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import datasets |
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_CITATION = """\ |
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@InProceedings{huggingface:dataset, |
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title = {printed_photos_attacks}, |
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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 40,000 videos and selfies with unique people. 15,000 |
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attack replays from 4,000 unique devices. 10,000 attacks with A4 printouts and |
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10,000 attacks with cut-out printouts. |
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""" |
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_NAME = 'printed_photos_attacks' |
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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 PrintedPhotosAttacks(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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'attack': datasets.Value('string'), |
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'live_selfie': datasets.Image(), |
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'live_video': 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}attack.tar.gz") |
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live_selfies = dl_manager.download(f"{_DATA}live_selfie.tar.gz") |
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live_videos = dl_manager.download(f"{_DATA}live_video.tar.gz") |
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attacks = dl_manager.iter_archive(attacks) |
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live_selfies = dl_manager.iter_archive(live_selfies) |
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live_videos = dl_manager.iter_archive(live_videos) |
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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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"live_selfies": live_selfies, |
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'live_videos': live_videos |
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}), |
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] |
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def _generate_examples(self, attacks, live_selfies, live_videos): |
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for idx, ((attack_path, attack), (live_selfie_path, live_selfie), |
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(live_video_path, live_video)) in enumerate( |
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zip(attacks, live_selfies, live_videos)): |
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yield idx, { |
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'attack': attack_path, |
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'live_selfie': { |
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'path': live_selfie_path, |
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'bytes': live_selfie.read() |
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}, |
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'live_video': live_video_path |
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} |
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