encyclopedia_britannica.py

# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""TODO"""

import os
import pandas as pd
import datasets
from PIL import Image

# TODO: Add BibTeX citation
# Find for instance the citation on arxiv or on the dataset repo/website
_CITATION = """TODO"""


_DESCRIPTION = """\
TODO"""

_HOMEPAGE = "TODO"

_LICENSE = "Public Domain"


class EncyclopaediaBritannica(datasets.GeneratorBasedBuilder):
    """TODO: Short description of my dataset."""

    VERSION = datasets.Version("1.1.0")

    def _info(self):

        features = datasets.Features(
            {
                "metadata": datasets.Value("string"),
                "image": datasets.Value("string"),
                "label": datasets.ClassLabel(names=["text-only", "illustrated"]),
            }
        )

        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        csv = dl_manager.download("annotations.csv")
        df = pd.read_csv(csv, low_memory=False)
        df = df[df["choice"].notna()]
        df = df[["meta", "choice", "image"]]
        annotations = df.to_dict(orient="records")
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "annotations": annotations,
                },
            ),
        ]

    def _generate_examples(self,  annotations):
        for id_, row in enumerate(annotations):
            row["image"] = row.pop("image")
            row["metadata"] = row.pop("meta")
            row["label"] = row.pop("choice")
            yield id_, row