89 lines
3.4 KiB
Python
89 lines
3.4 KiB
Python
|
import json
|
||
|
|
import pathlib
|
||
|
|
from typing import Any, Callable, List, Optional, Tuple, Union
|
||
|
|
from urllib.parse import urlparse
|
||
|
|
|
||
|
|
from PIL import Image
|
||
|
|
|
||
|
|
from .utils import download_and_extract_archive, verify_str_arg
|
||
|
|
from .vision import VisionDataset
|
||
|
|
|
||
|
|
|
||
|
|
class CLEVRClassification(VisionDataset):
|
||
|
|
"""`CLEVR <https://cs.stanford.edu/people/jcjohns/clevr/>`_ classification dataset.
|
||
|
|
|
||
|
|
The number of objects in a scene are used as label.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
root (str or ``pathlib.Path``): Root directory of dataset where directory ``root/clevr`` exists or will be saved to if download is
|
||
|
|
set to True.
|
||
|
|
split (string, optional): The dataset split, supports ``"train"`` (default), ``"val"``, or ``"test"``.
|
||
|
|
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 them 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://dl.fbaipublicfiles.com/clevr/CLEVR_v1.0.zip"
|
||
|
|
_MD5 = "b11922020e72d0cd9154779b2d3d07d2"
|
||
|
|
|
||
|
|
def __init__(
|
||
|
|
self,
|
||
|
|
root: Union[str, pathlib.Path],
|
||
|
|
split: str = "train",
|
||
|
|
transform: Optional[Callable] = None,
|
||
|
|
target_transform: Optional[Callable] = None,
|
||
|
|
download: bool = False,
|
||
|
|
) -> None:
|
||
|
|
self._split = verify_str_arg(split, "split", ("train", "val", "test"))
|
||
|
|
super().__init__(root, transform=transform, target_transform=target_transform)
|
||
|
|
self._base_folder = pathlib.Path(self.root) / "clevr"
|
||
|
|
self._data_folder = self._base_folder / pathlib.Path(urlparse(self._URL).path).stem
|
||
|
|
|
||
|
|
if download:
|
||
|
|
self._download()
|
||
|
|
|
||
|
|
if not self._check_exists():
|
||
|
|
raise RuntimeError("Dataset not found or corrupted. You can use download=True to download it")
|
||
|
|
|
||
|
|
self._image_files = sorted(self._data_folder.joinpath("images", self._split).glob("*"))
|
||
|
|
|
||
|
|
self._labels: List[Optional[int]]
|
||
|
|
if self._split != "test":
|
||
|
|
with open(self._data_folder / "scenes" / f"CLEVR_{self._split}_scenes.json") as file:
|
||
|
|
content = json.load(file)
|
||
|
|
num_objects = {scene["image_filename"]: len(scene["objects"]) for scene in content["scenes"]}
|
||
|
|
self._labels = [num_objects[image_file.name] for image_file in self._image_files]
|
||
|
|
else:
|
||
|
|
self._labels = [None] * len(self._image_files)
|
||
|
|
|
||
|
|
def __len__(self) -> int:
|
||
|
|
return len(self._image_files)
|
||
|
|
|
||
|
|
def __getitem__(self, idx: int) -> Tuple[Any, Any]:
|
||
|
|
image_file = self._image_files[idx]
|
||
|
|
label = self._labels[idx]
|
||
|
|
|
||
|
|
image = Image.open(image_file).convert("RGB")
|
||
|
|
|
||
|
|
if self.transform:
|
||
|
|
image = self.transform(image)
|
||
|
|
|
||
|
|
if self.target_transform:
|
||
|
|
label = self.target_transform(label)
|
||
|
|
|
||
|
|
return image, label
|
||
|
|
|
||
|
|
def _check_exists(self) -> bool:
|
||
|
|
return self._data_folder.exists() and self._data_folder.is_dir()
|
||
|
|
|
||
|
|
def _download(self) -> None:
|
||
|
|
if self._check_exists():
|
||
|
|
return
|
||
|
|
|
||
|
|
download_and_extract_archive(self._URL, str(self._base_folder), md5=self._MD5)
|
||
|
|
|
||
|
|
def extra_repr(self) -> str:
|
||
|
|
return f"split={self._split}"
|