Datasets:
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import os
import json
import numpy as np
import datasets
from datasets import Features, Value, Audio, Array2D, Sequence
from pathlib import Path
import librosa
_CITATION = """\
comming soon.
"""
_DESCRIPTION = """\
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.
"""
_HOMEPAGE = "https://huggingface.co/datasets/ASLP-lab/SongFormBench"
_LICENSE = "cc-by-4.0"
class SongFormBench(datasets.GeneratorBasedBuilder):
"""SongFormBench: A Benchmark for Song Structure Analysis (only test split)."""
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="default",
version=datasets.Version("1.0.0"),
description="MSA Benchmark Test Set",
),
]
DEFAULT_CONFIG_NAME = "default"
def _info(self):
features = Features(
{
"id": Value("string"),
"youtube_url": Value("string"),
"subset": Value("string"),
"language": Value("string"),
"audio": Audio(),
"mel_path": Value("string"),
"label_path": Value("string"),
"labels": {
"segments": Sequence(
{
"start": Value("float32"),
"label": Value("string"),
}
),
},
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
citation=_CITATION,
license=_LICENSE,
homepage=_HOMEPAGE,
)
def _split_generators(self, dl_manager):
test_path = os.path.join(dl_manager.manual_dir, "data/SongFormBench.jsonl")
self.root_dir = dl_manager.manual_dir # 保存根目录以供后续使用
with open(test_path, "r", encoding="utf-8") as f:
items = [json.loads(line) for line in f]
self.items = items # 将数据存储为实例变量，供 _generate_examples 使用
return [
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"items": self.items}, # 将数据传递给生成器
),
]
def _generate_examples(self, items):
"""从内存数据生成样本"""
for entry in items:
raw_labels = entry.get("labels", [])
yield (
entry["id"],
{
"id": entry["id"],
"youtube_url": entry.get("youtube_url", ""),
"subset": entry.get("subset", ""),
"language": entry.get("language", ""),
"audio": str(Path(self.root_dir) / entry["audio_path"]),
"mel_path": str(Path(self.root_dir) / entry.get("mel_path", "")),
"label_path": str(
Path(self.root_dir) / entry.get("label_path", "")
),
"labels": {
"segments": raw_labels,
},
},
)
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