Source code for torchvision.datasets.eurosat

import os
from pathlib import Path
from typing import Callable, Optional, Union

from .folder import ImageFolder
from .utils import download_and_extract_archive

[docs]class EuroSAT(ImageFolder): """RGB version of the `EuroSAT <>`_ Dataset. Args: root (str or ``pathlib.Path``): Root directory of dataset where ``root/eurosat`` exists. transform (callable, optional): A function/transform that takes in a PIL image and returns a transformed version. E.g, ``transforms.RandomCrop`` target_transform (callable, optional): A function/transform that takes in the target and transforms it. download (bool, optional): If True, downloads the dataset from the internet and puts it in root directory. If dataset is already downloaded, it is not downloaded again. Default is False. """ def __init__( self, root: Union[str, Path], transform: Optional[Callable] = None, target_transform: Optional[Callable] = None, download: bool = False, ) -> None: self.root = os.path.expanduser(root) self._base_folder = os.path.join(self.root, "eurosat") self._data_folder = os.path.join(self._base_folder, "2750") if download: if not self._check_exists(): raise RuntimeError("Dataset not found. You can use download=True to download it") super().__init__(self._data_folder, transform=transform, target_transform=target_transform) self.root = os.path.expanduser(root) def __len__(self) -> int: return len(self.samples) def _check_exists(self) -> bool: return os.path.exists(self._data_folder) def download(self) -> None: if self._check_exists(): return os.makedirs(self._base_folder, exist_ok=True) download_and_extract_archive( "", download_root=self._base_folder, md5="c8fa014336c82ac7804f0398fcb19387", )


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