aac_datasets.datasets.audiocaps module¶
- class AudioCaps(
- root: str | Path | None = None,
- subset: typing_extensions.Literal[train, val, test, train_fixed] = 'train',
- download: bool = False,
- transform: Callable[[AudioCapsItem], Any] | None = None,
- verbose: int = 0,
- force_download: bool = False,
- verify_files: bool = False,
- *,
- audio_duration: float = 10.0,
- audio_format: str = 'flac',
- audio_n_channels: int = 1,
- download_audio: bool = True,
- exclude_removed_audio: bool = True,
- ffmpeg_path: str | Path | None = None,
- flat_captions: bool = False,
- max_workers: int | None = 1,
- sr: int = 32000,
- with_tags: bool = False,
- ytdlp_path: str | Path | None = None,
- ytdlp_opts: Iterable[str] = (),
- version: typing_extensions.Literal[v1, v2] = 'v1',
- num_dl_attempts: int = 2,
Bases:
AACDataset[AudioCapsItem]Unofficial AudioCaps PyTorch dataset.
Subsets available are ‘train’, ‘val’ and ‘test’.
Audio is a waveform tensor of shape (1, n_times) of 10 seconds max, sampled at 32kHz by default. Target is a list of strings containing the captions. The ‘train’ subset has only 1 caption per sample and ‘val’ and ‘test’ have 5 captions. Download from YouTube requires ‘yt-dlp’ and ‘ffmpeg’ commands.
- /!YouTube website can sometimes block your IP when downloading audio with the error:
Sign in to confirm you’re not a bot. Use –cookies-from-browser or –cookies for the authentication. See https://github.com/yt-dlp/yt-dlp/wiki/FAQ#how-do-i-pass-cookies-to-yt-dlp for how to manually pass cookies. Also see https://github.com/yt-dlp/yt-dlp/wiki/Extractors#exporting-youtube-cookies for tips on effectively exporting YouTube cookies.
You can pass yt-dlp args with ytdlp_opts argument, e.g. AudioCaps(ytdlp_opts=[”–cookies-from-browser”, “firefox”]).
See also: AudioCaps paper : https://www.aclweb.org/anthology/N19-1011.pdf
Dataset folder tree (for version v1)¶{root} └── AUDIOCAPS ├── csv_files_v1 │ ├── train.csv │ ├── val.csv │ └── test.csv └── audio_32000Hz ├── train │ └── (46231/49838 flac files, ~42G for 32kHz) ├── val │ └── (465/495 flac files, ~425M for 32kHz) └── test └── (913/975 flac files, ~832M for 32kHz)- CARD: ClassVar[AudioCapsCard] = <aac_datasets.datasets.functional.audiocaps.AudioCapsCard object>¶
- property subset: typing_extensions.Literal[train, val, test, train_fixed]¶
- property version: typing_extensions.Literal[v1, v2]¶