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"""IRMAS dataset."""
import os
import re
import textwrap
import datasets
import itertools
import typing as tp
from pathlib import Path
SAMPLE_RATE = 44_100
_IRMAS_TRAIN_SET_URL = 'https://zenodo.org/record/1290750/files/IRMAS-TrainingData.zip'
_IRMAS_TEST_SET_PART1_URL = 'https://zenodo.org/record/1290750/files/IRMAS-TestingData-Part1.zip'
_IRMAS_TEST_SET_PART2_URL = 'https://zenodo.org/record/1290750/files/IRMAS-TestingData-Part2.zip'
_IRMAS_TEST_SET_PART3_URL = 'https://zenodo.org/record/1290750/files/IRMAS-TestingData-Part3.zip'
INSTRUMENTS = [
'cel', 'cla', 'flu', 'gac', 'gel', 'org', 'pia', 'sax', 'tru', 'vio', 'voi'
]
class IRMASConfig(datasets.BuilderConfig):
"""BuilderConfig for IRMAS."""
def __init__(self, features, **kwargs):
super(IRMASConfig, self).__init__(version=datasets.Version("0.0.1", ""), **kwargs)
self.features = features
class IRMAS(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
IRMASConfig(
features=datasets.Features(
{
"file": datasets.Value("string"),
"audio": datasets.Audio(sampling_rate=SAMPLE_RATE),
"instrument": datasets.Sequence(datasets.Value("string")),
"label": datasets.Sequence(datasets.ClassLabel(names=INSTRUMENTS)),
}
),
name="irmas",
description=textwrap.dedent(
"""\
IRMAS is intended to be used for training and testing methods for the automatic recognition of predominant instruments in musical audio.
The instruments considered are: cello, clarinet, flute, acoustic guitar, electric guitar, organ, piano, saxophone, trumpet, violin, and human singing voice.
"""
),
),
]
def _info(self):
return datasets.DatasetInfo(
description="",
features=self.config.features,
supervised_keys=None,
homepage="https://zenodo.org/records/1290750",
citation="""
@inproceedings{bosch2012comparison,
title={A Comparison of Sound Segregation Techniques for Predominant Instrument Recognition in Musical Audio Signals.},
author={Bosch, Juan J and Janer, Jordi and Fuhrmann, Ferdinand and Herrera, Perfecto},
booktitle={ISMIR},
pages={559--564},
year={2012}
}
""",
task_templates=None,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
train_archive_path = dl_manager.download_and_extract(_IRMAS_TRAIN_SET_URL)
test_archive_part1_path = dl_manager.download_and_extract(_IRMAS_TEST_SET_PART1_URL)
test_archive_part2_path = dl_manager.download_and_extract(_IRMAS_TEST_SET_PART2_URL)
test_archive_part3_path = dl_manager.download_and_extract(_IRMAS_TEST_SET_PART3_URL)
extensions = ['.wav']
_, _train_walker = fast_scandir(train_archive_path, extensions, recursive=True)
_test_walker = []
for part in [test_archive_part1_path, test_archive_part2_path, test_archive_part3_path]:
_, _walker = fast_scandir(part, extensions, recursive=True)
_test_walker.extend(_walker)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN, gen_kwargs={"audio_filepaths": _train_walker, "split": "train"}
),
datasets.SplitGenerator(
name=datasets.Split.TEST, gen_kwargs={"audio_filepaths": _test_walker, "split": "test"}
),
]
def _generate_examples(self, audio_filepaths, split=None):
def extract_bracketed_items(filename):
# Regex pattern to find text inside square brackets
pattern = r'\[([^\]]+)\]'
# Find all occurrences of the pattern
items = re.findall(pattern, filename)
return items
def deduplicate(lst):
return list(dict.fromkeys(lst))
if split == 'train':
for guid, audio_path in enumerate(audio_filepaths):
labels = extract_bracketed_items(audio_path)
labels = deduplicate(labels)
labels = [label for label in labels if label in INSTRUMENTS]
yield guid, {
"id": str(guid),
"file": audio_path,
"audio": audio_path,
"instrument": labels,
"label": labels
}
elif split == 'test':
for guid, audio_path in enumerate(audio_filepaths):
labels = []
with open(audio_path.replace('.wav', '.txt'), 'r') as f:
for line in f:
labels.append(line.strip())
labels = deduplicate(labels)
yield guid, {
"id": str(guid),
"file": audio_path,
"audio": audio_path,
"instrument": labels,
"label": labels
}
def fast_scandir(path: str, exts: tp.List[str], recursive: bool = False):
# Scan files recursively faster than glob
# From github.com/drscotthawley/aeiou/blob/main/aeiou/core.py
subfolders, files = [], []
try: # hope to avoid 'permission denied' by this try
for f in os.scandir(path):
try: # 'hope to avoid too many levels of symbolic links' error
if f.is_dir():
subfolders.append(f.path)
elif f.is_file():
if os.path.splitext(f.name)[1].lower() in exts:
files.append(f.path)
except Exception:
pass
except Exception:
pass
if recursive:
for path in list(subfolders):
sf, f = fast_scandir(path, exts, recursive=recursive)
subfolders.extend(sf)
files.extend(f) # type: ignore
return subfolders, files |