Metadata-Version: 2.1
Name: spela
Version: 0.0.2
Summary: spectrogram layers
Home-page: https://github.com/kongkip/spela.git
Author: Evans Kiplagat
Author-email: evanskiplagat3@gmail.com
License: MIT
Description: # SPELA - spectrogram layers
        Rewrote [kapre](https://github.com/kongkip/kapre#installation) using tensorflow.keras \
        credits go to Keunwoo Choi for writing kapre
        
        My main goal for rewriting it with tensorflow.keras is to use it with TensorFlow Lite \
        since Keunwoo Choi used core keras and I had problems converting the model to \
        tensorflow lite.
        
        Implementing audio features inside the keras layers allows the preprocessing \
        computations to be done on the GPU as highlighted in their [paper](https://arxiv.org/abs/1706.05781)
        
        # Installation
        The package uses tensorflow but is not listed as requirement, please install it.
        ```bash
        pip install spela
        ```
        or
        ```bash
        git clone https://github.com/kongkip/spela.git
        cd spela
        python setup.py install
        ```
        
        # Usage
        ## spectrogram
        ```python
        import tensorflow as tf
        from spela.spectrogram import Spectrogram
        
        # a one channel audio with 16000 sample rate
        input_shape = (1, 16000)
        
        x = get_data()
        y = get_data()
        
        
        model = tf.keras.Sequential()
        model.add(Spectrogram(n_dft=512, n_hop=256, input_shape=(input_shape),
                              return_decibel_spectrogram=True, power_spectrogram=2.0,
                              trainable_kernel=False, name='static_stft'))
        
        model.compile(optimizer=tf.keras.optimizers.Adam(lr=0.001), loss=tf.keras.losses.categorical_crossentropy
                      , metrics=["acc"])
        
        print(model.summary())
        
        model.fit(x,y)
        ```
        
        ## Mel Spectrogram
        ```python
        import tensorflow as tf
        from spela.melspectrogram import Melspectrogram
        
        # a one channel audio with 16000 sample rate
        input_shape = (1, 16000)
        
        x = get_data()
        y = get_data()
        
        model = tf.keras.Sequential()
        model.add(Melspectrogram(sr=SR, n_mels=128,
                  n_dft=512, n_hop=256, input_shape=input_shape,
                  return_decibel_melgram=True,
                  trainable_kernel=False, name='melgram'))
        
        model.compile(optimizer=tf.keras.optimizers.Adam(lr=0.001), loss=tf.keras.losses.categorical_crossentropy
                      , metrics=["acc"])
        
        print(model.summary())
        
        model.fit(x,y)
        ```
        
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