Datasets:

society-ethics
/

VIST

Dataset card Files Files and versions Community

VIST / VIST.py

NimaBoscarino

Update VIST.py

16fa1a3 over 1 year ago

raw history blame contribute delete

No virus

6.1 kB

	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# 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.
	# TODO: Address all TODOs and remove all explanatory comments
	"""TODO: Add a description here."""


	import json
	import os
	from huggingface_hub import hf_hub_download
	import datasets


	# TODO: Add BibTeX citation
	# Find for instance the citation on arxiv or on the dataset repo/website
	_CITATION = """\
	@InProceedings{huggingface:dataset,
	title = {A great new dataset},
	author={huggingface, Inc.
	},
	year={2020}
	}
	"""

	# TODO: Add description of the dataset here
	# You can copy an official description
	_DESCRIPTION = """\
	This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
	"""

	# TODO: Add a link to an official homepage for the dataset here
	_HOMEPAGE = "http://visionandlanguage.net/VIST/dataset.html"

	# TODO: Add the licence for the dataset here if you can find it
	_LICENSE = ""

	_DII_WORKER_IDS = hf_hub_download(repo_type="dataset", repo_id="society-ethics/VIST", filename="data/dii.worker_ids.csv", use_auth_token=True)

	_URLS = {
	"DII": {
	"train": "https://huggingface.co/datasets/NimaBoscarino/VIST/resolve/main/data/train.dii.jsonl.zip",
	"test": "https://huggingface.co/datasets/NimaBoscarino/VIST/resolve/main/data/test.dii.jsonl.zip",
	"val": "https://huggingface.co/datasets/NimaBoscarino/VIST/resolve/main/data/val.dii.jsonl.zip",
	},
	"SIS": "http://visionandlanguage.net/VIST/json_files/story-in-sequence/SIS-with-labels.tar.gz",
	}


	# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
	class VIST(datasets.GeneratorBasedBuilder):
	"""TODO: Short description of my dataset."""

	VERSION = datasets.Version("1.1.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(name="DII", version=VERSION, description=""),
	datasets.BuilderConfig(name="SIS", version=VERSION, description=""),
	]

	def _info(self):
	features = None
	if self.config.name == "DII":
	features = datasets.Features({
	'description': datasets.Value("string"),
	'title': datasets.Value("string"),
	'farm': datasets.ClassLabel(num_classes=10), # Actually 9, but datasets complains for some reason?
	'date_update': datasets.Value("timestamp[s]"),
	'primary': datasets.Value("int32"),
	'server': datasets.Value("int16"),
	'date_create': datasets.Value("timestamp[s]"),
	'photos': datasets.Value("int16"),
	'secret': datasets.Value("string"),
	'owner': datasets.Value("string"),
	'vist_label': datasets.Value("string"),
	'id': datasets.Value("int64"),
	"images": datasets.Sequence({
	'datetaken': datasets.Value("date64"),
	'license': datasets.ClassLabel(num_classes=7),
	'image_title': datasets.Value("string"),
	'longitude': datasets.Value("float64"),
	'url': datasets.Image(decode=False),
	'image_secret': datasets.Value("string"),
	'media': datasets.ClassLabel(num_classes=2, names=["photo", "video"]),
	'latitude': datasets.Value("float64"),
	'image_id': datasets.Value("int64"),
	'tags': [datasets.Value("string")],
	'image_farm': datasets.ClassLabel(names=["1", "2", "6", "7"]), # From exploring the data
	'image_server': datasets.Value("int16"),
	"annotations": datasets.Sequence({
	'original_text': datasets.Value("string"),
	'photo_order_in_story': datasets.Value("int8"),
	'worker_id': datasets.ClassLabel(names_file=_DII_WORKER_IDS),
	'text': datasets.Value("string"),
	})
	})
	})
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	urls = _URLS[self.config.name]
	data_dirs = dl_manager.download_and_extract(urls)

	for split in data_dirs:
	archive_path = data_dirs[split]
	if archive_path.endswith(".zip") or os.path.isdir(archive_path):
	data_dirs[split] = os.path.join(archive_path, os.listdir(archive_path)[0])

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": data_dirs["train"],
	"split": "train",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"filepath": data_dirs["val"],
	"split": "validation",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"filepath": data_dirs["test"],
	"split": "test"
	},
	),
	]

	def _generate_examples(self, filepath, split):
	with open(filepath, encoding="utf-8") as f:
	for key, row in enumerate(f):
	data = json.loads(row)
	yield key, data