| 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] |
| } |
|
|
