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import os |
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import random |
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import datasets |
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from datasets.tasks import ImageClassification, AudioClassification |
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_NAMES = [ |
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"PearlRiver", |
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"YoungChang", |
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"Steinway-T", |
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"Hsinghai", |
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"Kawai", |
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"Steinway", |
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"Kawai-G", |
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"Yamaha", |
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] |
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_DBNAME = os.path.basename(__file__).split(".")[0] |
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_HOMEPAGE = f"https://www.modelscope.cn/datasets/ccmusic/{_DBNAME}" |
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_DOMAIN = f"https://www.modelscope.cn/api/v1/datasets/ccmusic/{_DBNAME}/repo?Revision=master&FilePath=data" |
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_CITATION = """\ |
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@dataset{zhaorui_liu_2021_5676893, |
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author = {Monan Zhou, Shenyang Xu, Zhaorui Liu, Zhaowen Wang, Feng Yu, Wei Li and Zijin Li}, |
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title = {CCMusic: an Open and Diverse Database for Chinese and General Music Information Retrieval Research}, |
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month = {mar}, |
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year = {2024}, |
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publisher = {HuggingFace}, |
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version = {1.2}, |
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url = {https://huggingface.co/ccmusic-database} |
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} |
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""" |
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_DESCRIPTION = """\ |
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Piano-Sound-Quality is a dataset of piano sound. It consists of 8 kinds of pianos including PearlRiver, YoungChang, Steinway-T, Hsinghai, Kawai, Steinway, Kawai-G, Yamaha(recorded by Shaohua Ji with SONY PCM-D100). Data was annotated by students from the China Conservatory of Music (CCMUSIC) in Beijing and collected by Monan Zhou. |
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""" |
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_PITCHES = { |
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"009": "A2", |
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"010": "A2#/B2b", |
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"011": "B2", |
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"100": "C1", |
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"101": "C1#/D1b", |
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"102": "D1", |
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"103": "D1#/E1b", |
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"104": "E1", |
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"105": "F1", |
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"106": "F1#/G1b", |
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"107": "G1", |
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"108": "G1#/A1b", |
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"109": "A1", |
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"110": "A1#/B1b", |
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"111": "B1", |
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"200": "C", |
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"201": "C#/Db", |
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"202": "D", |
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"203": "D#/Eb", |
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"204": "E", |
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"205": "F", |
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"206": "F#/Gb", |
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"207": "G", |
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"208": "G#/Ab", |
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"209": "A", |
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"210": "A#/Bb", |
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"211": "B", |
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"300": "c", |
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"301": "c#/db", |
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"302": "d", |
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"303": "d#/eb", |
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"304": "e", |
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"305": "f", |
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"306": "f#/gb", |
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"307": "g", |
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"308": "g#/ab", |
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"309": "a", |
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"310": "a#/bb", |
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"311": "b", |
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"400": "c1", |
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"401": "c1#/d1b", |
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"402": "d1", |
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"403": "d1#/e1b", |
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"404": "e1", |
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"405": "f1", |
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"406": "f1#/g1b", |
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"407": "g1", |
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"408": "g1#/a1b", |
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"409": "a1", |
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"410": "a1#/b1b", |
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"411": "b1", |
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"500": "c2", |
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"501": "c2#/d2b", |
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"502": "d2", |
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"503": "d2#/e2b", |
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"504": "e2", |
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"505": "f2", |
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"506": "f2#/g2b", |
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"507": "g2", |
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"508": "g2#/a2b", |
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"509": "a2", |
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"510": "a2#/b2b", |
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"511": "b2", |
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"600": "c3", |
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"601": "c3#/d3b", |
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"602": "d3", |
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"603": "d3#/e3b", |
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"604": "e3", |
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"605": "f3", |
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"606": "f3#/g3b", |
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"607": "g3", |
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"608": "g3#/a3b", |
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"609": "a3", |
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"610": "a3#/b3b", |
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"611": "b3", |
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"700": "c4", |
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"701": "c4#/d4b", |
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"702": "d4", |
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"703": "d4#/e4b", |
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"704": "e4", |
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"705": "f4", |
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"706": "f4#/g4b", |
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"707": "g4", |
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"708": "g4#/a4b", |
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"709": "a4", |
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"710": "a4#/b4b", |
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"711": "b4", |
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"800": "c5", |
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} |
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_URLS = { |
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"audio": f"{_DOMAIN}/audio.zip", |
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"mel": f"{_DOMAIN}/mel.zip", |
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"eval": f"{_DOMAIN}/eval.zip", |
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} |
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class pianos_Config(datasets.BuilderConfig): |
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def __init__(self, features, supervised_keys, task_templates, **kwargs): |
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super(pianos_Config, self).__init__(version=datasets.Version("0.1.2"), **kwargs) |
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self.features = features |
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self.supervised_keys = supervised_keys |
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self.task_templates = task_templates |
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class pianos(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("0.1.2") |
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BUILDER_CONFIGS = [ |
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pianos_Config( |
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name="eval", |
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features=datasets.Features( |
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{ |
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"mel": datasets.Image(), |
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"label": datasets.features.ClassLabel(names=_NAMES), |
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"pitch": datasets.features.ClassLabel( |
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names=list(_PITCHES.values()) |
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), |
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} |
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), |
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supervised_keys=("mel", "label"), |
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task_templates=[ |
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ImageClassification( |
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task="image-classification", |
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image_column="mel", |
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label_column="label", |
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) |
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], |
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), |
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pianos_Config( |
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name="default", |
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features=datasets.Features( |
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{ |
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"audio": datasets.Audio(sampling_rate=22050), |
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"mel": datasets.Image(), |
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"label": datasets.features.ClassLabel(names=_NAMES), |
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"pitch": datasets.features.ClassLabel( |
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names=list(_PITCHES.values()) |
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), |
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} |
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), |
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supervised_keys=("audio", "label"), |
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task_templates=[ |
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AudioClassification( |
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task="audio-classification", |
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audio_column="audio", |
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label_column="label", |
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) |
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], |
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), |
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] |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=self.config.features, |
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homepage=_HOMEPAGE, |
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license="mit", |
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citation=_CITATION, |
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supervised_keys=self.config.supervised_keys, |
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task_templates=self.config.task_templates, |
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) |
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def _split_generators(self, dl_manager): |
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dataset = [] |
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if self.config.name == "eval": |
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data_files = dl_manager.download_and_extract(_URLS["eval"]) |
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for path in dl_manager.iter_files([data_files]): |
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fname = os.path.basename(path) |
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if fname.endswith(".jpg"): |
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dataset.append( |
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{ |
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"mel": path, |
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"label": os.path.basename(os.path.dirname(path)), |
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"pitch": _PITCHES[fname.split("_")[0]], |
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} |
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) |
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else: |
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subset = {} |
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audio_files = dl_manager.download_and_extract(_URLS["audio"]) |
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for path in dl_manager.iter_files([audio_files]): |
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fname = os.path.basename(path) |
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if fname.endswith(".wav"): |
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subset[fname.split(".")[0]] = { |
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"audio": path, |
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"label": os.path.basename(os.path.dirname(path)), |
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"pitch": _PITCHES[fname[1:4]], |
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} |
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mel_files = dl_manager.download_and_extract(_URLS["mel"]) |
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for path in dl_manager.iter_files([mel_files]): |
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fname = os.path.basename(path) |
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if fname.endswith(".jpg"): |
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subset[fname.split(".")[0]]["mel"] = path |
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dataset = list(subset.values()) |
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random.shuffle(dataset) |
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count = len(dataset) |
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p80 = int(0.8 * count) |
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p90 = int(0.9 * count) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, gen_kwargs={"files": dataset[:p80]} |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, gen_kwargs={"files": dataset[p80:p90]} |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, gen_kwargs={"files": dataset[p90:]} |
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), |
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] |
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def _generate_examples(self, files): |
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if self.config.name == "eval": |
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for i, path in enumerate(files): |
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yield i, { |
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"mel": path["mel"], |
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"label": path["label"], |
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"pitch": path["pitch"], |
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} |
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else: |
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for i, path in enumerate(files): |
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yield i, { |
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"audio": path["audio"], |
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"mel": path["mel"], |
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"label": path["label"], |
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"pitch": path["pitch"], |
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} |
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