presentation-attack-detection-2d-dataset.py

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],
                }