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import io |
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from tqdm import tqdm |
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from PIL import Image |
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from zipfile import ZipFile |
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import datasets |
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class ArabicDigits(datasets.GeneratorBasedBuilder): |
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"""Arabic Handwritten Digits Dataset.""" |
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VERSION = datasets.Version("1.0.0") |
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def _info(self): |
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return datasets.DatasetInfo( |
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description="""Arabic Handwritten Digits Dataset, composed of images of Arabic digits handwritten |
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by participants. This dataset is structured for use in machine learning tasks such |
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as digit classification.""", |
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features=datasets.Features( |
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{ |
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"image": datasets.Image(), |
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"label": datasets.ClassLabel(names=[str(i) for i in range(10)]) |
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} |
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), |
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supervised_keys=("image", "label"), |
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homepage="https://github.com/mloey/Arabic-Handwritten-Digits-Dataset", |
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citation="""@inproceedings{el2016cnn, |
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title={CNN for handwritten arabic digits recognition based on LeNet-5}, |
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author={El-Sawy, Ahmed and Hazem, EL-Bakry and Loey, Mohamed}, |
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booktitle={International conference on advanced intelligent systems and informatics}, |
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pages={566--575}, |
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year={2016}, |
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organization={Springer} |
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}""", |
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license="odbl" |
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) |
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def _split_generators(self, dl_manager): |
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urls = { |
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"train": "https://github.com/mloey/Arabic-Handwritten-Digits-Dataset/raw/master/Train%20Images.zip", |
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"test": "https://github.com/mloey/Arabic-Handwritten-Digits-Dataset/raw/master/Test%20Images.zip" |
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} |
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downloaded_files = dl_manager.download(urls) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"archive_path": downloaded_files["train"], "split": "train"}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"archive_path": downloaded_files["test"], "split": "test"}, |
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) |
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] |
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def _generate_examples(self, archive_path, split): |
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"""Generate examples from the ZIP archives of images and labels.""" |
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with ZipFile(archive_path, "r") as archive: |
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for entry in tqdm(archive.infolist(), desc=f"Processing {split} set"): |
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if entry.filename.endswith(".png"): |
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content = archive.read(entry) |
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image = Image.open(io.BytesIO(content)) |
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label = int(entry.filename.split("_")[-1][:-4]) |
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yield entry.filename, { |
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"image": image, |
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"label": label |
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} |
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