vrptest2.py

# Builder script
# coding=utf-8
# 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.


#                    GNU GENERAL PUBLIC LICENSE
#                       Version 3, 29 June 2007
#
# Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
# Everyone is permitted to copy and distribute verbatim copies
# of this license document, but changing it is not allowed.
"""VRP2 dataset"""

import copy
import json
import os
import pandas as pd

import datasets
from datasets import load_dataset

_CITATION = """\
@article{vp2r2022jjk,
  title={xxxxx},
  author={test1},
  journal={arXiv preprint arXiv:2203.10981},
  year={2022}
}
"""
_DESCRIPTION = """\
yhello
"""

_LICENSE = "GNU General Public License v3.0"
_SPLITS = ["test"]

_URL = "https://huggingface.co/datasets/mujif/vrptest2/resolve/main/data/IQ" # todo


class ChartQA(datasets.GeneratorBasedBuilder):
    
    def _info(self):
        features = datasets.Features(
            {
                "imgname": datasets.Value("string"),
                "image": datasets.Image(),
                "question": datasets.Value("string"),
                "gt_answer": datasets.Value("string"),
            }
        )

        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            supervised_keys=None,
            license=_LICENSE,
        )

    def _split_generators(self, dl_manager):
        # downloaded_file = dl_manager.download_and_extract(_URL) + "/ChartQA Dataset"
        downloaded_file = dl_manager.download_and_extract(_URL) 

        
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "images_path": downloaded_file + "/test",
                    "img_anno_path": downloaded_file + "/test/result.jsonl",
                },
            ),
        ]

    def _generate_examples(self, img_anno_path:str  ,images_path: str):
        idx = 0
        with open(img_anno_path, "r", encoding="utf-8") as f:
            data = json.load(f)
            #returns the examples in the raw in json file
            for item in data:
                item = copy.deepcopy(item)
                item["image"] = os.path.join(images_path,item["file_name"])
                item["question"] = item["question"]
                item["gt_answer"] = item["gt_answer"]

                yield idx, item
                idx += 1