Add loader for candombe_beat_downbeat

docs/source/mirdata.rst

@@ -52,6 +52,14 @@ billboard
    :inherited-members:
 
 
+candombe
+^^^^^^^^
+
+.. automodule:: mirdata.datasets.candombe
+   :members:
+   :inherited-members:
+
+
 cante100
 ^^^^^^^^
 

docs/source/table.rst

@@ -53,6 +53,14 @@
      - .. image:: https://licensebuttons.net/l/zero/1.0/80x15.png
           :target: http://creativecommons.org/publicdomain/zero/1.0/
 
+   * - Candombe
+     - - audio: ✅
+       - annotations: ✅
+     - - :ref:`beats`
+     - 35
+     - .. image:: https://licensebuttons.net/l/by-nc-sa/4.0/80x15.png
+          :target: https://creativecommons.org/licenses/by-nc-sa/4.0
+
    * - cante100
      - - audio: 🔑
        - annotations: ✅

mirdata/datasets/candombe.py

@@ -0,0 +1,177 @@
+"""Candombe Dataset Loader
+
+.. admonition:: Dataset Info
+    :class: dropdown
+
+    This is a dataset of Candombe recordings with annotated beats and downbeats, totaling over 2 hours of audio. 
+    It comprises 35 complete performances by renowned players, in groups of three to five drums. 
+    Recording sessions were conducted in studio, in the context of musicological research over the past two decades.
+    A total of 26 tambor players took part, belonging to different generations and representing all the important traditional Candombe styles.
+    The audio files are stereo with a sampling rate of 44.1 kHz and 16-bit precision. 
+    The location of beats and downbeats was annotated by an expert, adding to more than 4700 downbeats.
+
+    The audio is provided as .flac files and the annotations as .csv files. 
+    The values in the first column of the csv file are the time instants of the beats.
+    The numbers on the second column indicate both the bar number and the beat number within the bar.
+    For instance, 1.1, 1.2, 1.3 and 1.4 are the four beats of the first bar. Hence, each label ending with .1 indicates a downbeat.
+    Another set of annotations are provided as .beats files in which the bar numbers are removed.
+
+"""
+import csv
+from typing import BinaryIO, Optional, TextIO, Tuple
+
+import librosa
+import numpy as np
+
+from mirdata import download_utils, jams_utils, core, annotations, io
+
+BIBTEX = """
+@inproceedings{Nunes2015,
+    author = {Leonardo Nunes and Martín Rocamora and Luis Jure and Luiz W. P. Biscainho},
+    title = {{Beat and Downbeat Tracking Based on Rhythmic Patterns Applied to the Uruguayan Candombe Drumming}},
+    booktitle = {Proceedings of the 16th International Society for Music Information Retrieval Conference (ISMIR 2015)},
+    month = {Oct.},
+    address = {Málaga, Spain},
+    pages = {264--270},
+    year = {2015}
+}
+"""
+
+INDEXES = {
+    "default": "1.0",
+    "test": "1.0",
+    "1.0": core.Index(filename="candombe_index_1.0.json"),
+}
+
+
+REMOTES = {
+    "annotations": download_utils.RemoteFileMetadata(
+        filename="candombe_annotations.zip",
+        url="https://zenodo.org/record/6533068/files/candombe_annotations.zip",
+        checksum="f78aff60aa413cb4960c0c77cc31c243",
+        destination_dir=None,
+    ),
+    "audio": download_utils.RemoteFileMetadata(
+        filename="candombe_audio.zip",
+        url="https://zenodo.org/record/6533068/files/candombe_audio.zip",
+        checksum="ccd7f437024807b1a52c0818aa0b7f06",
+        destination_dir=None,
+    ),
+}
+
+LICENSE_INFO = """
+Creative Commons Attribution 4.0 International
+"""
+
+
+class Track(core.Track):
+    """candombe track class
+    # -- YOU CAN AUTOMATICALLY GENERATE THIS DOCSTRING BY CALLING THE SCRIPT:
+    # -- `scripts/print_track_docstring.py my_dataset`
+    # -- note that you'll first need to have a test track (see "Adding tests to your dataset" below)
+
+    Args:
+        track_id (str): track id of the track
+
+    Attributes:
+        audio_path (str): path to audio file
+        annotation_path (str): path to annotation file
+        # -- Add any of the dataset specific attributes here
+
+    Cached Properties:
+        annotation (EventData): a description of this annotation
+
+    """
+
+    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")
+        self.beats_path = self.get_path("beats")
+
+    @core.cached_property
+    def beats(self) -> Optional[annotations.BeatData]:
+        """The track's beats
+
+        Returns:
+            BeatData: loaded beat data
+
+        """
+        return load_beats(self.beats_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)
+
+    def to_jams(self):
+        """Jams: the track's data in jams format"""
+        return jams_utils.jams_converter(
+            audio_path=self.audio_path, beat_data=[(self.beats, None)], metadata=None
+        )
+
+
+@io.coerce_to_bytes_io
+def load_audio(fhandle: BinaryIO) -> Tuple[np.ndarray, float]:
+    """Load a candombe audio file.
+
+    Args:
+        fhandle (str or file-like): path or file-like object pointing to an audio file
+
+    Returns:
+        * np.ndarray - the audio signal
+        * float - The sample rate of the audio file
+
+    """
+    return librosa.load(fhandle, sr=None, mono=True)
+
+
+@io.coerce_to_string_io
+def load_beats(fhandle: TextIO) -> annotations.BeatData:
+    """Load a candombe beats file.
+
+    Args:
+        fhandle (str or file-like): path or file-like object pointing to an audio file
+
+    Returns:
+        * BeatData: loaded beat data
+
+
+    """
+    reader = csv.reader(fhandle, delimiter=",")
+    times = []
+    beats = []
+    for line in reader:
+        times.append(float(line[0]))
+        beats.append(int(line[1].split(".")[1]))
+
+    beat_data = annotations.BeatData(
+        times=np.array(times),
+        time_unit="s",
+        positions=np.array(beats),
+        position_unit="bar_index",
+    )
+    return beat_data
+
+
+@core.docstring_inherit(core.Dataset)
+class Dataset(core.Dataset):
+    """The candombe dataset"""
+
+    def __init__(self, data_home=None, version="default"):
+        super().__init__(
+            data_home,
+            version,
+            name="candombe",
+            track_class=Track,
+            bibtex=BIBTEX,
+            indexes=INDEXES,
+            remotes=REMOTES,
+            license_info=LICENSE_INFO,
+        )