| import datasets | |
| import pandas as pd | |
| _CITATION = """\ | |
| @InProceedings{huggingface:dataset, | |
| title = {anti-spoofing_Live}, | |
| author = {TrainingDataPro}, | |
| year = {2023} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| The dataset consists of 40,000 videos and selfies with unique people. | |
| 15,000 attack replays from 4,000 unique devices. | |
| """ | |
| _NAME = 'anti-spoofing_Live' | |
| _HOMEPAGE = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}" | |
| _LICENSE = "" | |
| _DATA = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}/resolve/main/data/" | |
| class AntiSpoofingLive(datasets.GeneratorBasedBuilder): | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features({ | |
| 'phone': datasets.Value('string'), | |
| 'selfie': datasets.Image(), | |
| 'video': datasets.Value('string'), | |
| 'worker_id': datasets.Value('string'), | |
| 'age': datasets.Value('int8'), | |
| 'country': datasets.Value('string'), | |
| 'gender': datasets.Value('string') | |
| }), | |
| supervised_keys=None, | |
| homepage=_HOMEPAGE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| data = dl_manager.download(f"{_DATA}data.tar.gz") | |
| annotations = dl_manager.download(f"{_DATA}{_NAME}.csv") | |
| data = dl_manager.iter_archive(data) | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "data": data, | |
| 'annotations': annotations | |
| }), | |
| ] | |
| def _generate_examples(self, data, annotations): | |
| annotations_df = pd.read_csv(annotations, sep=';') | |
| for idx, (image_path, image) in enumerate(data): | |
| if image_path.endswith('.jpg'): | |
| yield idx, { | |
| 'phone': | |
| annotations_df.loc[ | |
| annotations_df['selfie_link'] == image_path] | |
| ['phone'].values[0], | |
| 'selfie': { | |
| 'path': image_path, | |
| 'bytes': image.read() | |
| }, | |
| 'video': | |
| annotations_df.loc[ | |
| annotations_df['selfie_link'] == image_path] | |
| ['video_link'].values[0], | |
| 'worker_id': | |
| annotations_df.loc[ | |
| annotations_df['selfie_link'] == image_path] | |
| ['worker_id'].values[0], | |
| 'age': | |
| annotations_df.loc[ | |
| annotations_df['selfie_link'] == image_path] | |
| ['age'].values[0], | |
| 'country': | |
| annotations_df.loc[ | |
| annotations_df['selfie_link'] == image_path] | |
| ['country'].values[0], | |
| 'gender': | |
| annotations_df.loc[ | |
| annotations_df['selfie_link'] == image_path] | |
| ['gender'].values[0], | |
| } | |