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import os
from pathlib import Path
from typing import Any, Callable, Optional, Tuple, Union
from .folder import default_loader
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 (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 or torch.Tensor, depends on the given loader,
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.
loader (callable, optional): A function to load an image given its path.
By default, it uses PIL as its image loader, but users could also pass in
``torchvision.io.decode_image`` for decoding image data into tensors directly.
"""
url = "https://www.cs.rice.edu/~vo9/sbucaptions/SBUCaptionedPhotoDataset.tar.gz"
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,
loader: Callable[[str], Any] = default_loader,
) -> None:
super().__init__(root, transform=transform, target_transform=target_transform)
self.loader = loader
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 = self.loader(filename)
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():
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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