Datasets:
Multilinguality:
other-iconclass-metadata
Size Categories:
10K<n<100K
Language Creators:
expert-generated
Annotations Creators:
expert-generated
License:
| # Copyright 2022 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. | |
| """Brill Iconclass AI Test Set data.""" | |
| import json | |
| import os | |
| from PIL import Image | |
| import datasets | |
| _CITATION = """\ | |
| @MISC{iconclass, | |
| title = {Brill Iconclass AI Test Set}, | |
| author={Etienne Posthumus}, | |
| year={2020} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| A dataset for applying machine learning to collections described with the Iconclass classification system. | |
| """ | |
| _HOMEPAGE = "https://iconclass.org/testset/" | |
| _LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/" | |
| _URL = "https://iconclass.org/testset/779ba2ca9e977c58d818e3823a676973.zip" | |
| class BrillIconclass(datasets.GeneratorBasedBuilder): | |
| """Brill IconClass AI dataset""" | |
| VERSION = datasets.Version("1.1.0") | |
| def _info(self): | |
| features = datasets.Features( | |
| { | |
| "image": datasets.Image(), | |
| "label": [datasets.Value("string")] | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| homepage=_HOMEPAGE, | |
| license=_LICENSE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| data_dir = dl_manager.download_and_extract(_URL) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={"data_json": os.path.join(data_dir, "data.json"), "data_dir": data_dir}, | |
| ), | |
| ] | |
| def _generate_examples(self, data_json, data_dir): | |
| with open(data_json, encoding="utf-8") as f: | |
| data = json.load(f) | |
| for row, item in enumerate(data.items()): | |
| filepath, labels = item | |
| yield row, {"image": os.path.join(data_dir, filepath), "label": labels} | |