def _init_ ( self, root : str, image : str, collections : List =, transforms : Optional ], Dict ]] = None, download : bool = False, api_key : Optional = None, checksum : bool = False, ) -> None : """Initialize a new SpaceNet Dataset instance. abstractmethod def chip_size ( self ) -> Dict ]: """Mapping of images and their chip size.""" abstractmethod def collection_md5_dict ( self ) -> Dict : """Mapping of collection id and md5 checksum.""". abstractmethod def label_glob ( self ) -> str : """Label filename.""". abstractmethod def imagery ( self ) -> Dict : """Mapping of image identifier and filename.""". abstractmethod def dataset_id ( self ) -> str : """Dataset ID.""". The `SpaceNet `_ datasets are a set of datasets that all together contain >11M building footprints and ~20,000 km of road labels mapped over high-resolution satellite imagery obtained from a variety of sensors such as Worldview-2, Worldview-3 and Dove. ABC ): """Abstract base class for the SpaceNet datasets. ![]() utils import ( check_integrity, download_radiant_mlhub_collection, extract_archive, percentile_normalization, ) class SpaceNet ( VisionDataset, abc. """SpaceNet datasets.""" import abc import copy import glob import math import os import re from typing import Any, Callable, Dict, List, Optional, Tuple import fiona import matplotlib.pyplot as plt import numpy as np import rasterio as rio import torch from fiona.errors import FionaValueError from ansform import transform_geom from matplotlib.figure import Figure from rasterio.crs import CRS from rasterio.features import rasterize from ansform import Affine from torch import Tensor from.
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