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import datasets |
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_CITATION = """\ |
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@article{Pattern Recognition, |
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Author = {bri A. Mahmoud, Irfan Ahmad, Wasfi G. Al-Khatib, Mohammad Alshayeb, Mohammad Tanvir Parvez, Volker Märgner, Gernot A. Fink}, |
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Title = { {KHATT: An Open Arabic Offline Handwritten Text Database} }, |
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Year = {2013}, |
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doi = {10.1016/j.patcog.2013.08.009}, |
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} |
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""" |
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_HOMEPAGE = "https://khatt.ideas2serve.net/KHATTAgreement.php" |
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_DESCRIPTION = """\ |
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KHATT (KFUPM Handwritten Arabic TexT) database is a database of unconstrained handwritten Arabic Text written by 1000 different writers. This research database’s development was undertaken by a research group from KFUPM, Dhahran, S audi Arabia headed by Professor Sabri Mahmoud in collaboration with Professor Fink from TU-Dortmund, Germany and Dr. Märgner from TU-Braunschweig, Germany. |
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""" |
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_DATA_URL = { |
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"train": [ |
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"https://huggingface.co/datasets/benhachem/KHATT/resolve/main/data/train.zip" |
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], |
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"validation": [ |
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"https://huggingface.co/datasets/benhachem/KHATT/resolve/main/data/validation.zip" |
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], |
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} |
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class KHATT(datasets.GeneratorBasedBuilder): |
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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=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"image": datasets.Image(), |
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"text": datasets.Value("string"), |
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} |
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), |
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homepage=_HOMEPAGE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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archives = dl_manager.download(_DATA_URL) |
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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={ |
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"archives": [dl_manager.iter_archive(archive) for archive in archives["train"]], |
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"split": "train", |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"archives": [dl_manager.iter_archive(archive) for archive in archives["validation"]], |
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"split": "validation", |
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}, |
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), |
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] |
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def _generate_examples(self, archives, split): |
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"""Yields examples.""" |
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idx = 0 |
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for archive in archives: |
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for path, file in archive: |
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if path.endswith(".tif"): |
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if split != "test": |
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img_file = file |
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else: |
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text = "" |
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elif path.endswith(".txt"): |
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text = file.read() |
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text = text.decode('utf-8') |
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ex = {"image": {"path": path, "bytes": img_file.read()}, "text": text} |
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yield idx, ex |
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idx += 1 |
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