Add fma keys dataset

This adds support for the FMA Keys dataset, which is a new dataset
for the evaluation of key detection containing 340 hours (5489 songs)
of song-level key and mode annotations, spread across 17 genres.

Author: stellaywong

mirdata/datasets/fma_keys.py

@@ -0,0 +1,251 @@
+import csv
+import os
+import numpy as np
+from math import floor
+from smart_open import open
+
+import librosa
+
+from mirdata import download_utils, core, io
+from mirdata import jams_utils
+
+from typing import BinaryIO, Optional, Tuple
+
+NAME = "fma_keys"
+
+BIBTEX = """
+We present a new expert-labeled dataset for the evaluation of key detection containing 
+340 hours (5489 songs) of song-level key and mode annotations, spread across 17 genres. 
+
+For each song, we provide annotations for:
+* FMA track id
+* Spotify URI (when available)
+* Key and mode
+All the audio is collected in and distributed by the FMA dataset by Michael Defferrard, 
+Kirell Benzi, Pierre Vandergheynst, and Xavier Bresson.
+
+* The FMA metadata is made freely available for public use under a Creative Commons license
+* We do not hold the copyright on the audio and distribute it under the license chosen by the artist
+* The dataset is meant for research purposes
+
+Please cite our work if you use our dataset:
+    @inproceedings{
+        wong_fma_keys,
+        title = {{FMAK}: A Dataset of Key and Mode Annotations for the Free Music Archive},
+        author = {Wong, Stella and Hernandez, Gandalf},
+        booktitle = {24th International Society for Music Information Retrieval Conference (ISMIR)},
+        year = {2023}
+    }
+    
+}
+"""
+
+LICENSE_INFO = "Creative Commons Attribution 4.0 International"
+
+INDEXES = {
+    "default": "1.0",
+    "test": "1.0",
+    "1.0": core.Index(filename="fma_keys_index_1.0.json"),
+}
+
+# what the user will download
+REMOTES = {
+    "metadata": download_utils.RemoteFileMetadata(
+        filename="fma_keys_metadata.csv",
+        url="https://zenodo.org/records/10719860/files/fma_keys_metadata.csv?download=1",
+        checksum="d80a03bc8659edc60e335bd7f6bdf12a",
+    ),
+    "tracks-000-019": download_utils.RemoteFileMetadata(
+        filename="000-019.zip",
+        url="https://zenodo.org/records/10719860/files/000-019.zip?download=1",
+        checksum="b86f6414820c1422b2c6cdf87be1ef3a",
+    ),
+    "tracks-020-039": download_utils.RemoteFileMetadata(
+        filename="020-039.zip",
+        url="https://zenodo.org/records/10719860/files/020-039.zip?download=1",
+        checksum="a2da8377fdbc1d3a1f54dd60aa7b8f9b",
+    ),
+    "tracks-040-049": download_utils.RemoteFileMetadata(
+        filename="040-049.zip",
+        url="https://zenodo.org/records/10719860/files/040-049.zip?download=1",
+        checksum="d70babe5f66bdf3e821c42a8b8aafb9b",
+    ),
+    "tracks-050-059": download_utils.RemoteFileMetadata(
+        filename="050-059.zip",
+        url="https://zenodo.org/records/10719860/files/050-059.zip?download=1",
+        checksum="f53fcba704fce27e5c7f3ec2532dcb44",
+    ),
+    "tracks-060-069": download_utils.RemoteFileMetadata(
+        filename="060-069.zip",
+        url="https://zenodo.org/records/10719860/files/060-069.zip?download=1",
+        checksum="1520f067d7caaf0813780ff69bc4ba85",
+    ),
+    "tracks-070-079": download_utils.RemoteFileMetadata(
+        filename="070-079.zip",
+        url="https://zenodo.org/records/10719860/files/070-079.zip?download=1",
+        checksum="186643746fcb1f4722a28d3eb9c6b99c",
+    ),
+    "tracks-080-089": download_utils.RemoteFileMetadata(
+        filename="080-089.zip",
+        url="https://zenodo.org/records/10719860/files/080-089.zip?download=1",
+        checksum="8cf882609fc2f301621c2e9f9da03214",
+    ),
+    "tracks-090-099": download_utils.RemoteFileMetadata(
+        filename="090-099.zip",
+        url="https://zenodo.org/records/10719860/files/090-099.zip?download=1",
+        checksum="84f0f036e3778ffd97c10b591f803d06",
+    ),
+    "tracks-100-109": download_utils.RemoteFileMetadata(
+        filename="100-109.zip",
+        url="https://zenodo.org/records/10719860/files/100-109.zip?download=1",
+        checksum="4a307f019d3354064814f05d1dffa1e2",
+    ),
+    "tracks-110-124": download_utils.RemoteFileMetadata(
+        filename="110-124.zip",
+        url="https://zenodo.org/records/10719860/files/110-124.zip?download=1",
+        checksum="88d7dbcca82189ed75b7baa5aa132fc1",
+    ),
+}
+
+KEY_MAP = {
+    "C": 0,
+    "C#": 1,
+    "D": 2,
+    "D#": 3,
+    "E": 4,
+    "F": 5,
+    "F#": 6,
+    "G": 7,
+    "G#": 8,
+    "A": 9,
+    "Bb": 10,
+    "B": 11,
+}
+
+MODE_MAP = {"minor": 0, "Major": 1}
+
+
+class Track(core.Track):
+    """FMA Keys Track class
+
+    Args:
+        track_id (str): track id of the track
+
+    Attributes:
+        spotify_uri (str): Spotify URI if available
+        key (str): path to the track's audio file
+        mode (str): path to the track's audio file
+        key_number (int): path to the track's audio file
+        mode_number (int): path to the track's audio file
+        audio (str): path to the track's audio file
+    """
+
+    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 spotify_uri(self):
+        return self._track_metadata.get("spotify_uri")
+
+    @property
+    def key(self):
+        return self._track_metadata.get("key")
+
+    @property
+    def mode(self):
+        return self._track_metadata.get("mode")
+
+    @property
+    def key_number(self):
+        return self._track_metadata.get("key_number")
+
+    @property
+    def mode_number(self):
+        return self._track_metadata.get("mode_number")
+
+    @property
+    def audio(self) -> Optional[Tuple[np.ndarray, float]]:
+        """audio
+
+        Returns:
+            * np.ndarray - audio signal
+            * float - sample rate
+
+        """
+        return load_audio(self.audio_path)
+
+    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(
+            metadata=self._track_metadata,
+        )
+
+
+@core.docstring_inherit(core.Dataset)
+class Dataset(core.Dataset):
+    """
+    The FMA Keys dataset
+    """
+
+    def __init__(self, data_home=None, version="default"):
+        super().__init__(
+            data_home,
+            version,
+            name="fma_keys",
+            track_class=Track,
+            bibtex=BIBTEX,
+            indexes=INDEXES,
+            remotes=REMOTES,
+            license_info=LICENSE_INFO,
+        )
+
+    def _track_to_dict(self, t):
+        key_and_mode = t["key_and_mode"].split(" ")
+
+        return {
+            "spotify_uri": t["spotify_uri"],
+            "key": key_and_mode[0],
+            "mode": key_and_mode[1],
+            "key_number": KEY_MAP[key_and_mode[0]],
+            "mode_number": MODE_MAP[key_and_mode[1]],
+        }
+
+    @core.cached_property
+    def _metadata(self):
+        metadata_path = os.path.join(self.data_home, "fma_keys_metadata.csv")
+
+        metadata_index = {}
+        try:
+            with open(metadata_path) as f:
+                metadata_index = {
+                    t["track_id"]: self._track_to_dict(t) for t in csv.DictReader(f)
+                }
+
+        except FileNotFoundError:
+            raise FileNotFoundError("Metadata not found. Did you run .download()?")
+
+        return metadata_index
+
+
+@io.coerce_to_bytes_io
+def load_audio(fhandle: BinaryIO) -> Tuple[np.ndarray, float]:
+    """Load vocadito vocal audio
+
+    Args:
+        fhandle (str or file-like): File-like object or path to audio file
+
+    Returns:
+        * np.ndarray - audio signal
+        * float - sample rate
+
+    """
+    # librosa has problems reading FMA mp3s without clamping down to the second.
+    duration = librosa.get_duration(path=fhandle)
+    return librosa.load(fhandle, sr=None, mono=True, duration=floor(duration))