# coding=utf-8 # Copyright 2021 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors. # # 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. import textwrap import datasets _CITATION = """\\n""" _DESCRIPTION = """\\n""" class FixturesAde20kConfig(datasets.BuilderConfig): """BuilderConfig for fixtures ADE20k""" def __init__( self, data_url, url, task_templates=None, **kwargs, ): super(FixturesAde20kConfig, self).__init__( version=datasets.Version("1.9.0", ""), **kwargs ) self.data_url = data_url self.url = url self.task_templates = task_templates class FixturesAde20k(datasets.GeneratorBasedBuilder): """Fixtures of the Ade20k dataset. Includes 1 image and its corresponding segmentation map.""" BUILDER_CONFIGS = [ FixturesAde20kConfig( name="image", description=textwrap.dedent(""), url="", data_url="", ) ] DEFAULT_CONFIG_NAME = "image" def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "id": datasets.Value("string"), "file": datasets.Value("string"), } ), supervised_keys=("file",), homepage=self.config.url, citation=_CITATION, ) def _split_generators(self, dl_manager): DL_URLS = [ f"https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/raw/main/{name}" for name in ["ADE_val_00000001.jpg", "ADE_val_00000001.png", "ADE_val_00000002.jpg", "ADE_val_00000002.png"] ] archive_path = dl_manager.download_and_extract(DL_URLS) return [ datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={"archive_path": archive_path}, ), ] def _generate_examples(self, archive_path): """Generate examples.""" for i, filename in enumerate(archive_path): key = str(i) example = { "id": key, "file": filename, } yield key, example