Source code for torchvision.datasets.sbu

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

from PIL import Image

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

[docs]class SBU(VisionDataset): """`SBU Captioned Photo <>`_ Dataset. Args: root (str or ``pathlib.Path``): 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 = "" filename = "SBUCaptionedPhotoDataset.tar.gz" md5_checksum = "9aec147b3488753cf758b4d493422285" def __init__( self, root: Union[str, Path], transform: Optional[Callable] = None, target_transform: Optional[Callable] = None, download: bool = True, ) -> None: super().__init__(root, transform=transform, target_transform=target_transform) if 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.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.captions.append(caption)
[docs] 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",[index]) img ="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( 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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