A practically universal music pre-processor
Project description
pumpp
practically universal music pre-processor
pumpp up the jams
The goal of this package is to make it easy to convert pairs of (audio, jams) into data that can
be easily consumed by statistical algorithms. Some desired features:
- Converting tags to sparse encoding vectors
- Sampling
(start, end, label)to frame-level annotations at a specific frame rate - Extracting input features (eg, Mel spectra or CQT) from audio
- Converting between annotation spaces for a given task
Example usage
>>> import jams
>>> import pumpp
>>> audio_f = '/path/to/audio/myfile.ogg'
>>> jams_f = '/path/to/annotations/myfile.jamz'
>>> # Set up sampling and frame rate parameters
>>> sr, hop_length = 44100, 512
>>> # Create a feature extraction object
>>> p_cqt = pumpp.feature.CQT(name='cqt', sr=sr, hop_length=hop_length)
>>> # Create some annotation extractors
>>> p_beat = pumpp.task.BeatTransformer(sr=sr, hop_length=hop_length)
>>> p_chord = pumpp.task.SimpleChordTransformer(sr=sr, hop_length=hop_length)
>>> # Collect the operators in a pump
>>> pump = pumpp.Pump(p_cqt, p_beat, p_chord)
>>> # Apply the extractors to generate training data
>>> data = pump(audio_f=audio_f, jam=jams_fjams_f)
>>> # Or test data
>>> test_data = pump(audio_f='/my/test/audio.ogg')
>>> # Or in-memory
>>> y, sr = librosa.load(audio_f)
>>> test_data = pump(y=y, sr=sr)
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