Metadata-Version: 2.1
Name: AudioFeaturizer
Version: 1.0.0
Summary: Takes audio as input and returns computed features as a dataframe
Home-page: https://github.com/N-Harish/AudioFeaturizer
Author: Harish-Natarajan
Author-email: harishnatarajan24@gmail.com
License: MIT
Description: # AudioFeaturizer
        
        AudioFeaturizer is a python package that uses librosa under the hood and extracts features from audio and returns it into a pandas dataframe. 
        It also has a spectrogram generation function which generates spectrogram of the audio file path which is passed. 
        
        
        ## Installation
        
        You can install the AudioFeaturizer from [PyPI](https://pypi.org/project/AudioFeaturizer/):
        
            pip install AudioFeaturizer
        
        The reader is supported on Python 3.7 and above.
        
        
        ## How to Use
        
        For extracting features
        ```>>> from audio_feature.audio_featurizer import *
        >>> audio_process(r'D:\PYTHON_FILES\audio-ml\genres\classical\classical.00000.wav')
           chroma_stft      rmse  spectral_centroid  spectral_bandwidth  ...    mfcc17    mfcc18    mfcc19    mfcc20
        0     0.252391  0.036255        1505.299012         1558.952849  ... -0.303796  1.778557  0.890328 -0.837884
        
        [1 rows x 26 columns]
        >>>
        ```
        
        for displaying spectrogram
        ```
        from audio_feature.audio_featurizer import *
        
        spectrogram_plot(r'D:\PYTHON_FILES\audio-ml\genres\classical\classical.00000.wav')
        ```
        
        ![Output](https://github.com/N-Harish/AudioFeaturizer/blob/master/Figure_1.png)
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.7
Description-Content-Type: text/markdown
