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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 = {anti-spoofing_Live}, |
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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. |
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15,000 attack replays from 4,000 unique devices. |
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""" |
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_NAME = 'anti-spoofing_Live' |
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_HOMEPAGE = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}" |
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_LICENSE = "" |
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_DATA = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}/resolve/main/data/" |
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class AntiSpoofingLive(datasets.GeneratorBasedBuilder): |
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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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'phone': datasets.Value('string'), |
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'selfie': datasets.Image(), |
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'video': datasets.Value('string'), |
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'worker_id': datasets.Value('string'), |
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'age': datasets.Value('int8'), |
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'country': datasets.Value('string'), |
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'gender': 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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) |
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def _split_generators(self, dl_manager): |
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data = dl_manager.download(f"{_DATA}data.tar.gz") |
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annotations = dl_manager.download(f"{_DATA}{_NAME}.csv") |
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data = dl_manager.iter_archive(data) |
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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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"data": data, |
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'annotations': annotations |
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}), |
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] |
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def _generate_examples(self, data, annotations): |
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annotations_df = pd.read_csv(annotations, sep=';') |
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for idx, (image_path, image) in enumerate(data): |
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if image_path.endswith('.jpg'): |
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yield idx, { |
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'phone': |
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annotations_df.loc[ |
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annotations_df['selfie_link'] == image_path] |
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['phone'].values[0], |
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'selfie': { |
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'path': image_path, |
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'bytes': image.read() |
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}, |
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'video': |
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annotations_df.loc[ |
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annotations_df['selfie_link'] == image_path] |
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['video_link'].values[0], |
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'worker_id': |
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annotations_df.loc[ |
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annotations_df['selfie_link'] == image_path] |
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['worker_id'].values[0], |
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'age': |
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annotations_df.loc[ |
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annotations_df['selfie_link'] == image_path] |
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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['selfie_link'] == image_path] |
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['country'].values[0], |
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'gender': |
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annotations_df.loc[ |
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annotations_df['selfie_link'] == image_path] |
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['gender'].values[0], |
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} |
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