Metadata-Version: 2.1
Name: musicnn_keras
Version: 0.1.0
Summary: Pronounced as "musician", musicnn is a set of pre-trained deep convolutional neural networks for music audio tagging. Musicnn_keras is a tf.keras implementation of musicnn
Home-page: https://github.com/Quint-e/musicnn_keras
Author: Elio Quinton
License: ISC
Description: # musicnn_keras
        `Musicnn_keras` is a tf.keras implementation of [musicnn](https://github.com/jordipons/musicnn), originally written in "pure" TensorFlow. 
        `Musicnn_keras` is aimed at making musicnn accessible via the popular tf.keras interface. 
        
        
        Pronounced as "musician", `musicnn` is a set of pre-trained musically motivated convolutional neural networks for music audio tagging. This repository also includes some pre-trained [vgg-like](https://github.com/Quint-e/musicnn_keras/blob/master/vgg_example.ipynb) baselines.
        
        Check the [documentation](https://github.com/Quint-e/musicnn_keras/blob/master/DOCUMENTATION.md) and our [basic](https://github.com/Quint-e/musicnn_keras/blob/master/tagging_example.ipynb) / [advanced](https://github.com/Quint-e/musicnn_keras/blob/master/musicnn_example.ipynb) examples to understand how to use `musicnn`.
        
        Do you have questions? Check the [FAQs](https://github.com/Quint-e/musicnn_keras/blob/master/FAQs.md).
        
        
        ## Installation
        
        `pip install musicnn_keras`
        
        
        Or clone the repository and install from source: 
        
        ``` git clone https://github.com/Quint-e/musicnn_keras/musicnn_keras.git```
        
        ``` python setup.py install```
        
        Dependencies:  `Tensorflow>=2.0`, `librosa>=0.7.0` and `numpy<1.17,>=1.14.5`. 
        
        ## Load pre-trained models
        Loading pre-trained model is simply achieved by using the dedicated tf.keras API: 
        
        ~~~~python
        import tensorflow as tf
        musicnn = tf.keras.models.load_model('./musicnn_keras/keras_checkpoints/MSD_musicnn.h5')
        ~~~~
        
        `musicnn` can then be used like any other keras model. 
        
        Note that if you are only interested in loading the pre-trained models in your code, you do not need to install the `musicnn_keras` package. `tf.keras.models.load_model` is sufficient. 
        
        ## Predict tags
        
        From within **python**, you can estimate the topN tags:
        ~~~~python
        from musicnn_keras.tagger import top_tags
        top_tags('./audio/joram-moments_of_clarity-08-solipsism-59-88.mp3', model='MTT_musicnn', topN=10)
        ~~~~
        >['techno', 'electronic', 'synth', 'fast', 'beat', 'drums', 'no vocals', 'no vocal', 'dance', 'beats']
        
        Let's try another song!
        
        ~~~~python
        top_tags('./audio/TRWJAZW128F42760DD_test.mp3')
        ~~~~
        >['guitar', 'piano', 'fast']
        
        From the **command-line**, you can also print the topN tags on the screen:
        
        ~~~~
        python -m musicnn_keras.tagger file_name.ogg --print
        python -m musicnn_keras.tagger file_name.au --model 'MSD_musicnn' --topN 3 --length 3 --overlap 1.5 --print
        ~~~~~
        
        or save to a file:
        
        ~~~~
        python -m musicnn_keras.tagger file_name.wav --save out.tags
        python -m musicnn_keras.tagger file_name.mp3 --model 'MTT_musicnn' --topN 10 --length 3 --overlap 1 --print --save out.tags
        ~~~~
        
        ## Extract the Taggram
        
        You can also compute the taggram using **python** (see our [basic](https://github.com/Quint-e/musicnn_keras/blob/master/tagging_example.ipynb) example for more details on how to depict it):
        
        ~~~~python
        from musicnn_keras.extractor import extractor
        taggram, tags = extractor('./audio/joram-moments_of_clarity-08-solipsism-59-88.mp3', model='MTT_musicnn')
        ~~~~
        ![Taggram](./images/taggram.png "Taggram")
        
        The above analyzed music clips are included in the `./audio/` folder of this repository. 
        
        
        
        ## musicnn_keras and musicnn
        This repo mirrors the contents of the original musicnn repository, adapted to tf.keras. As a result, some of the code and examples used in this repository came from the [original musicnn repo](https://github.com/jordipons/musicnn). 
        
Keywords: audio music deep learning tagging tensorflow keras machine listening
Platform: UNKNOWN
Classifier: License :: OSI Approved :: ISC License (ISCL)
Classifier: Programming Language :: Python
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Multimedia :: Sound/Audio :: Analysis
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
