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"""The dataset contains 13,955 imgaes of pills inside medication bottles, |
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which are from a top down view. They are labeled with 20 distinct National |
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Drug Code (NDC) and each image is associated with an image id. The dataset |
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is split into train, test, and validation sets. """ |
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import os |
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from typing import List |
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import datasets |
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_CITATION = """\ |
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@InProceedings{University of Michigan - Deep Blue Data, |
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title = {Images of pills inside medication bottles dataset}, |
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author={Lester, C. A., Al Kontar, R., Chen, Q.}, |
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year={2022} |
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} |
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""" |
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_DESCRIPTION = """\ |
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This dataset contains pills images inside medication bottles from a top down view, with National Drug Code (NDC) and image id. |
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""" |
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_HOMEPAGE = "https://deepblue.lib.umich.edu/data/concern/data_sets/6d56zw997?locale=en#items_display" |
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_LICENSE = "CC BY 4.0" |
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_URLS = { |
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"dataset": "https://deepblue.lib.umich.edu/data/downloads/rr171x63c", |
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} |
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class NewDataset(datasets.GeneratorBasedBuilder): |
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"""The dataset contains train, test, and validation data for pills images inside medication bottles""" |
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_URLS = _URLS |
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VERSION = datasets.Version("1.1.0") |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"image": datasets.Image(), |
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"id": datasets.Value("string"), |
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"ndc": datasets.Value("string") |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: |
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data_dir = dl_manager.download_and_extract(self._URLS["dataset"]) |
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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={"filepath": os.path.join(data_dir, "NLM20/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={"filepath": os.path.join(data_dir, "NLM20/test")}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={"filepath": os.path.join(data_dir, "NLM20/valid")}, |
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), |
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] |
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def _generate_examples(self, filepath): |
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for ndc in os.listdir(filepath): |
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ndc_path = os.path.join(filepath, ndc) |
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if os.path.isdir(ndc_path): |
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for image_file in os.listdir(ndc_path): |
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image_path = os.path.join(ndc_path, image_file) |
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image_id = os.path.splitext(image_file)[0] |
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yield image_id, { |
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"image": image_path, |
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"id": image_id, |
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"ndc": ndc, |
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} |
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