habitat.datasets.pointnav.pointnav_dataset.PointNavDatasetV1 class

Class inherited from Dataset that loads Point Navigation dataset.

Class methods

def build_content_scenes_filter(config) -> typing.Callable[[T], bool]: Returns a filter function that takes an episode and returns True if that episode is valid under the content_scenes field of the provided config
def get_scenes_to_load(config: DictConfig) -> typing.List[str]: Return list of scene ids for which dataset has separate files with episodes.

Static methods

def check_config_paths_exist(config: DictConfig) -> bool

Methods

def _load_from_file(self, fname: str, scenes_dir: str) -> None: Load the data from a file into self.episodes. This can load .pickle or .json.gz file formats.
def filter_episodes(self, filter_fn: typing.Callable[[T], bool]) -> core.dataset.Dataset: Returns a new dataset with only the filtered episodes from the original dataset.
def from_binary(self, data_dict: typing.Dict[str, typing.Any], scenes_dir: typing.Optional[str] = None) -> None
def from_json(self, json_str: str, scenes_dir: typing.Optional[str] = None) -> None
def get_episode_iterator(self, *args: typing.Any, **kwargs: typing.Any) -> typing.Iterator[T]: Gets episode iterator with options. Options are specified in EpisodeIterator documentation.
def get_episodes(self, indexes: typing.List[int]) -> typing.List[T]: Get all episodes from a set of indices.
def get_scene_episodes(self, scene_id: str) -> typing.List[T]: Get all episodes involving a particular scene.
def get_splits(self, num_splits: int, episodes_per_split: typing.Optional[int] = None, remove_unused_episodes: bool = False, collate_scene_ids: bool = True, sort_by_episode_id: bool = False, allow_uneven_splits: bool = False) -> typing.List[core.dataset.Dataset]: Returns a list of new datasets, each with a subset of the original episodes.
def scene_from_scene_path(scene_path: str) -> str: Helper method to get the scene name from an episode.
def to_binary(self) -> typing.Dict[str, typing.Any]
def to_json(self) -> str: Serialize the Dataset into JSON formatted string so it can be written to a file.

Special methods

def __init__(self, config: typing.Optional[DictConfig] = None)

Properties

num_episodes: int get: number of episodes in the dataset
scene_ids: typing.List[str] get: unique scene ids present in the dataset.

Data

content_scenes_path: str = '{data_path}/content/{scene}.json.gz'
episodes: typing.List[tasks.nav.nav.NavigationEpisode] = None

Method documentation

def habitat.datasets.pointnav.pointnav_dataset.PointNavDatasetV1.filter_episodes(self, filter_fn: typing.Callable[[T], bool]) -> core.dataset.Dataset

Returns a new dataset with only the filtered episodes from the original dataset.

Parameters
filter_fn	function used to filter the episodes.
Returns	the new dataset.

def habitat.datasets.pointnav.pointnav_dataset.PointNavDatasetV1.get_episode_iterator(self, *args: typing.Any, **kwargs: typing.Any) -> typing.Iterator[T]

Gets episode iterator with options. Options are specified in EpisodeIterator documentation.

Parameters
args	positional args for iterator constructor
kwargs	keyword args for iterator constructor
Returns	episode iterator with specified behavior

To further customize iterator behavior for your Dataset subclass, create a customized iterator class like EpisodeIterator and override this method.

def habitat.datasets.pointnav.pointnav_dataset.PointNavDatasetV1.get_episodes(self, indexes: typing.List[int]) -> typing.List[T]

Get all episodes from a set of indices.

Parameters
indexes	episode indices in dataset.
Returns	list of episodes corresponding to indexes.

def habitat.datasets.pointnav.pointnav_dataset.PointNavDatasetV1.get_scene_episodes(self, scene_id: str) -> typing.List[T]

Get all episodes involving a particular scene.

Parameters
scene_id	id of scene in scene dataset.
Returns	list of episodes for the `scene_id`.

def habitat.datasets.pointnav.pointnav_dataset.PointNavDatasetV1.get_splits(self, num_splits: int, episodes_per_split: typing.Optional[int] = None, remove_unused_episodes: bool = False, collate_scene_ids: bool = True, sort_by_episode_id: bool = False, allow_uneven_splits: bool = False) -> typing.List[core.dataset.Dataset]

Returns a list of new datasets, each with a subset of the original episodes.

Parameters
num_splits	the number of splits to create.
episodes_per_split	if provided, each split will have up to this many episodes. If it is not provided, each dataset will have `len(original_dataset.episodes) // num_splits` episodes. If max_episodes_per_split is provided and is larger than this value, it will be capped to this value.
remove_unused_episodes	once the splits are created, the extra episodes will be destroyed from the original dataset. This saves memory for large datasets.
collate_scene_ids	if true, episodes with the same scene id are next to each other. This saves on overhead of switching between scenes, but means multiple sequential episodes will be related to each other because they will be in the same scene.
sort_by_episode_id	if true, sequences are sorted by their episode ID in the returned splits.
allow_uneven_splits	if true, the last splits can be shorter than the others. This is especially useful for splitting over validation/test datasets in order to make sure that all episodes are copied but none are duplicated.
Returns	a list of new datasets, each with their own subset of episodes.

All splits will have the same number of episodes, but no episodes will be duplicated.

def habitat.datasets.pointnav.pointnav_dataset.PointNavDatasetV1.scene_from_scene_path(scene_path: str) -> str

Helper method to get the scene name from an episode.

Parameters
scene_path	The path to the scene, assumes this is formatted: `/path/to/<scene_name>.<ext>`
Returns	<scene_name> from the path