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# Source code for torchvision.datasets.sbu

    import os
    from typing import Any, Callable, Optional, Tuple

    from PIL import Image

    from .utils import check_integrity, download_and_extract_archive, download_url
    from .vision import VisionDataset

    class SBU(VisionDataset):
        """`SBU Captioned Photo <http://www.cs.virginia.edu/~vicente/sbucaptions/>`_ Dataset.

        Args:
            root (string): Root directory of dataset where tarball
                ``SBUCaptionedPhotoDataset.tar.gz`` 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.
        """

        url = "https://www.cs.rice.edu/~vo9/sbucaptions/SBUCaptionedPhotoDataset.tar.gz"
        filename = "SBUCaptionedPhotoDataset.tar.gz"
        md5_checksum = "9aec147b3488753cf758b4d493422285"

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

            if download:
                self.download()

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

            # Read the caption for each photo
            self.photos = []
            self.captions = []

            file1 = os.path.join(self.root, "dataset", "SBU_captioned_photo_dataset_urls.txt")
            file2 = os.path.join(self.root, "dataset", "SBU_captioned_photo_dataset_captions.txt")

            for line1, line2 in zip(open(file1), open(file2)):
                url = line1.rstrip()
                photo = os.path.basename(url)
                filename = os.path.join(self.root, "dataset", photo)
                if os.path.exists(filename):
                    caption = line2.rstrip()
                    self.photos.append(photo)
                    self.captions.append(caption)

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

            Returns:
                tuple: (image, target) where target is a caption for the photo.
            """
            filename = os.path.join(self.root, "dataset", self.photos[index])
            img = Image.open(filename).convert("RGB")
            if self.transform is not None:
                img = self.transform(img)

            target = self.captions[index]
            if self.target_transform is not None:
                target = self.target_transform(target)

            return img, target

        def __len__(self) -> int:
            """The number of photos in the dataset."""
            return len(self.photos)

        def _check_integrity(self) -> bool:
            """Check the md5 checksum of the downloaded tarball."""
            root = self.root
            fpath = os.path.join(root, self.filename)
            if not check_integrity(fpath, self.md5_checksum):
                return False
            return True

        def download(self) -> None:
            """Download and extract the tarball, and download each individual photo."""

            if self._check_integrity():
                print("Files already downloaded and verified")
                return

            download_and_extract_archive(self.url, self.root, self.root, self.filename, self.md5_checksum)

            # Download individual photos
            with open(os.path.join(self.root, "dataset", "SBU_captioned_photo_dataset_urls.txt")) as fh:
                for line in fh:
                    url = line.rstrip()
                    try:
                        download_url(url, os.path.join(self.root, "dataset"))
                    except OSError:
                        # The images point to public images on Flickr.
                        # Note: Images might be removed by users at anytime.
                        pass

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