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from pathlib import Path
import datasets
import pandas as pd
_CITATION = """\
@misc{,
author = "",
title = "",
url = "",
publisher = "",
year = ""
}
"""
_DESCRIPTION = """\
The BanglaBeats dataset comprises 16,170 3-second audio tracks extracted from 1,617 distinct Bengali songs, spanning genres such as adhunik, folk, hiphop, islamic, indie, metal, pop, and rock.
"""
_HOMEPAGE = ""
# TODO: Add the licence for the dataset here if you can find it
_LICENSE = ""
_URL = ""
GENRES = ["Adhunik", "Folk", "Hiphop", "Indie", "Islamic", "Metal", "Pop", "Rock"]
CORRUPTED_FILES = ["abcd.wav"]
class BanglaBeats(datasets.GeneratorBasedBuilder):
"""The BanglaBeats dataset"""
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"file": datasets.Value("string"),
"audio": datasets.Audio(sampling_rate=22_050),
"genre": datasets.ClassLabel(names=GENRES),
}
),
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
local_extracted_archive = dl_manager.download_and_extract("data/data.zip")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"local_extracted_archive": local_extracted_archive,
},
)
]
def _generate_examples(self, local_extracted_archive):
paths = list(Path(local_extracted_archive).glob("**/*.wav"))
paths = [p for p in paths if "._" not in p.name]
data = []
for path in paths:
label = str(path).split("/")[-2]
name = str(path).split("/")[-1]
if name in CORRUPTED_FILES:
continue
data.append({"file": str(path), "genre": label})
df = pd.DataFrame(data)
df.sort_values("file", inplace=True)
for idx_, row in df.iterrows():
yield idx_, {"file": row["file"], "audio": row["file"], "genre": row["genre"]} |