Datasets:
Yougen/datacos_dataset
DaCoS (Da Cover Song) audio dataset, packed as WebDataset tar shards.
Each row in the original output.csv is one recording; rows sharing the
same clique are alternative versions ("covers") of the same underlying
song.
Layout
data/
train/
metadata.csv
audio/
train-000.tar
train-001.tar
...
Shard counts:
train: 90 tar shard(s)
Inside each tar, every sample is a pair sharing a unique key:
<key>.mp3 # raw MP3 bytes
<key>.json # {"id":..., "rel_path":..., "wav_format":"mp3",
# "duration":..., "label_str":"<clique>", "label":<int>,
# "clique":..., "version":..., "title":...,
# "performer":..., "video_id":...}
metadata.csv columns:
key, shard, id, rel_path, wav_format, duration, label_str, label, clique, version, title, performer, video_id
Loading
from datasets import load_dataset
ds = load_dataset("Yougen/datacos_dataset")
print(ds)
print(ds["train"][0])
# sample keys: 'mp3' (decoded audio), 'json' (metadata), '__key__', '__url__'
For streaming (no full download needed):
ds = load_dataset("Yougen/datacos_dataset", streaming=True)
for example in ds["train"]:
print(example["__key__"], example["json"]["clique"], example["json"]["title"])
break
HuggingFace's webdataset builder will automatically pair <key>.mp3 with
<key>.json inside every tar and decode the audio.
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