Source code for torchvision.datasets.semeion

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

import numpy as np
from PIL import Image

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

[docs]class SEMEION(VisionDataset): r"""`SEMEION <>`_ Dataset. Args: root (str or ``pathlib.Path``): Root directory of dataset where directory ```` 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 = "" md5_checksum = "cb545d371d2ce14ec121470795a77432" 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") fp = os.path.join(self.root, self.filename) data = np.loadtxt(fp) # convert value to 8 bit unsigned integer # color (white #255) the pixels = (data[:, :256] * 255).astype("uint8") = np.reshape(, (-1, 16, 16)) self.labels = np.nonzero(data[:, 256:])[1]
[docs] def __getitem__(self, index: int) -> Tuple[Any, Any]: """ Args: index (int): Index Returns: tuple: (image, target) where target is index of the target class. """ img, target =[index], int(self.labels[index]) # doing this so that it is consistent with all other datasets # to return a PIL Image img = Image.fromarray(img, mode="L") if self.transform is not None: img = self.transform(img) if self.target_transform is not None: target = self.target_transform(target) return img, target
def __len__(self) -> int: return len( def _check_integrity(self) -> bool: 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: if self._check_integrity(): print("Files already downloaded and verified") return root = self.root download_url(self.url, root, self.filename, self.md5_checksum)


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