"""MedleyDB melody Dataset Loader
.. admonition:: Dataset Info
:class: dropdown
MedleyDB melody is a subset of the MedleyDB dataset containing only
the mixtures and melody annotations.
MedleyDB is a dataset of annotated, royalty-free multitrack recordings.
MedleyDB was curated primarily to support research on melody extraction,
addressing important shortcomings of existing collections. For each song
we provide melody f0 annotations as well as instrument activations for
evaluating automatic instrument recognition.
For more details, please visit: https://medleydb.weebly.com
"""
import csv
import json
import os
from typing import BinaryIO, Optional, TextIO, Tuple
from deprecated.sphinx import deprecated
import librosa
import numpy as np
from smart_open import open
from mirdata import annotations, core, io, jams_utils
BIBTEX = """@inproceedings{bittner2014medleydb,
Author = {Bittner, Rachel M and Salamon, Justin and Tierney, Mike and Mauch, Matthias and Cannam, Chris and Bello, Juan P},
Booktitle = {International Society of Music Information Retrieval (ISMIR)},
Month = {October},
Title = {Medley{DB}: A Multitrack Dataset for Annotation-Intensive {MIR} Research},
Year = {2014}
}"""
INDEXES = {
"default": "5.0",
"test": "5.0",
"5.0": core.Index(filename="medleydb_melody_index_5.0.json"),
}
DOWNLOAD_INFO = """
To download this dataset, visit:
https://zenodo.org/record/2628782#.XKZdABNKh24
and request access.
Once downloaded, unzip the file MedleyDB-Melody.zip
and copy the result to:
{}
"""
LICENSE_INFO = (
"Creative Commons Attribution Non-Commercial Share-Alike 4.0 (CC BY-NC-SA 4.0)."
)
[docs]
class Track(core.Track):
"""medleydb_melody Track class
Args:
track_id (str): track id of the track
Attributes:
artist (str): artist
audio_path (str): path to the audio file
genre (str): genre
is_excerpt (bool): True if the track is an excerpt
is_instrumental (bool): True of the track does not contain vocals
melody1_path (str): path to the melody1 annotation file
melody2_path (str): path to the melody2 annotation file
melody3_path (str): path to the melody3 annotation file
n_sources (int): Number of instruments in the track
title (str): title
track_id (str): track id
Cached Properties:
melody1 (F0Data): the pitch of the single most predominant source (often the voice)
melody2 (F0Data): the pitch of the predominant source for each point in time
melody3 (MultiF0Data): the pitch of any melodic source. Allows for more than one f0 value at a time
"""
def __init__(self, track_id, data_home, dataset_name, index, metadata):
super().__init__(track_id, data_home, dataset_name, index, metadata)
self.melody1_path = self.get_path("melody1")
self.melody2_path = self.get_path("melody2")
self.melody3_path = self.get_path("melody3")
self.audio_path = self.get_path("audio")
@property
def artist(self):
return self._track_metadata.get("artist")
@property
def title(self):
return self._track_metadata.get("title")
@property
def genre(self):
return self._track_metadata.get("genre")
@property
def is_excerpt(self):
return self._track_metadata.get("is_excerpt")
@property
def is_instrumental(self):
return self._track_metadata.get("is_instrumental")
@property
def n_sources(self):
return self._track_metadata.get("n_sources")
@core.cached_property
def melody1(self) -> Optional[annotations.F0Data]:
return load_melody(self.melody1_path)
@core.cached_property
def melody2(self) -> Optional[annotations.F0Data]:
return load_melody(self.melody2_path)
@core.cached_property
def melody3(self) -> Optional[annotations.MultiF0Data]:
return load_melody3(self.melody3_path)
@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
"""
# jams does not support multiF0, so we skip melody3
return jams_utils.jams_converter(
audio_path=self.audio_path,
f0_data=[(self.melody1, "melody1"), (self.melody2, "melody2")],
metadata=self._track_metadata,
)
[docs]
@io.coerce_to_bytes_io
def load_audio(fhandle: BinaryIO) -> Tuple[np.ndarray, float]:
"""Load a MedleyDB 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]
@io.coerce_to_string_io
def load_melody(fhandle: TextIO) -> annotations.F0Data:
"""Load a MedleyDB melody1 or melody2 annotation file
Args:
fhandle (str or file-like): File-like object or path to a melody annotation file
Raises:
IOError: if melody_path does not exist
Returns:
F0Data: melody data
"""
times = []
freqs = []
voicing = []
reader = csv.reader(fhandle, delimiter=",")
for line in reader:
times.append(float(line[0]))
freq_val = float(line[1])
freqs.append(freq_val)
voicing.append(float(freq_val > 0))
times = np.array(times) # type: ignore
freqs = np.array(freqs) # type: ignore
voicing = np.array(voicing) # type: ignore
return annotations.F0Data(times, "s", freqs, "hz", voicing, "binary")
[docs]
@io.coerce_to_string_io
def load_melody3(fhandle: TextIO) -> annotations.MultiF0Data:
"""Load a MedleyDB melody3 annotation file
Args:
fhandle (str or file-like): File-like object or melody 3 melody annotation path
Raises:
IOError: if melody_path does not exist
Returns:
MultiF0Data: melody 3 annotation data
"""
times = []
freqs_list = []
conf_list = []
reader = csv.reader(fhandle, delimiter=",")
for line in reader:
times.append(float(line[0]))
freqs_list.append([float(v) for v in line[1:] if float(v) != 0])
conf_list.append([1.0 for v in line[1:] if float(v) != 0])
times = np.array(times) # type: ignore
melody_data = annotations.MultiF0Data(
times, "s", freqs_list, "hz", conf_list, "binary"
)
return melody_data
[docs]
@core.docstring_inherit(core.Dataset)
class Dataset(core.Dataset):
"""
The medleydb_melody dataset
"""
def __init__(self, data_home=None, version="default"):
super().__init__(
data_home,
version,
name="medleydb_melody",
track_class=Track,
bibtex=BIBTEX,
indexes=INDEXES,
download_info=DOWNLOAD_INFO,
license_info=LICENSE_INFO,
)
@core.cached_property
def _metadata(self):
metadata_path = os.path.join(self.data_home, "medleydb_melody_metadata.json")
try:
with open(metadata_path, "r") as fhandle:
metadata = json.load(fhandle)
except FileNotFoundError:
raise FileNotFoundError("Metadata not found. Did you run .download()?")
return metadata
[docs]
@deprecated(
reason="Use mirdata.datasets.medleydb_melody.load_audio", version="0.3.4"
)
def load_audio(self, *args, **kwargs):
return load_audio(*args, **kwargs)
[docs]
@deprecated(
reason="Use mirdata.datasets.medleydb_melody.load_melody", version="0.3.4"
)
def load_melody(self, *args, **kwargs):
return load_melody(*args, **kwargs)
[docs]
@deprecated(
reason="Use mirdata.datasets.medleydb_melody.load_melody3", version="0.3.4"
)
def load_melody3(self, *args, **kwargs):
return load_melody3(*args, **kwargs)