Audio Classification Features
It is made to extract the features from any audio dataset. User's have to provide location of the dataset folder and this library will produce x and y npy files. We also provide custom built Keras model for training.
Installation
$ pip install audio_classification_features
Usage
Making Training Dataset
from audio_classification_features import audio_features as af
af().extractor('dataset')
These npy files are loaded with numpy using following commands:
import numpy
x=np.load('x.npy')
y=np.load('y.npy')
Training Custom Built Model
#input_shape generated by this package is of shape (9,13,1)
input_shape=(9,13,1)
Making Predictions
from audio_classification_features import audio_features as af
#filename example: audio_test.wav
#num_classes same as above
#model
af().make_prediction(filename,num_classes,model)
Dataset Structure
folder name of audio will be used as label.
- dataset
- audio class 1
- audiofile.wav
- audio class 2
- audiofile.wav
- audio class 1
LICENSE
GNU General Public License v3.0
Release files for audio-classification-features 2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| audio_classification_features-2.0.tar.gz | 4.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| audio_classification_features-2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 21.2 kB
Release files / audio_classification_features-2.0.tar.gz
| Download URL | audio_classification_features-2.0.tar.gz |
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| Size | 4.2 kB |
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Release files / audio_classification_features-2.0-py3-none-any.whl
| Download URL | audio_classification_features-2.0-py3-none-any.whl |
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| Size | 17.0 kB |
| Tags | Python 3 |
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