Deep Raaga Project Description

DeepRaaga is aimed to teach & train AI with Indian classical music and to generate classical ragas ,and to see how AI having fun with Carnatic music.

Tools </br>

Following are the proposed steps

1. Environment Setup

Includes package installation for sequence synthesis. May take a few minutes.

• with Docker ?? (TBD)

2. Building your Dataset

use convert_dir_to_note_sequences.py link

Converts music files to NoteSequence protos and writes TFRecord file. Currently supports MIDI (.mid, .midi) and MusicXML (.xml, .mxl) files.
Example usage: </br> ‘ $ python magenta/scripts/convert_dir_to_note_sequences.py \ –input_dir=/path/to/input/dir \ –output_file=/path/to/tfrecord/file \ –log=INFO ‘

3. Train your model and evaluate

4. Generating performance

5. UI screens and presentation

6. ineracting with trained model

7. Building API interface for the trained model

Refer Wiki page for more details

• Wiki