Datasets:
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Parent(s):
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upload dataset script
Browse files- brill_iconclass.py +77 -0
- dataset_infos.json +1 -0
brill_iconclass.py
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# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Brill Iconclass AI Test Set data."""
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import json
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import os
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from PIL import Image
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import datasets
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_CITATION = """\
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@MISC{iconclass,
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title = {Brill Iconclass AI Test Set},
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author={Etienne Posthumus},
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year={2020}
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}
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"""
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_DESCRIPTION = """\
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A dataset for applying machine learning to collections described with the Iconclass classification system.
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"""
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_HOMEPAGE = "https://labs.brill.com/ictestset/"
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_LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/"
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_URL = "https://labs.brill.com/ictestset/779ba2ca9e977c58d818e3823a676973.zip"
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class BrillIconclass(datasets.GeneratorBasedBuilder):
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"""Brill IconClass AI dataset"""
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VERSION = datasets.Version("1.1.0")
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def _info(self):
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features = datasets.Features(
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{
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"image": datasets.Image(),
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"label": [datasets.Value("string")]
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}
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)
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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data_dir = dl_manager.download_and_extract(_URL)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={"data_json": os.path.join(data_dir, "data.json"), "data_dir": data_dir},
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),
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]
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def _generate_examples(self, data_json, data_dir):
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with open(data_json, encoding="utf-8") as f:
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data = json.load(f)
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for row, item in enumerate(data.items()):
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filepath, labels = item
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image = Image.open(os.path.join(data_dir, filepath))
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yield row, {"image": image, "label": labels}
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dataset_infos.json
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{"default": {"description": "A dataset for applying machine learning to collections described with the Iconclass classification system.\n", "citation": "@MISC{iconclass,\ntitle = {Brill Iconclass AI Test Set},\nauthor={Etienne Posthumus},\nyear={2020}\n}\n", "homepage": "https://labs.brill.com/ictestset/", "license": "https://creativecommons.org/publicdomain/zero/1.0/", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "label": [{"dtype": "string", "id": null, "_type": "Value"}]}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "brill_iconclass", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 19925506, "num_examples": 87744, "dataset_name": "brill_iconclass"}}, "download_checksums": {"https://labs.brill.com/ictestset/779ba2ca9e977c58d818e3823a676973.zip": {"num_bytes": 3295276816, "checksum": "96403cd3fdd34c71e4fa97078435350c244c9023af022cc3b8c2500cc13c684a"}}, "download_size": 3295276816, "post_processing_size": null, "dataset_size": 19925506, "size_in_bytes": 3315202322}}
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