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import datasets |
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import pandas as pd |
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_CITATION = """\ |
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@InProceedings{huggingface:dataset, |
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title = {MacBook-Attacks-Dataset}, |
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author = {TrainingDataPro}, |
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year = {2023} |
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} |
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""" |
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_DESCRIPTION = """\ |
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The dataset consists of videos of replay attacks played on different |
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models of MacBooks. The dataset solves tasks in the field of anti-spoofing and |
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it is useful for buisness and safety systems. |
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The dataset includes: **replay attacks** - videos of real people played on |
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a computer and filmed on the phone. |
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""" |
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_NAME = 'MacBook-Attacks-Dataset' |
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_HOMEPAGE = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}" |
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_LICENSE = "cc-by-nc-nd-4.0" |
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_DATA = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}/resolve/main/data/" |
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class MacBookAttacksDataset(datasets.GeneratorBasedBuilder): |
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def _info(self): |
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return datasets.DatasetInfo(description=_DESCRIPTION, |
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features=datasets.Features({ |
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'file': datasets.Value('string'), |
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'phone': datasets.Value('string'), |
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'computer': datasets.Value('string'), |
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'gender': datasets.Value('string'), |
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'age': datasets.Value('int16'), |
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'country': datasets.Value('string'), |
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}), |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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citation=_CITATION, |
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license=_LICENSE) |
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def _split_generators(self, dl_manager): |
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attacks = dl_manager.download(f"{_DATA}attacks.tar.gz") |
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annotations = dl_manager.download(f"{_DATA}{_NAME}.csv") |
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attacks = dl_manager.iter_archive(attacks) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"attacks": attacks, |
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'annotations': annotations |
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}), |
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] |
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def _generate_examples(self, attacks, annotations): |
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annotations_df = pd.read_csv(annotations, sep=';') |
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for idx, (video_path, video) in enumerate(attacks): |
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yield idx, { |
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'file': |
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video_path, |
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'phone': |
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annotations_df.loc[ |
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annotations_df['file'] == video_path.lower()] |
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['phone'].values[0], |
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'computer': |
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annotations_df.loc[ |
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annotations_df['file'] == video_path.lower()] |
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['computer'].values[0], |
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'gender': |
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annotations_df.loc[ |
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annotations_df['file'] == video_path.lower()] |
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['gender'].values[0], |
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'age': |
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annotations_df.loc[ |
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annotations_df['file'] == video_path.lower()] |
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['age'].values[0], |
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'country': |
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annotations_df.loc[ |
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annotations_df['file'] == video_path.lower()] |
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['country'].values[0] |
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} |
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