"""TinySOL Dataset Loader.
.. admonition:: Dataset Info
:class: dropdown
TinySOL is a dataset of 2913 samples, each containing a single musical note from one of 14
different instruments:
- Bass Tuba
- French Horn
- Trombone
- Trumpet in C
- Accordion
- Contrabass
- Violin
- Viola
- Violoncello
- Bassoon
- Clarinet in B-flat
- Flute
- Oboe
- Alto Saxophone
These sounds were originally recorded at Ircam in Paris (France) between 1996
and 1999, as part of a larger project named Studio On Line (SOL). Although SOL
contains many combinations of mutes and extended playing techniques, TinySOL
purely consists of sounds played in the so-called "ordinary" style, and in
absence of mute.
TinySOL can be used for education and research purposes. In particular, it can
be employed as a dataset for training and/or evaluating music information
retrieval (MIR) systems, for tasks such as instrument recognition or
fundamental frequency estimation. For this purpose, we provide an official 5-fold
split of TinySOL as a metadata attribute. This split has been carefully balanced
in terms of instrumentation, pitch range, and dynamics. For the sake of research
reproducibility, we encourage users of TinySOL to adopt this split and report
their results in terms of average performance across folds.
We encourage TinySOL users to subscribe to the Ircam Forum so that they can
have access to larger versions of SOL.
For more details, please visit: https://www.orch-idea.org/
"""
import csv
import os
from typing import BinaryIO, Optional, Tuple
from deprecated.sphinx import deprecated
import librosa
import numpy as np
from smart_open import open
from mirdata import core, download_utils, io, jams_utils
BIBTEX = """@inproceedings{cella2020preprint,
author={Cella, Carmine Emanuele and Ghisi, Daniele and Lostanlen, Vincent and
Lévy, Fabien and Fineberg, Joshua and Maresz, Yan},
title={{OrchideaSOL}: {A} dataset of extended
instrumental techniques for computer-aided orchestration},
bootktitle={Under review},
year={2020}
}"""
INDEXES = {
"default": "6.0",
"test": "6.0",
"6.0": core.Index(filename="tinysol_index_6.0.json"),
}
REMOTES = {
"audio": download_utils.RemoteFileMetadata(
filename="TinySOL.tar.gz",
url="https://zenodo.org/record/3685367/files/TinySOL.tar.gz?download=1",
checksum="36030a7fe389da86c3419e5ee48e3b7f",
destination_dir="audio",
),
"annotations": download_utils.RemoteFileMetadata(
filename="TinySOL_metadata.csv",
url="https://zenodo.org/record/3685367/files/TinySOL_metadata.csv?download=1",
checksum="a86c9bb115f69e61f2f25872e397fc4a",
destination_dir="annotation",
),
}
STRING_ROMAN_NUMERALS = {1: "I", 2: "II", 3: "III", 4: "IV"}
LICENSE_INFO = "Creative Commons Attribution 4.0 International Public License."
[docs]
class Track(core.Track):
"""tinysol Track class
Args:
track_id (str): track id of the track
Attributes:
audio_path (str): path of the audio file
dynamics (str): dynamics abbreviation. Ex: pp, mf, ff, etc.
dynamics_id (int): pp=0, p=1, mf=2, f=3, ff=4
family (str): instrument family encoded by its English name
instance_id (int): instance ID. Either equal to 0, 1, 2, or 3.
instrument_abbr (str): instrument abbreviation
instrument_full (str): instrument encoded by its English name
is_resampled (bool): True if this sample was pitch-shifted from a neighbor; False if it was genuinely recorded.
pitch (str): string containing English pitch class and octave number
pitch_id (int): MIDI note index, where middle C ("C4") corresponds to 60
string_id (NoneType): string ID. By musical convention, the first
string is the highest. On wind instruments, this is replaced by `None`.
technique_abbr (str): playing technique abbreviation
technique_full (str): playing technique encoded by its English name
track_id (str): track id
"""
def __init__(self, track_id, data_home, dataset_name, index, metadata):
super().__init__(track_id, data_home, dataset_name, index, metadata)
self.audio_path = self.get_path("audio")
@property
def split(self):
return self._track_metadata.get("Fold")
@property
def family(self):
return self._track_metadata.get("Family")
@property
def instrument_abbr(self):
return self._track_metadata.get("Instrument (abbr.)")
@property
def instrument_full(self):
return self._track_metadata.get("Instrument (in full)")
@property
def technique_abbr(self):
return self._track_metadata.get("Technique (abbr.)")
@property
def technique_full(self):
return self._track_metadata.get("Technique (in full)")
@property
def pitch(self):
return self._track_metadata.get("Pitch")
@property
def pitch_id(self):
return self._track_metadata.get("Pitch ID")
@property
def dynamics(self):
return self._track_metadata.get("Dynamics")
@property
def dynamics_id(self):
return self._track_metadata.get("Dynamics ID")
@property
def instance_id(self):
return self._track_metadata.get("Instance ID")
@property
def string_id(self):
return self._track_metadata.get("String ID")
@property
def is_resampled(self):
return self._track_metadata.get("Resampled")
@property
def audio(self) -> Optional[Tuple[np.ndarray, float]]:
"""The track's audio
Returns:
* np.ndarray - audio signal
* float - sample rate
"""
return load_audio(self.audio_path)
[docs]
def to_jams(self):
"""Get the track's data in jams format
Returns:
jams.JAMS: the track's data in jams format
"""
return jams_utils.jams_converter(
audio_path=self.audio_path, metadata=self._track_metadata
)
[docs]
@io.coerce_to_bytes_io
def load_audio(fhandle: BinaryIO) -> Tuple[np.ndarray, float]:
"""Load a TinySOL audio file.
Args:
fhandle (str or file-like): File-like object or path to audio file
Returns:
* np.ndarray - the mono audio signal
* float - The sample rate of the audio file
"""
return librosa.load(fhandle, sr=None, mono=True)
[docs]
@core.docstring_inherit(core.Dataset)
class Dataset(core.Dataset):
"""
The tinysol dataset
"""
def __init__(self, data_home=None, version="default"):
super().__init__(
data_home,
version,
name="tinysol",
track_class=Track,
bibtex=BIBTEX,
indexes=INDEXES,
remotes=REMOTES,
license_info=LICENSE_INFO,
)
@core.cached_property
def _metadata(self):
metadata_path = os.path.join(
self.data_home, "annotation", "TinySOL_metadata.csv"
)
metadata_index = {}
try:
with open(metadata_path, "r") as fhandle:
csv_reader = csv.reader(fhandle, delimiter=",")
next(csv_reader)
for row in csv_reader:
key = os.path.splitext(os.path.split(row[0])[1])[0]
metadata_index[key] = {
"Fold": int(row[1]),
"Family": row[2],
"Instrument (abbr.)": row[3],
"Instrument (in full)": row[4],
"Technique (abbr.)": row[5],
"Technique (in full)": row[6],
"Pitch": row[7],
"Pitch ID": int(row[8]),
"Dynamics": row[9],
"Dynamics ID": int(row[10]),
"Instance ID": int(row[11]),
"Resampled": (row[13] == "TRUE"),
}
if len(row[12]) > 0:
metadata_index[key]["String ID"] = int(float(row[12]))
except FileNotFoundError:
raise FileNotFoundError("Metadata not found. Did you run .download()?")
return metadata_index
[docs]
@deprecated(reason="Use mirdata.datasets.tinysol.load_audio", version="0.3.4")
def load_audio(self, *args, **kwargs):
return load_audio(*args, **kwargs)