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fixtures_ade20k

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fixtures_ade20k / fixtures_ade20k.py

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nielsr HF staff

Add image and segmentation map

ddd1a5c over 2 years ago

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	# 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