Module `pandaset.dataset`

Expand source code

#!/usr/bin/env python3
from typing import overload, List, Dict

from .sequence import Sequence
from .utils import subdirectories


class DataSet:
    """Top-level class to load PandaSet

        ``DataSet`` prepares and loads ``Sequence`` objects for every sequence found in provided directory.
        Access to a specific sequence is provided by using the sequence name as a key on the ``DataSet`` object.

        Args:
             directory: Absolute or relative path where PandaSet has been extracted to.

        Examples:
            >>> pandaset = DataSet('/data/pandaset')
            >>> s = pandaset['002']
        """

    def __init__(self, directory: str) -> None:
        self._directory: str = directory
        self._sequences: Dict[str, Sequence] = None
        self._load_sequences()

    def __getitem__(self, item) -> Sequence:
        return self._sequences[item]

    def _load_sequences(self) -> None:
        self._sequences = {}
        sequence_directories = subdirectories(self._directory)
        for sd in sequence_directories:
            seq_id = sd.split('/')[-1].split('\\')[-1]
            self._sequences[seq_id] = Sequence(sd)

    def sequences(self, with_semseg: bool = False) -> List[str]:
        """ Lists all available sequence names

        Args:
            with_semseg: Set `True` if only sequences with semantic segmentation annotations should be returned. Set `False` to return all sequences (with or without semantic segmentation).

        Returns:
            List of sequence names.

        Examples:
            >>> pandaset = DataSet('/data/pandaset')
            >>> print(pandaset.sequences())
            ['002','004','080']


        """
        if with_semseg:
            return [s for s in list(self._sequences.keys()) if self._sequences[s].semseg]
        else:
            return list(self._sequences.keys())


if __name__ == '__main__':
    pass

Classes

class DataSet (directory: str)

Top-level class to load PandaSet

DataSet prepares and loads Sequence objects for every sequence found in provided directory. Access to a specific sequence is provided by using the sequence name as a key on the DataSet object.

Args

directory: Absolute or relative path where PandaSet has been extracted to.

Examples

>>> pandaset = DataSet('/data/pandaset')
>>> s = pandaset['002']

Expand source code

class DataSet:
    """Top-level class to load PandaSet

        ``DataSet`` prepares and loads ``Sequence`` objects for every sequence found in provided directory.
        Access to a specific sequence is provided by using the sequence name as a key on the ``DataSet`` object.

        Args:
             directory: Absolute or relative path where PandaSet has been extracted to.

        Examples:
            >>> pandaset = DataSet('/data/pandaset')
            >>> s = pandaset['002']
        """

    def __init__(self, directory: str) -> None:
        self._directory: str = directory
        self._sequences: Dict[str, Sequence] = None
        self._load_sequences()

    def __getitem__(self, item) -> Sequence:
        return self._sequences[item]

    def _load_sequences(self) -> None:
        self._sequences = {}
        sequence_directories = subdirectories(self._directory)
        for sd in sequence_directories:
            seq_id = sd.split('/')[-1].split('\\')[-1]
            self._sequences[seq_id] = Sequence(sd)

    def sequences(self, with_semseg: bool = False) -> List[str]:
        """ Lists all available sequence names

        Args:
            with_semseg: Set `True` if only sequences with semantic segmentation annotations should be returned. Set `False` to return all sequences (with or without semantic segmentation).

        Returns:
            List of sequence names.

        Examples:
            >>> pandaset = DataSet('/data/pandaset')
            >>> print(pandaset.sequences())
            ['002','004','080']


        """
        if with_semseg:
            return [s for s in list(self._sequences.keys()) if self._sequences[s].semseg]
        else:
            return list(self._sequences.keys())

Methods

def sequences(self, with_semseg: bool = False) -> List[str]

Lists all available sequence names

Args

with_semseg: Set True if only sequences with semantic segmentation annotations should be returned. Set False to return all sequences (with or without semantic segmentation).

Returns

List of sequence names.

Examples

>>> pandaset = DataSet('/data/pandaset')
>>> print(pandaset.sequences())
['002','004','080']

Expand source code

def sequences(self, with_semseg: bool = False) -> List[str]:
    """ Lists all available sequence names

    Args:
        with_semseg: Set `True` if only sequences with semantic segmentation annotations should be returned. Set `False` to return all sequences (with or without semantic segmentation).

    Returns:
        List of sequence names.

    Examples:
        >>> pandaset = DataSet('/data/pandaset')
        >>> print(pandaset.sequences())
        ['002','004','080']


    """
    if with_semseg:
        return [s for s in list(self._sequences.keys()) if self._sequences[s].semseg]
    else:
        return list(self._sequences.keys())