# coding=utf-8 """MagnaTagATune dataset.""" import os import json import gzip import shutil import pathlib import logging import textwrap import datasets import itertools import typing as tp import pandas as pd import urllib.request from pathlib import Path from copy import deepcopy from tqdm.auto import tqdm from rich.logging import RichHandler logger = logging.getLogger(__name__) logger.addHandler(RichHandler()) logger.setLevel(logging.INFO) SAMPLE_RATE = 16_000 # Cache location VERSION = "0.0.1" DEFAULT_XDG_CACHE_HOME = "~/.cache" XDG_CACHE_HOME = os.getenv("XDG_CACHE_HOME", DEFAULT_XDG_CACHE_HOME) DEFAULT_HF_CACHE_HOME = os.path.join(XDG_CACHE_HOME, "huggingface") HF_CACHE_HOME = os.path.expanduser(os.getenv("HF_HOME", DEFAULT_HF_CACHE_HOME)) DEFAULT_HF_DATASETS_CACHE = os.path.join(HF_CACHE_HOME, "datasets") HF_DATASETS_CACHE = Path(os.getenv("HF_DATASETS_CACHE", DEFAULT_HF_DATASETS_CACHE)) TOP_50_CLASSES = [ 'ambient', 'beat', 'beats', 'cello', 'choir', 'choral', 'classic', 'classical', 'country', 'dance', 'drums', 'electronic', 'fast', 'female', 'female vocal', 'female voice', 'flute', 'guitar', 'harp', 'harpsichord', 'indian', 'loud', 'male', 'male vocal', 'male voice', 'man', 'metal', 'new age', 'no vocal', 'no vocals', 'no voice', 'opera', 'piano', 'pop', 'quiet', 'rock', 'singing', 'sitar', 'slow', 'soft', 'solo', 'strings', 'synth', 'techno', 'violin', 'vocal', 'vocals', 'voice', 'weird', 'woman' ] CLASS2INDEX = {cls:idx for idx, cls in enumerate(TOP_50_CLASSES)} INDEX2CLASS = {idx:cls for idx, cls in enumerate(TOP_50_CLASSES)} class MagnaTagATuneConfig(datasets.BuilderConfig): """BuilderConfig for MagnaTagATune.""" def __init__(self, features, **kwargs): super(MagnaTagATuneConfig, self).__init__(version=datasets.Version(VERSION, ""), **kwargs) self.features = features class MagnaTagATune(datasets.GeneratorBasedBuilder): BUILDER_CONFIGS = [ MagnaTagATuneConfig( features=datasets.Features( { "file": datasets.Value("string"), "audio": datasets.Audio(sampling_rate=SAMPLE_RATE), "tags": datasets.Sequence(datasets.Value("string")), "label": datasets.Sequence(datasets.features.ClassLabel(names=TOP_50_CLASSES)), } ), name="top50", description="", ), ] DEFAULT_CONFIG_NAME = "top50" def _info(self): return datasets.DatasetInfo( description="", features=self.config.features, supervised_keys=None, homepage="", citation="", task_templates=None, ) def _load_metadata(self): # Read metadata df = pd.read_csv("https://mirg.city.ac.uk/datasets/magnatagatune/annotations_final.csv", sep="\t") df = df[df[TOP_50_CLASSES].sum(axis=1) > 0] df = df[TOP_50_CLASSES + ["mp3_path", "clip_id"]] train_ids_df = pd.read_csv( 'https://raw.githubusercontent.com/jordipons/musicnn-training/master/data/index/mtt/train_gt_mtt.tsv', sep='\t', header=None ) train_ids = train_ids_df[0].tolist() train_df = df[df["clip_id"].isin(train_ids)] validation_ids_df = pd.read_csv( "https://raw.githubusercontent.com/jordipons/musicnn-training/master/data/index/mtt/val_gt_mtt.tsv", sep="\t", header=None ) validation_ids = validation_ids_df[0].tolist() validation_df = df[df["clip_id"].isin(validation_ids)] test_ids_df = pd.read_csv( "https://raw.githubusercontent.com/jordipons/musicnn-training/master/data/index/mtt/test_gt_mtt.tsv", sep="\t", header=None ) test_ids = test_ids_df[0].tolist() test_df = df[df["clip_id"].isin(test_ids)] label_names = df.columns label_names = label_names.drop(["mp3_path", "clip_id"]) return train_df, validation_df, test_df, label_names def _split_generators(self, dl_manager): """Returns SplitGenerators.""" if self.config.name == 'top50': mp3_zip_files = [ 'https://mirg.city.ac.uk/datasets/magnatagatune/mp3.zip.001', 'https://mirg.city.ac.uk/datasets/magnatagatune/mp3.zip.002', 'https://mirg.city.ac.uk/datasets/magnatagatune/mp3.zip.003', ] for zip_file_url in mp3_zip_files: _filename = zip_file_url.split('/')[-1] _save_path = os.path.join( HF_DATASETS_CACHE, 'confit___magnatagatune/top50', VERSION, _filename ) download_file(zip_file_url, _save_path) logger.info(f"`{_filename}` is downloaded to {_save_path}") main_zip_filename = 'mp3.zip' _save_dir = os.path.join(HF_DATASETS_CACHE, 'confit___magnatagatune/top50', VERSION) _output_file = os.path.join(_save_dir, main_zip_filename) if not os.path.exists(_output_file): logger.info(f"Concatenate zip files to {main_zip_filename}") os.system(f"cat {os.path.join(_save_dir, 'mp3.zip.*')} > {_output_file}") archive_path = dl_manager.extract(_output_file) logger.info(f"`{main_zip_filename}` is now extracted to {archive_path}") return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={"archive_path": archive_path, "split": "train"} ), datasets.SplitGenerator( name=datasets.Split.VALIDATION, gen_kwargs={"archive_path": archive_path, "split": "validation"} ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={"archive_path": archive_path, "split": "test"} ), ] def _generate_examples(self, archive_path, split=None, metadata_df=None): train_df, validation_df, test_df, label_names = self._load_metadata() extensions = ['.mp3'] _, _walker = fast_scandir(archive_path, extensions, recursive=True) class2index = {cls:idx for idx, cls in enumerate(label_names)} index2class = {idx:cls for idx, cls in enumerate(label_names)} if split == 'train': fileid2class = {} for idx, row in train_df.iterrows(): fileid = row['mp3_path'] class_ = row[label_names].tolist() if sum(class_) == 0: continue class_ = [idx for idx, val in enumerate(class_) if val != 0] class_ = [index2class.get(idx) for idx in class_] fileid2class[fileid] = class_ elif split == 'validation': fileid2class = {} for idx, row in validation_df.iterrows(): fileid = row['mp3_path'] class_ = row[label_names].tolist() if sum(class_) == 0: continue class_ = [idx for idx, val in enumerate(class_) if val != 0] class_ = [index2class.get(idx) for idx in class_] fileid2class[fileid] = class_ elif split == 'test': fileid2class = {} for idx, row in test_df.iterrows(): fileid = row['mp3_path'] class_ = row[label_names].tolist() if sum(class_) == 0: continue class_ = [idx for idx, val in enumerate(class_) if val != 0] class_ = [index2class.get(idx) for idx in class_] fileid2class[fileid] = class_ for guid, audio_path in enumerate(_walker): parent = Path(audio_path).parent.stem filename = Path(audio_path).name fileid = f"{parent}/{filename}" if fileid not in fileid2class: continue tags = fileid2class.get(fileid) yield guid, { "id": str(guid), "file": audio_path, "audio": audio_path, "tags": tags, "label": tags, } 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 def download_file( source, dest, unpack=False, dest_unpack=None, replace_existing=False, write_permissions=False, ): """Downloads the file from the given source and saves it in the given destination path. Arguments --------- source : path or url Path of the source file. If the source is an URL, it downloads it from the web. dest : path Destination path. unpack : bool If True, it unpacks the data in the dest folder. dest_unpack: path Path where to store the unpacked dataset replace_existing : bool If True, replaces the existing files. write_permissions: bool When set to True, all the files in the dest_unpack directory will be granted write permissions. This option is active only when unpack=True. """ class DownloadProgressBar(tqdm): """DownloadProgressBar class.""" def update_to(self, b=1, bsize=1, tsize=None): """Needed to support multigpu training.""" if tsize is not None: self.total = tsize self.update(b * bsize - self.n) # Create the destination directory if it doesn't exist dest_dir = pathlib.Path(dest).resolve().parent dest_dir.mkdir(parents=True, exist_ok=True) if "http" not in source: shutil.copyfile(source, dest) elif not os.path.isfile(dest) or ( os.path.isfile(dest) and replace_existing ): print(f"Downloading {source} to {dest}") with DownloadProgressBar( unit="B", unit_scale=True, miniters=1, desc=source.split("/")[-1], ) as t: urllib.request.urlretrieve( source, filename=dest, reporthook=t.update_to ) else: print(f"{dest} exists. Skipping download") # Unpack if necessary if unpack: if dest_unpack is None: dest_unpack = os.path.dirname(dest) print(f"Extracting {dest} to {dest_unpack}") # shutil unpack_archive does not work with tar.gz files if ( source.endswith(".tar.gz") or source.endswith(".tgz") or source.endswith(".gz") ): out = dest.replace(".gz", "") with gzip.open(dest, "rb") as f_in: with open(out, "wb") as f_out: shutil.copyfileobj(f_in, f_out) else: shutil.unpack_archive(dest, dest_unpack) if write_permissions: set_writing_permissions(dest_unpack) def set_writing_permissions(folder_path): """ This function sets user writing permissions to all the files in the given folder. Arguments --------- folder_path : folder Folder whose files will be granted write permissions. """ for root, dirs, files in os.walk(folder_path): for file_name in files: file_path = os.path.join(root, file_name) # Set writing permissions (mode 0o666) to the file os.chmod(file_path, 0o666)