File size: 3,215 Bytes
15ca8b0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 |
import datasets
import pandas as pd
_CITATION = """\
@InProceedings{huggingface:dataset,
title = {low_quality_webcam_video_attacks},
author = {TrainingDataPro},
year = {2023}
}
"""
_DESCRIPTION = """\
The dataset includes live-recorded Anti-Spoofing videos from around the world,
captured via low-quality webcams with resolutions like QVGA, QQVGA and QCIF.
"""
_NAME = 'low_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 LowQualityWebcamVideoAttacks(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]
}
|