fixtures-captioning / fixtures-captioning.py
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Update fixtures-captioning.py
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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 FixturesCaptioningConfig(datasets.BuilderConfig):
"""BuilderConfig for fixtures captioning"""
def __init__(
self,
data_url,
url,
task_templates=None,
**kwargs,
):
super(FixturesCaptioningConfig, self).__init__(
version=datasets.Version("1.9.0", ""), **kwargs
)
self.data_url = data_url
self.url = url
self.task_templates = task_templates
class FixturesCaptioning(datasets.GeneratorBasedBuilder):
"""Fixtures for captioning and VQA models. Includes 4 images."""
BUILDER_CONFIGS = [
FixturesCaptioningConfig(
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-captioning/raw/main/{name}"
for name in ["bbox_sample_image.jpeg", "bus.png", "chart.png", "skateboard.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