93 lines
3.1 KiB
Python
93 lines
3.1 KiB
Python
import os.path
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from pathlib import Path
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from typing import Any, Callable, Optional, Tuple, Union
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import numpy as np
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from PIL import Image
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from .utils import check_integrity, download_url
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from .vision import VisionDataset
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class SEMEION(VisionDataset):
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r"""`SEMEION <http://archive.ics.uci.edu/ml/datasets/semeion+handwritten+digit>`_ Dataset.
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Args:
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root (str or ``pathlib.Path``): Root directory of dataset where directory
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``semeion.py`` exists.
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transform (callable, optional): A function/transform that takes in a PIL image
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and returns a transformed version. E.g, ``transforms.RandomCrop``
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target_transform (callable, optional): A function/transform that takes in the
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target and transforms it.
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download (bool, optional): If true, downloads the dataset from the internet and
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puts it in root directory. If dataset is already downloaded, it is not
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downloaded again.
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"""
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url = "http://archive.ics.uci.edu/ml/machine-learning-databases/semeion/semeion.data"
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filename = "semeion.data"
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md5_checksum = "cb545d371d2ce14ec121470795a77432"
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def __init__(
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self,
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root: Union[str, Path],
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transform: Optional[Callable] = None,
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target_transform: Optional[Callable] = None,
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download: bool = True,
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) -> None:
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super().__init__(root, transform=transform, target_transform=target_transform)
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if download:
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self.download()
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if not self._check_integrity():
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raise RuntimeError("Dataset not found or corrupted. You can use download=True to download it")
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fp = os.path.join(self.root, self.filename)
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data = np.loadtxt(fp)
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# convert value to 8 bit unsigned integer
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# color (white #255) the pixels
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self.data = (data[:, :256] * 255).astype("uint8")
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self.data = np.reshape(self.data, (-1, 16, 16))
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self.labels = np.nonzero(data[:, 256:])[1]
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def __getitem__(self, index: int) -> Tuple[Any, Any]:
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"""
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Args:
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index (int): Index
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Returns:
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tuple: (image, target) where target is index of the target class.
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"""
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img, target = self.data[index], int(self.labels[index])
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# doing this so that it is consistent with all other datasets
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# to return a PIL Image
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img = Image.fromarray(img, mode="L")
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if self.transform is not None:
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img = self.transform(img)
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if self.target_transform is not None:
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target = self.target_transform(target)
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return img, target
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def __len__(self) -> int:
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return len(self.data)
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def _check_integrity(self) -> bool:
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root = self.root
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fpath = os.path.join(root, self.filename)
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if not check_integrity(fpath, self.md5_checksum):
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return False
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return True
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def download(self) -> None:
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if self._check_integrity():
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print("Files already downloaded and verified")
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return
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root = self.root
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download_url(self.url, root, self.filename, self.md5_checksum)
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