https://github.com/cursedprograms/gennhausser

Music generation using a Long Short-Term Memory (LSTM) neural network. The gennhausser project uses TensorFlow and music21 libraries to create a synthetic dataset, train an LSTM model, and generate music sequences.
https://github.com/cursedprograms/gennhausser

ai ltsm ltsm-model midi music-generation music-generation-deep-learning neural-network neural-networks python python3 tensorflow

Last synced: about 1 month ago
JSON representation

Music generation using a Long Short-Term Memory (LSTM) neural network. The gennhausser project uses TensorFlow and music21 libraries to create a synthetic dataset, train an LSTM model, and generate music sequences.

• Host: GitHub
• URL: https://github.com/cursedprograms/gennhausser
• Owner: CursedPrograms
• License: mit
• Created: 2024-02-10T22:14:13.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2024-10-20T22:39:21.000Z (3 months ago)
• Last Synced: 2024-10-22T02:33:07.630Z (3 months ago)
• Topics: ai, ltsm, ltsm-model, midi, music-generation, music-generation-deep-learning, neural-network, neural-networks, python, python3, tensorflow
• Language: Python
• Homepage: https://cursedprograms.github.io/gennhausser-pr/
• Size: 4.39 MB
• Stars: 6
• Watchers: 2
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
[![Twitter: @NorowaretaGemu](https://img.shields.io/badge/[email protected]?style=flat)](https://x.com/NorowaretaGemu)

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

  

  




  

    

  



  




  





    

    



  






    





  


  

The gennhausser project is for music generation using a Long Short-Term Memory (LSTM) neural network. The gennhausser project uses TensorFlow and music21 libraries to create a synthetic dataset, train an LSTM model, and generate MIDI sequences.


  


## Scripts:

- **main.py:** The selection menu for gennhuasser

- **app.py:** Run gennhuasser as a web-server

### /scripts/

- **trainer.py:** Runs gennhuasser trainer

- **install_dependencies.py:** Install dependencies





    





## How to Run:

### Install Requirements

Using Python directly:

```bash

pip install -r requirements.txt

```

Or run: 

- `install_requirements.bat`

  

  


### Run main.py

Using Python directly:

```bash

python main.py

```

Using provided scripts:

Windows:

- `.\run.bat`

or

- `.\run.ps1`

Unix-like systems (Linux/macOS):

- `.\run.sh`