ds(a, idx)	Given a single bounding box (ID) and other arbitrary data, convert everything to a State object.
configure_torch_module(module[, train])	Set compute mode and send model to the device or multiple parallel devices if applicable.
get_image_crops(ds)	Add the image crops and local key-points to a given state.
get_path_in_dataset(path)	Given an arbitrary file- or directory-path, return its absolute path.
terminate()	Terminate this module and all of its submodules.
transform_crop_resize()	Given one single image, with its corresponding bounding boxes and key-points, obtain a cropped image for every bounding box with localized key-points.
transform_resize_image()	Given an image, bboxes, and key-points, resize them with custom modes.
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.
data	Arbitrary data, which will be converted using self.arbitrary_to_ds()
dataset_path	The base path to the dataset.