SarCode / music-generation-using-GAN

Music Generation using GAN

Welcome to the "Music Generation using GAN" project! This guide will walk you through the steps to run the project successfully.

Project Structure

The project repository contains the following folders and files:

• Music_GAN: Contains the code and dataset for the project.
• Sentiment_Poetry.ipynb: Used for emotion analysis on poetry, which contributes to music generation.
• MIDI_Image.ipynb: Converts MIDI files to images for training data preparation.
• Music_GAN.ipynb: Main code file for the GAN-based music generation process.

Setup and Prerequisites

1. Clone the repository: GitHub Repository.
2. Upload the Music_GAN.ipynb file to Google Colab.

Running the Code

Follow these steps to run the main code for music generation:

1. Upload Dataset: You can use the original dataset available in the GitHub Repository. Optionally, you can upload the dataset to your Google Drive for easy access.

2. Run Music_GAN.ipynb:

   • Open the Music_GAN.ipynb notebook in Google Colab.
   • Mount your Google Drive if you've uploaded the dataset there.
   • Modify any necessary paths or configurations as mentioned in the notebook.
   • Run the cells step by step to execute the GAN-based music generation process.

Output and Results

• The output images generated from the MIDI files can be found in the lofi_png folder.
• Sample input and output files are stored in the Final_Output folder. The input, named "Sample Poem," and the corresponding output .wav files are located in the same directory.

Note

• You do not need to run Sentiment_Poetry.ipynb or MIDI_Image.ipynb as their outputs are already available.
• The original dataset and additional resources are available in the GitHub Repository.

Enjoy exploring the world of music generation using GANs!