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import os |
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import json |
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import numpy as np |
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import datasets |
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from datasets import Features, Value, Audio, Array2D, Sequence |
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from pathlib import Path |
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import librosa |
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_CITATION = """\ |
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comming soon. |
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""" |
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_DESCRIPTION = """\ |
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SongFormBench is a high-quality benchmark dataset for song structure analysis, consisting of 200 songs from HarmonixSet and 100 Chinese pop songs, aimed at establishing a unified evaluation standard in the MSA field, advancing the task, and addressing the lack of Chinese data. |
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""" |
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_HOMEPAGE = "https://huggingface.co/datasets/ASLP-lab/SongFormBench" |
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_LICENSE = "cc-by-4.0" |
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class SongFormBench(datasets.GeneratorBasedBuilder): |
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"""SongFormBench: A Benchmark for Song Structure Analysis (only test split).""" |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name="default", |
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version=datasets.Version("1.0.0"), |
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description="MSA Benchmark Test Set", |
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), |
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] |
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DEFAULT_CONFIG_NAME = "default" |
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def _info(self): |
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features = Features( |
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{ |
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"id": Value("string"), |
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"youtube_url": Value("string"), |
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"subset": Value("string"), |
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"language": Value("string"), |
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"audio": Audio(), |
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"mel_path": Value("string"), |
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"label_path": Value("string"), |
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"labels": { |
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"segments": Sequence( |
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{ |
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"start": Value("float32"), |
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"label": Value("string"), |
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} |
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), |
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}, |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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citation=_CITATION, |
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license=_LICENSE, |
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homepage=_HOMEPAGE, |
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) |
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def _split_generators(self, dl_manager): |
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test_path = os.path.join(dl_manager.manual_dir, "data/SongFormBench.jsonl") |
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self.root_dir = dl_manager.manual_dir |
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with open(test_path, "r", encoding="utf-8") as f: |
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items = [json.loads(line) for line in f] |
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self.items = items |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"items": self.items}, |
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), |
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] |
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def _generate_examples(self, items): |
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"""从内存数据生成样本""" |
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for entry in items: |
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raw_labels = entry.get("labels", []) |
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yield ( |
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entry["id"], |
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{ |
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"id": entry["id"], |
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"youtube_url": entry.get("youtube_url", ""), |
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"subset": entry.get("subset", ""), |
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"language": entry.get("language", ""), |
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"audio": str(Path(self.root_dir) / entry["audio_path"]), |
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"mel_path": str(Path(self.root_dir) / entry.get("mel_path", "")), |
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"label_path": str( |
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Path(self.root_dir) / entry.get("label_path", "") |
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), |
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"labels": { |
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"segments": raw_labels, |
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}, |
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}, |
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) |
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