o i- @sddlZddlmZddlmZmZmZddlmZddl m Z ddl m Z ddl mZmZdZd gd gd d d ddddZdZdZdefddZdedededeefddZdedefddZdedefd d!ZGd"d#d#e ZGd$d%d%eZGd&d'd'eZdS)(N)Path)ListTupleUnion)Tensor)Dataset)download_url_to_file) _extract_zip_load_waveformi>zvox1_dev_wav.zip)zIhttps://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partaazIhttps://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partabzIhttps://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partaczIhttps://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partad)@21ec6ca843659ebc2fdbe04b530baa4f191ad4b0971912672d92c158f32226a0@311d21e0c8cbf33573a4fce6c80e5a279d80736274b381c394319fc557159a04@92b64465f2b2a3dc0e4196ae8dd6828cbe9ddd1f089419a11e4cbfe2e1750df0@00e6190c770b27f27d2a3dd26ee15596b17066b715ac111906861a7d09a211a5) archive_nameurls checksumszvox1_test_wav.zipzGhttps://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_test_wav.zip@8de57f347fe22b2c24526e9f444f689ecf5096fc2a92018cf420ff6b5b15eaea)rurlchecksumdevtestzBhttps://www.robots.ox.ac.uk/~vgg/data/voxceleb/meta/iden_split.txtzAhttps://www.robots.ox.ac.uk/~vgg/data/voxceleb/meta/veri_test.txtrootc CsdD]}t|d}tj||}|dkrot|d}t|d}t|d@}t||D]2\}}tj|tj|} t|| |dt| d} || Wdn1sYwYq,Wdn1siwYnt|d }t|d }t|||dt |qdS) Nrrrrrwb) hash_prefixrbrr) _ARCHIVE_CONFIGSospathjoinopenzipbasenamerwritereadr ) rarchiver archive_pathrrfrr file_pathf_splitr*Q/home/ubuntu/.local/lib/python3.10/site-packages/torchaudio/datasets/voxceleb1.py_download_extract_wavs&s,        r,r(subsetreturnc Csg}|dkr d}n |dkrd}nd}t|d!}|D]}|\}}t||kr-||qWdt|S1s;wYt|S)Ntrainrr)r splitintappendsorted) rr(r-f_listindexr'lineidrr*r*r+ _get_flist<s"     r<veri_test_pathcCs\g}t|d}|D]}|\}}}||||fq Wd|S1s'wY|S)Nr3)r r4r6)rr=r8r'r:labelpath1path2r*r*r+_get_paired_flistLs  rA _ext_audiocCs8|ddd\}}}||d}d|||g}|S)N/-)r4replacer)r(rB speaker_id youtube_id utterance_idfile_idr*r*r+ _get_file_idUs rLc@s^eZdZdZdZddeeefdeddfdd Z d e fd d Z d e fd dZ de fddZ dS) VoxCeleb1a"*VoxCeleb1* :cite:`nagrani2017voxceleb` dataset. Args: root (str or Path): Path to the directory where the dataset is found or downloaded. download (bool, optional): Whether to download the dataset if it is not found at root path. (Default: ``False``). z.wavFrdownloadr.NcCsNt|}tj|d|_tj|js%|std|jdt|dSdS)NwavzDataset not found at z5. Please set `download=True` to download the dataset.)rfspathrr_pathisdir RuntimeErrorr,)selfrrNr*r*r+__init__gs   zVoxCeleb1.__init__ncCtNNotImplementedErrorrTrVr*r*r+ get_metadatarzVoxCeleb1.get_metadatacCrWrXrYr[r*r*r+ __getitem__ur]zVoxCeleb1.__getitem__cCrWrXrYrTr*r*r+__len__xr]zVoxCeleb1.__len__)F)__name__ __module__ __qualname____doc__rBrstrrboolrUr5r\r^r`r*r*r*r+rM\s  rMc seZdZdZdedfdeeefdedededd f fd d Z d e de ee e effd dZ d e de e e e effddZde fddZZS)VoxCeleb1Identificationu*VoxCeleb1* :cite:`nagrani2017voxceleb` dataset for speaker identification task. Each data sample contains the waveform, sample rate, speaker id, and the file id. Args: root (str or Path): Path to the directory where the dataset is found or downloaded. subset (str, optional): Subset of the dataset to use. Options: ["train", "dev", "test"]. (Default: ``"train"``) meta_url (str, optional): The url of meta file that contains the list of subset labels and file paths. The format of each row is ``subset file_path". For example: ``1 id10006/nLEBBc9oIFs/00003.wav``. ``1``, ``2``, ``3`` mean ``train``, ``dev``, and ``test`` subest, respectively. (Default: ``"https://www.robots.ox.ac.uk/~vgg/data/voxceleb/meta/iden_split.txt"``) download (bool, optional): Whether to download the dataset if it is not found at root path. (Default: ``False``). Note: The file structure of `VoxCeleb1Identification` dataset is as follows: └─ root/ └─ wav/ └─ speaker_id folders Users who pre-downloaded the ``"vox1_dev_wav.zip"`` and ``"vox1_test_wav.zip"`` files need to move the extracted files into the same ``root`` directory. r/Frr-meta_urlrNr.Ncs^t|||dvrtdtj|tj|}tj|s%t||t |j |||_ dS)N)r/rrz0`subset` must be one of ['train', 'dev', 'test']) superrU ValueErrorrrrr"existsrr<rQ_flist)rTrr-rhrNmeta_list_path __class__r*r+rUs  z VoxCeleb1Identification.__init__rVcCs@|j|}t||j}|dd}t|dd}|t||fS)aGet metadata for the n-th sample from the dataset. Returns filepath instead of waveform, but otherwise returns the same fields as :py:func:`__getitem__`. Args: n (int): The index of the sample Returns: Tuple of the following items; str: Path to audio int: Sample rate int: Speaker ID str: File ID rFrr2N)rlrLrBr4r5 SAMPLE_RATE)rTrVr(rKrHr*r*r+r\s   z$VoxCeleb1Identification.get_metadatacCs2||}t|j|d|d}|f|ddS)adLoad the n-th sample from the dataset. Args: n (int): The index of the sample to be loaded Returns: Tuple of the following items; Tensor: Waveform int: Sample rate int: Speaker ID str: File ID rr0Nr\r rQ)rTrVmetadatawaveformr*r*r+r^s z#VoxCeleb1Identification.__getitem__cC t|jSrXlenrlr_r*r*r+r` zVoxCeleb1Identification.__len__)rarbrcrd_IDEN_SPLIT_URLrrerrfrUr5rr\rr^r` __classcell__r*r*rnr+rg|s"  rgc seZdZdZedfdeeefdededdffdd Z d e de eee e eeffd d Z d e de e e e e eeffd dZde fddZZS)VoxCeleb1Verificationu*VoxCeleb1* :cite:`nagrani2017voxceleb` dataset for speaker verification task. Each data sample contains a pair of waveforms, sample rate, the label indicating if they are from the same speaker, and the file ids. Args: root (str or Path): Path to the directory where the dataset is found or downloaded. meta_url (str, optional): The url of meta file that contains a list of utterance pairs and the corresponding labels. The format of each row is ``label file_path1 file_path2". For example: ``1 id10270/x6uYqmx31kE/00001.wav id10270/8jEAjG6SegY/00008.wav``. ``1`` means the two utterances are from the same speaker, ``0`` means not. (Default: ``"https://www.robots.ox.ac.uk/~vgg/data/voxceleb/meta/veri_test.txt"``) download (bool, optional): Whether to download the dataset if it is not found at root path. (Default: ``False``). Note: The file structure of `VoxCeleb1Verification` dataset is as follows: └─ root/ └─ wav/ └─ speaker_id folders Users who pre-downloaded the ``"vox1_dev_wav.zip"`` and ``"vox1_test_wav.zip"`` files need to move the extracted files into the same ``root`` directory. FrrhrNr.NcsLt||tj|tj|}tj|st||t|j ||_ dSrX) rirUrrrr"rkrrArQrl)rTrrhrNrmrnr*r+rUs   zVoxCeleb1Verification.__init__rVcCs@|j|\}}}t|}t||j}t||j}||t|||fS)agGet metadata for the n-th sample from the dataset. Returns filepaths instead of waveforms, but otherwise returns the same fields as :py:func:`__getitem__`. Args: n (int): The index of the sample Returns: Tuple of the following items; str: Path to audio file of speaker 1 str: Path to audio file of speaker 2 int: Sample rate int: Label str: File ID of speaker 1 str: File ID of speaker 2 )rlr5rLrBrp)rTrVr>file_path_spk1file_path_spk2 file_id_spk1 file_id_spk2r*r*r+r\s   z"VoxCeleb1Verification.get_metadatacCsJ||}t|j|d|d}t|j|d|d}||f|ddS)aLoad the n-th sample from the dataset. Args: n (int): The index of the sample to be loaded. Returns: Tuple of the following items; Tensor: Waveform of speaker 1 Tensor: Waveform of speaker 2 int: Sample rate int: Label str: File ID of speaker 1 str: File ID of speaker 2 rr1r0Nrq)rTrVrr waveform_spk1 waveform_spk2r*r*r+r^s z!VoxCeleb1Verification.__getitem__cCrtrXrur_r*r*r+r`4rwzVoxCeleb1Verification.__len__)rarbrcrd_VERI_TEST_URLrrerrfrUr5rr\rr^r`ryr*r*rnr+rzs ,""rz)rpathlibrtypingrrrtorchrtorch.utils.datartorchaudio._internalrtorchaudio.datasets.utilsr r rprrxrrer,r<rArLrMrgrzr*r*r*r+s4      [