| import datasets | |
| import pandas as pd | |
| _CITATION = """\ | |
| @InProceedings{huggingface:dataset, | |
| title = {high_quality_webcam_video_attacks}, | |
| author = {TrainingDataPro}, | |
| year = {2023} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| The dataset includes live-recorded Anti-Spoofing videos from around the world, | |
| captured via **high-quality** webcams with Full HD resolution and above. | |
| """ | |
| _NAME = 'high_quality_webcam_video_attacks' | |
| _HOMEPAGE = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}" | |
| _LICENSE = "cc-by-nc-nd-4.0" | |
| _DATA = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}/resolve/main/data/" | |
| class HighQualityWebcamVideoAttacks(datasets.GeneratorBasedBuilder): | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features({ | |
| 'video_file': datasets.Value('string'), | |
| 'assignment_id': datasets.Value('string'), | |
| 'worker_id': datasets.Value('string'), | |
| 'gender': datasets.Value('string'), | |
| 'age': datasets.Value('uint8'), | |
| 'country': datasets.Value('string'), | |
| 'resolution': datasets.Value('string') | |
| }), | |
| supervised_keys=None, | |
| homepage=_HOMEPAGE, | |
| citation=_CITATION, | |
| license=_LICENSE) | |
| def _split_generators(self, dl_manager): | |
| videos = dl_manager.download(f"{_DATA}videos.tar.gz") | |
| annotations = dl_manager.download(f"{_DATA}{_NAME}.csv") | |
| videos = dl_manager.iter_archive(videos) | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "videos": videos, | |
| 'annotations': annotations | |
| }), | |
| ] | |
| def _generate_examples(self, videos, annotations): | |
| annotations_df = pd.read_csv(annotations, sep=';') | |
| for idx, (image_path, video) in enumerate(videos): | |
| file_name = image_path.split('/')[-1] | |
| assignment_id = file_name.split('.')[0] | |
| yield idx, { | |
| "video_file": | |
| file_name, | |
| 'assignment_id': | |
| assignment_id, | |
| 'worker_id': | |
| annotations_df.loc[ | |
| annotations_df['assignment_id'] == assignment_id] | |
| ['worker_id'].values[0], | |
| 'gender': | |
| annotations_df.loc[ | |
| annotations_df['assignment_id'] == assignment_id] | |
| ['gender'].values[0], | |
| 'age': | |
| annotations_df.loc[ | |
| annotations_df['assignment_id'] == assignment_id] | |
| ['age'].values[0], | |
| 'country': | |
| annotations_df.loc[ | |
| annotations_df['assignment_id'] == assignment_id] | |
| ['country'].values[0], | |
| 'resolution': | |
| annotations_df.loc[ | |
| annotations_df['assignment_id'] == assignment_id] | |
| ['resolution'].values[0] | |
| } | |