Datasets:

shpotes
/

waxal-wolof

License:

Dataset card Files Files and versions Community

waxal-wolof / waxal-wolof.py

Santiago

Add some minimal documentation

d7fbc3f over 1 year ago

raw history blame contribute delete

No virus

6.03 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.
	"""Waxal Wolof Dataset."""


	import csv
	import os

	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 a link to an official homepage for the dataset here
	_HOMEPAGE = ""

	_LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)"

	_MODALITIES_COMBINATION = [
	["audio", "image", "text"],
	["audio", "text"],
	["audio", "image"],
	["image", "text"],
	["audio"],
	["image"],
	["text"],
	]

	_URLs = {
	"train-transcriptions": "train_transcriptions.csv",
	"test-transcriptions": "test_transcriptions.csv",
	"image-files": "images.tar.gz",
	"captioned-images": "captioned_images.tar.gz",
	"audio-files": "audios.tar.gz",
	"transcribed-audio": "transcribed_audio.tar.gz"
	}


	class WaxalConfig(datasets.BuilderConfig):
	"""BuilderConfig for Waxal dataset."""

	def __init__(self, name, version, modalities, **kwargs):
	self.modalities = modalities
	self.language = kwargs.pop("language", None)

	modalities_str = " to ".join(self.modalities)
	description = f"Waxal {modalities_str} in {self.language}"

	super(WaxalConfig, self).__init__(
	name=name,
	version=version,
	description=description,
	**kwargs,
	)


	class WaxalWolof(datasets.GeneratorBasedBuilder):
	BUILDER_CONFIGS = [
	WaxalConfig(
	name="-".join(modalities),
	version=datasets.Version("1.1.0"),
	modalities=modalities,
	language="wolof",
	)
	for modalities in _MODALITIES_COMBINATION
	]

	DEFAULT_CONFIG_NAME = "audio-text"

	def _info(self):
	features = {}

	if "audio" in self.config.modalities:
	features["audio"] = datasets.features.Audio()
	features["audio_duration"] = datasets.Value("float")
	features["participant"] = datasets.Value("int32")

	if "image" in self.config.modalities:
	features["image"] = datasets.features.Image()

	if "text" in self.config.modalities:
	features["text_annotation"] = datasets.Value("string")

	return datasets.DatasetInfo(
	description=self.config.description,
	features=datasets.Features(features),
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	@property
	def with_audio(self):
	return "audio" in self.config.modalities

	@property
	def with_image(self):
	return "image" in self.config.modalities

	@property
	def with_text(self):
	return "text" in self.config.modalities

	def _split_generators(self, dl_manager):
	audio_url_key = "transcribed-audio" if self.with_text else "audio-files"
	image_url_key = "captioned-images" if self.with_text else "image-files"

	audio_files = (
	dl_manager.download_and_extract(_URLs[audio_url_key])
	if self.with_audio
	else None
	)

	image_files = (
	dl_manager.download_and_extract(_URLs[image_url_key])
	if self.with_image
	else None
	)

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"metadata_path": dl_manager.download(
	_URLs["train-transcriptions"]
	),
	"audio_files": audio_files,
	"image_files": image_files,
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"metadata_path": dl_manager.download(
	_URLs["test-transcriptions"]
	),
	"audio_files": audio_files,
	"image_files": image_files,
	},
	),
	]

	def _generate_examples(
	self,
	metadata_path,
	audio_files=None,
	path_to_audio="transcribed_audio",
	image_files=None,
	path_to_images="captioned_images",
	):
	metadata = {}

	with open(metadata_path) as buf:
	reader = csv.DictReader(buf)
	for row in reader:
	del row["prompt"] # TODO(shpotes): remove it in future versions!

	if self.with_text:
	if not row["transcription"]:
	continue

	if self.with_image:
	row["image_file_path"] = os.path.join(
	path_to_images, self.config.language, row["image_file_name"]
	)
	if self.with_audio:
	row["audio_file_path"] = os.path.join(
	path_to_audio, row["audio_file_name"]
	) # TODO(shpotes): add lang name to the csv path.

	metadata[row["idx"]] = row

	for idx, sample in metadata.items():
	result = {}

	if self.with_audio:
	result["participant"] = sample["participant"]
	result["audio_duration"] = sample["duration"]
	audio_path = os.path.join(audio_files, sample["audio_file_path"])
	with open(audio_path, "rb") as f:
	result["audio"] = {"path": audio_path, "bytes": f.read()}

	if self.with_image:
	image_path = os.path.join(image_files, sample["image_file_path"])
	with open(image_path, "rb") as f:
	result["image"] = {"path": image_path, "bytes": f.read()}

	if self.with_text:
	result["text_annotation"] = sample["transcription"]

	yield idx, result