aac_datasets.datasets.macs module¶
- class MACS(
- root: str | Path | None = None,
- subset: str = 'full',
- download: bool = False,
- transform: Callable[[MACSItem], Any] | None = None,
- verbose: int = 0,
- force_download: bool = False,
- verify_files: bool = False,
- *,
- clean_archives: bool = True,
- flat_captions: bool = False,
Bases:
AACDataset
[MACSItem
]Unofficial MACS PyTorch dataset.
{root} └── MACS ├── audio │ └── (3930 wav files, ~13GB) ├── LICENCE.txt ├── MACS.yaml ├── MACS_competence.csv └── tau_meta ├── fold1_evaluate.csv ├── fold1_test.csv ├── fold1_train.csv └── meta.csv
- get_annotator_id_to_competence_dict() Dict[int, float] [source]¶
Get annotator to competence dictionary.