Vadzim Kashko commited on
Commit
97399d3
1 Parent(s): 064b95e

feat: script

Browse files
cut-2d-masks-presentation-attack-detection.py ADDED
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+ import datasets
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+ import pandas as pd
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+
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+ _CITATION = """\
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+ @InProceedings{huggingface:dataset,
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+ title = {2d-masks-presentation-attack-detection},
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+ author = {TrainingDataPro},
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+ year = {2023}
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+ }
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+ """
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+
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+ _DESCRIPTION = """\
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+ The dataset consists of videos of individuals wearing printed 2D masks or
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+ printed 2D masks with cut-out eyes and directly looking at the camera.
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+ Videos are filmed in different lightning conditions and in different places
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+ (indoors, outdoors). Each video in the dataset has an approximate duration of 2
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+ seconds.
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+ """
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+ _NAME = '2d-masks-presentation-attack-detection'
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+
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+ _HOMEPAGE = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}"
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+
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+ _LICENSE = ""
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+
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+ _DATA = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}/resolve/main/data/"
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+
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+
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+ class MasksPresentationAttackDetection(datasets.GeneratorBasedBuilder):
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+ """Small sample of image-text pairs"""
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+
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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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+ 'user': datasets.Value('string'),
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+ 'real_1': datasets.Value('string'),
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+ 'real_2': datasets.Value('string'),
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+ 'real_3': datasets.Value('string'),
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+ 'real_4': datasets.Value('string'),
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+ 'mask_1': datasets.Value('string'),
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+ 'mask_2': datasets.Value('string'),
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+ 'mask_3': datasets.Value('string'),
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+ 'mask_4': datasets.Value('string'),
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+ 'cut_1': datasets.Value('string'),
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+ 'cut_2': datasets.Value('string'),
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+ 'cut_3': datasets.Value('string'),
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+ 'cut_4': 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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+
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+ def _split_generators(self, dl_manager):
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+ files = dl_manager.download(f"{_DATA}files.tar.gz")
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+ annotations = dl_manager.download(f"{_DATA}{_NAME}.csv")
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+ files = dl_manager.iter_archive(files)
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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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+ "files": files,
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+ 'annotations': annotations
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+ }),
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+ ]
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+
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+ def _generate_examples(self, files, annotations):
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+ annotations_df = pd.read_csv(annotations, sep=';')
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+
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+ for idx, (file_path, file) in enumerate(files):
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+ if 'real_1' in file_path.lower():
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+ user = file_path.split('/')[-2]
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+ yield idx, {
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+ 'user':
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+ user,
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+ 'real_1':
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+ annotations_df.loc[annotations_df['user'] == user]
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+ ['real_1'].values[0],
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+ 'real_2':
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+ annotations_df.loc[annotations_df['user'] == user]
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+ ['real_2'].values[0],
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+ 'real_3':
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+ annotations_df.loc[annotations_df['user'] == user]
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+ ['real_3'].values[0],
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+ 'real_4':
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+ annotations_df.loc[annotations_df['user'] == user]
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+ ['real_4'].values[0],
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+ 'mask_1':
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+ annotations_df.loc[annotations_df['user'] == user]
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+ ['mask_1'].values[0],
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+ 'mask_2':
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+ annotations_df.loc[annotations_df['user'] == user]
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+ ['mask_2'].values[0],
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+ 'mask_3':
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+ annotations_df.loc[annotations_df['user'] == user]
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+ ['mask_3'].values[0],
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+ 'mask_4':
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+ annotations_df.loc[annotations_df['user'] == user]
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+ ['mask_4'].values[0],
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+ 'cut_1':
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+ annotations_df.loc[annotations_df['user'] == user]
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+ ['cut_1'].values[0],
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+ 'cut_2':
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+ annotations_df.loc[annotations_df['user'] == user]
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+ ['cut_2'].values[0],
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+ 'cut_3':
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+ annotations_df.loc[annotations_df['user'] == user]
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+ ['cut_3'].values[0],
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+ 'cut_4':
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+ annotations_df.loc[annotations_df['user'] == user]
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+ ['cut_4'].values[0],
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+ }