Delete fixtures_ocr.py
Browse files- fixtures_ocr.py +0 -78
fixtures_ocr.py
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# coding=utf-8
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# Copyright 2021 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
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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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import textwrap
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import datasets
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_CITATION = """\\n"""
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_DESCRIPTION = """\\n"""
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class FixturesOCRConfig(datasets.BuilderConfig):
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"""BuilderConfig for fixtures OCR"""
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def __init__(
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self,
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data_url,
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url,
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task_templates=None,
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**kwargs,
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):
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super(FixturesOCRConfig, self).__init__(
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version=datasets.Version("1.9.0", ""), **kwargs
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)
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self.data_url = data_url
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self.url = url
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self.task_templates = task_templates
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class FixturesOCR(datasets.GeneratorBasedBuilder):
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"""Fixtures for OCR models. Includes 2 images."""
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BUILDER_CONFIGS = [
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FixturesOCRConfig(
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name="image",
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description=textwrap.dedent(""),
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url="",
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data_url="",
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)
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]
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DEFAULT_CONFIG_NAME = "image"
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"id": datasets.Value("string"),
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"file": datasets.Value("string"),
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}
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),
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supervised_keys=("file",),
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homepage=self.config.url,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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DL_URLS = [
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f"https://huggingface.co/datasets/hf-internal-testing/fixtures_ocr/raw/main/{name}"
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for name in ["iam_picture.jpeg", "SROIE-receipt.jpeg"]
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]
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archive_path = dl_manager.download_and_extract(DL_URLS)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={"archive_path": archive_path},
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),
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]
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def _generate_examples(self, archive_path):
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"""Generate examples."""
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for i, filename in enumerate(archive_path):
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key = str(i)
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example = {
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"id": key,
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"file": filename,
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}
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yield key, example
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