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vm_sound_classification

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vm_sound_classification
File size: 3,028 Bytes 
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#!/usr/bin/python3
# -*- coding: utf-8 -*-
from glob import glob
import os
from pathlib import Path

import datasets


_URLS = {
    "EarlyMedia-1": "data/wav_finished/EarlyMedia-1.zip",
    "EarlyMedia-55": "data/wav_finished/EarlyMedia-55.zip",
    "EarlyMedia-60": "data/wav_finished/EarlyMedia-60.zip",
    "EarlyMedia-62": "data/wav_finished/EarlyMedia-62.zip",
    "EarlyMedia-66": "data/wav_finished/EarlyMedia-66.zip",
    "en-IN": "data/wav_finished/en-IN.zip",
    "en-PH": "data/wav_finished/en-PH.zip",
    "en-SG": "data/wav_finished/en-SG.zip",
    "en-US": "data/wav_finished/en-US.zip",
    "es-MX": "data/wav_finished/es-MX.zip",
    "es-PE": "data/wav_finished/es-PE.zip",
    "id-ID": "data/wav_finished/id-ID.zip",
    "ja-JP": "data/wav_finished/ja-JP.zip",
    "ko-KR": "data/wav_finished/ko-KR.zip",
    "ms-MY": "data/wav_finished/ms-MY.zip",
    "pt-BR": "data/wav_finished/pt-BR.zip",
    "th-TH": "data/wav_finished/th-TH.zip",
    "zh-TW": "data/wav_finished/zh-TW.zip",

}


_CITATION = """\
@dataset{early_media,
  author       = {Xing Tian},
  title        = {vm_sound_classification},
  month        = aug,
  year         = 2024,
  publisher    = {Xing Tian},
  version      = {1.0},
}
"""


_DESCRIPTION = """\

"""


VERSION = datasets.Version("1.0.0")


class VMSoundClassification(datasets.GeneratorBasedBuilder):

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name=name, version=VERSION, description=name) for name in _URLS.keys()
    ]

    def _info(self):
        features = datasets.Features(
            {
                "country": datasets.Value("string"),
                "label": datasets.Value("string"),
                "path": datasets.Value("string"),
                "audio": datasets.Audio(sampling_rate=8000),
            }
        )

        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            supervised_keys=None,
            homepage="",
            license="",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        url = _URLS[self.config.name]
        dl_path = dl_manager.download_and_extract(url)
        archive_path = os.path.join(dl_path, self.config.name)

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={"archive_path": archive_path, "split": "train"},
            ),
        ]

    def _generate_examples(self, archive_path, split):
        """Yields examples."""
        archive_path = Path(archive_path)

        filename_list = archive_path.glob("*/*/*.wav")
        for idx, filename in enumerate(filename_list):

            label = filename.parts[-2]
            country = filename.parts[-4]

            yield idx, {
                "country": country,
                "label": label,
                "path": filename.as_posix(),
                "audio": filename.as_posix(),

            }


if __name__ == '__main__':
    pass