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from itertools import count
import datasets
import pandas as pd
_CITATION = """\
@InProceedings{huggingface:dataset,
title = {presentation-attack-detection-2d-dataset},
author = {TrainingDataPro},
year = {2023}
}
"""
_DESCRIPTION = """\
The dataset consists of photos of individuals and videos of him/her wearing printed 2D
mask with cut-out holes for eyes. Videos are filmed in different lightning conditions
and in different places (*indoors, outdoors*), a person moves his/her head left, right,
up and down. Each video in the dataset has an approximate duration of 15-17 seconds.
"""
_NAME = "presentation-attack-detection-2d-dataset"
_HOMEPAGE = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}"
_LICENSE = ""
_DATA = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}/resolve/main/data/"
class PresentationAttackDetection2dDataset(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"photo": datasets.Image(),
"video": datasets.Value("string"),
"worker_id": datasets.Value("string"),
"set_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):
attacks = dl_manager.download(f"{_DATA}attacks.tar.gz")
annotations = dl_manager.download(f"{_DATA}{_NAME}.csv")
attacks = dl_manager.iter_archive(attacks)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"attacks": attacks, "annotations": annotations},
),
]
def _generate_examples(self, attacks, annotations):
annotations_df = pd.read_csv(annotations, sep=",")
for idx, (image_path, image) in enumerate(attacks):
if image_path.endswith("jpg"):
yield idx, {
"photo": {"path": image_path, "bytes": image.read()},
"video": annotations_df.loc[
annotations_df["image"] == image_path
]["video"].values[0],
"worker_id": annotations_df.loc[
annotations_df["image"] == image_path
]["worker_id"].values[0],
"set_id": annotations_df.loc[
annotations_df["image"] == image_path
]["set_id"].values[0],
"age": annotations_df.loc[
annotations_df["image"] == image_path
]["age"].values[0],
"country": annotations_df.loc[
annotations_df["image"] == image_path
]["country"].values[0],
"gender": annotations_df.loc[
annotations_df["image"] == image_path
]["gender"].values[0],
}
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