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# Source code for torchvision.datasets.omniglot

    from os.path import join
    from typing import Any, Callable, List, Optional, Tuple

    from PIL import Image

    from .utils import check_integrity, download_and_extract_archive, list_dir, list_files
    from .vision import VisionDataset

    class Omniglot(VisionDataset):
        """`Omniglot <https://github.com/brendenlake/omniglot>`_ Dataset.

        Args:
            root (string): Root directory of dataset where directory
                ``omniglot-py`` exists.
            background (bool, optional): If True, creates dataset from the "background" set, otherwise
                creates from the "evaluation" set. This terminology is defined by the authors.
            transform (callable, optional): A function/transform that  takes in an 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 zip files from the internet and
                puts it in root directory. If the zip files are already downloaded, they are not
                downloaded again.
        """

        folder = "omniglot-py"
        download_url_prefix = "https://raw.githubusercontent.com/brendenlake/omniglot/master/python"
        zips_md5 = {
            "images_background": "68d2efa1b9178cc56df9314c21c6e718",
            "images_evaluation": "6b91aef0f799c5bb55b94e3f2daec811",
        }

        def __init__(
            self,
            root: str,
            background: bool = True,
            transform: Optional[Callable] = None,
            target_transform: Optional[Callable] = None,
            download: bool = False,
        ) -> None:
            super().__init__(join(root, self.folder), transform=transform, target_transform=target_transform)
            self.background = background

            if download:
                self.download()

            if not self._check_integrity():
                raise RuntimeError("Dataset not found or corrupted. You can use download=True to download it")

            self.target_folder = join(self.root, self._get_target_folder())
            self._alphabets = list_dir(self.target_folder)
            self._characters: List[str] = sum(
                ([join(a, c) for c in list_dir(join(self.target_folder, a))] for a in self._alphabets), []
            )
            self._character_images = [
                [(image, idx) for image in list_files(join(self.target_folder, character), ".png")]
                for idx, character in enumerate(self._characters)
            ]
            self._flat_character_images: List[Tuple[str, int]] = sum(self._character_images, [])

        def __len__(self) -> int:
            return len(self._flat_character_images)

        def __getitem__(self, index: int) -> Tuple[Any, Any]:
            """
            Args:
                index (int): Index

            Returns:
                tuple: (image, target) where target is index of the target character class.
            """
            image_name, character_class = self._flat_character_images[index]
            image_path = join(self.target_folder, self._characters[character_class], image_name)
            image = Image.open(image_path, mode="r").convert("L")

            if self.transform:
                image = self.transform(image)

            if self.target_transform:
                character_class = self.target_transform(character_class)

            return image, character_class

        def _check_integrity(self) -> bool:
            zip_filename = self._get_target_folder()
            if not check_integrity(join(self.root, zip_filename + ".zip"), self.zips_md5[zip_filename]):
                return False
            return True

        def download(self) -> None:
            if self._check_integrity():
                print("Files already downloaded and verified")
                return

            filename = self._get_target_folder()
            zip_filename = filename + ".zip"
            url = self.download_url_prefix + "/" + zip_filename
            download_and_extract_archive(url, self.root, filename=zip_filename, md5=self.zips_md5[filename])

        def _get_target_folder(self) -> str:
            return "images_background" if self.background else "images_evaluation"

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