dgs.models.dataset.MOT.MOTImageHistory

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

Load a ground-truth- or detection-file in the MOT format by making sure, that all detections except the first L ones are loaded and are returned with the history.

Params

data_path (FilePath):

The local or absolute path to the txt or csv file containing the MOT annotations.

Optional Params

file_separator (str, optional):

The str or regular expression used to split the lines in the annotation file. Default DEF_VAL["dataset"]["MOT"]["file_separator"].

crop_key (str, optional):

The name of the key in the seqinfo file containing the info for the image crops. Default DEF_VAL["dataset"]["MOT"]["crop_key"].

seqinfo_path (str, optional):

The optional path to the seqinfo.ini file. Default DEF_VAL["dataset"]["MOT"]["seqinfo_path"].

seqinfo_key (str, optional):

The key to use in the seqinfo file. Default DEF_VAL["submission"]["MOT"]["seqinfo_key"].

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

Methods

arbitrary_to_ds(a, idx)	Given a single image ID or filepath, obtain the image, bbox, and possibly more information, then 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()
L
dataset_path	The base path to the dataset.