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AudClas

Package that uses audio classification model extracted from neonbjb/DL-Art-School - for filtering fine audio files.

Classes

Classifier model returns one of 6 possible labels:

label class name
0 fine
1 env_noise
2 music
3 two_voices
4 reverb
- unknown

Installation

pip install audclas

examples of usage

For single audio file:

    from audclas.tortoise_audio_classifier import TortoiseAudioClassifier
    classifier = TortoiseAudioClassifier()

    label = classifier('wavs/test.wav')

    print(label)

For directory containing audio files (it searches recursively for all .wav / .mp3 files):

    from tqdm import tqdm
    from audclas.tortoise_audio_classifier import TortoiseAudioClassifier
    classifier = TortoiseAudioClassifier()

    batch_size = 32
    do_classify, total = classifier.prepare_classify_dir_job('/content/wavs', batch_size)

    fine_audio_paths = []

    for result in tqdm(do_classify(), total=total):
        for audio_path, audio_label in result:
            if audio_label == 'fine':
                fine_audio_paths.append(audio_path)

    print(f'directory contains {len(fine_audio_paths)} fine files (total files: {total * batch_size})')

Metadata

Release files for audclas 0.0.6

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Source distribution for audclas 0.0.6
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Table of built distributions (wheels) for audclas 0.0.6
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audclas-0.0.6-py3-none-any.whl Python 3 none any Details

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