Metadata-Version: 2.1
Name: musicgen
Version: 0.0.1
Summary: A module for pre-processing steps in music generation
Home-page: https://github.com/ranjith-ms
Author: Ranjith M S
Author-email: ranjithms523@gmail.com
License: MIT
Download-URL: https://github.com/ranjith-ms/musicgen/archive/v0.1.tar.gz
Description: ï»¿# musicgen
        musicgen is a module for pre-processing audio and to prepare the dataset for neural networks in genarating music. Built on top of Music21 and youtube_dl
        ### Features
          - Download the songs,videos from URL
          - Get the notes from music
          - Prepare the dataset for neural networks
        
        ### Installation
        
        
        
        ```sh
        $ pip install musicgen
        ```
        #### get_notes(path='*.mid')
        Get all the notes and chords from the midi files  
        ##### Args:  
        path : path for the song with midi extension. â€˜*.midâ€™ by default which gets the note of all the songs in the current working directory.  
        ##### Returns:  
        List of notes obtained from the midi file   
        #### download_song_with_url(url,audio_type='mp3',quality='192')
        Downloads the audio of a video present in the given video URL to current working directory.  
        ##### Args:   
        url : (string)  URL of a video  
        audio_type :(string)"aac", "flac", "mp3", "m4a", "opus", "vorbis", or "wav". â€˜mp3â€™ by default  
        #### create_midi(prediction_output,name='output')
        convert the output from the prediction to notes and create a midi file from the notes in current working directory.  
        ##### Args:   
        prediction_output : the output predictions of a trained model.  
        name : (string) name of the generated file. output by default.  
        #### prepare_sequences(notes, n_vocab,sequence_length = 100)
        Prepare the sequences used by the Neural Network  
        ##### Args:  
        notes : (list) notes of midi file   
        n_vocab : (int) number of unique notes  
        sequence_length : (int) number of time steps required. 100 by default.  
        ##### Returns:  
        network_input, network_output   
        
        #### download_video_with_url(url)
        Downloads the video from the given URL into current working directory.  
        ##### Args:  
        url : (string)  URL of a video  
        
        #### download_videos(path)
        Downloads the videos from the URLâ€™s present in a text file into current working directory.  
        ##### Args:  
        path : (string)  path of a text file containing URLâ€™s  
        
        #### download_songs(path)
        Downloads the audio of videos from the URLâ€™s present in a text file into current working directory.  
        ##### Args:  
        path : (string)  path of a text file containing URLâ€™s.  
        
        #### song_notes_to_pickle(path,output)
        saves the notes of a midi file as a pickle object.  
        ##### Args:  
        path : (string) path  of the songs    
        output : (string) name of the pickle file.  
        
        #### generate_notes(model, network_input, pitchnames, n_vocab)
        generates the notes from the trained keras model  
        ##### Args:  
        model : Trained keras model for prediction  
        network_input : input to the network  
        pitchnames : set of items in the notes. It is found using pitchnames = sorted(set(item for item in notes))  
        n_vocab : (int) number of unique notes  
        ##### Returns:  
        predicted_output  
        
        
        
        
        
        
Keywords: LSTM,Sequence models,RNN,Neural network,Music generation
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
