PyTorch implementation of MuseMorphose, a Transformer-based model for music style transfer.

Overview

MuseMorphose

This repository contains the official implementation of the following paper:

  • Shih-Lun Wu, Yi-Hsuan Yang
    MuseMorphose: Full-Song and Fine-Grained Music Style Transfer with One Transformer VAE
    ArXiv preprint, May 2021 [arXiv] [demo website]

Prerequisites

  • Python >= 3.6
  • Install dependencies
pip3 install -r requirements.txt
  • GPU with >6GB RAM (optional, but recommended)

Preprocessing

# download REMI-pop-1.7K dataset
wget -O remi_dataset.tar.gz https://zenodo.org/record/4782721/files/remi_dataset.tar.gz?download=1
tar xzvf remi_dataset.tar.gz
rm remi_dataset.tar.gz

# compute attributes classes
python3 attributes.py

Training

python3 train.py [config file]
  • e.g.
python3 train.py config/default.yaml
  • Or, you may download the pretrained weights straight away
wget -O musemorphose_pretrained_weights.pt https://zenodo.org/record/5119525/files/musemorphose_pretrained_weights.pt?download=1

Generation

python3 generate.py [config file] [ckpt path] [output dir] [num pieces] [num samples per piece]
  • e.g.
python3 generate.py config/default.yaml musemorphose_pretrained_weights.pt generations/ 10 5

This script will randomly draw the specified # of pieces from the test set.
For each sample of a piece, the rhythmic intensity and polyphonicity will be shifted entirely and randomly by [-3, 3] classes for the model to generate style-transferred music.
You may modify random_shift_attr_cls() in generate.py or write your own function to set the attributes.

Customized Generation (To Be Added)

We welcome the community's suggestions and contributions for an interface on which users may

  • upload their own MIDIs, and
  • set their desired bar-level attributes easily

Citation BibTex

If you find this work helpful and use our code in your research, please kindly cite our paper:

@article{musemorphose21arxiv,
    title={{MuseMorphose}: Full-Song and Fine-Grained Music Style Transfer with One {Transformer VAE}},
    author={Shih-Lun Wu and Yi-Hsuan Yang},
    year={2021},
    journal={arXiv preprint arXiv:2105.04090},
}
Owner
Yating Music, Taiwan AI Labs
A research team working on Music AI technology at the Taiwan AI Labs, Taiwan
Yating Music, Taiwan AI Labs
[ICCV21] Code for RetrievalFuse: Neural 3D Scene Reconstruction with a Database

RetrievalFuse Paper | Project Page | Video RetrievalFuse: Neural 3D Scene Reconstruction with a Database Yawar Siddiqui, Justus Thies, Fangchang Ma, Q

Yawar Nihal Siddiqui 75 Dec 22, 2022
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and reinforcement learning

safe-control-gym Physics-based CartPole and Quadrotor Gym environments (using PyBullet) with symbolic a priori dynamics (using CasADi) for learning-ba

Dynamic Systems Lab 300 Dec 28, 2022
Generate images from texts. In Russian

ruDALL-E Generate images from texts pip install rudalle==1.1.0rc0 🤗 HF Models: ruDALL-E Malevich (XL) ruDALL-E Emojich (XL) (readme here) ruDALL-E S

AI Forever 1.6k Dec 31, 2022
This tool uses Deep Learning to help you draw and write with your hand and webcam.

This tool uses Deep Learning to help you draw and write with your hand and webcam. A Deep Learning model is used to try to predict whether you want to have 'pencil up' or 'pencil down'.

lmagne 169 Dec 10, 2022
Official implementation of NLOS-OT: Passive Non-Line-of-Sight Imaging Using Optimal Transport (IEEE TIP, accepted)

NLOS-OT Official implementation of NLOS-OT: Passive Non-Line-of-Sight Imaging Using Optimal Transport (IEEE TIP, accepted) Description In this reposit

Ruixu Geng(耿瑞旭) 16 Dec 16, 2022
Worktory is a python library created with the single purpose of simplifying the inventory management of network automation scripts.

Worktory is a python library created with the single purpose of simplifying the inventory management of network automation scripts.

Renato Almeida de Oliveira 18 Aug 31, 2022
Official NumPy Implementation of Deep Networks from the Principle of Rate Reduction (2021)

Deep Networks from the Principle of Rate Reduction This repository is the official NumPy implementation of the paper Deep Networks from the Principle

Ryan Chan 49 Dec 16, 2022
Official code of CVPR 2021's PLOP: Learning without Forgetting for Continual Semantic Segmentation

PLOP: Learning without Forgetting for Continual Semantic Segmentation This repository contains all of our code. It is a modified version of Cermelli e

Arthur Douillard 116 Dec 14, 2022
Machine Learning Privacy Meter: A tool to quantify the privacy risks of machine learning models with respect to inference attacks, notably membership inference attacks

ML Privacy Meter Machine learning is playing a central role in automated decision making in a wide range of organization and service providers. The da

Data Privacy and Trustworthy Machine Learning Research Lab 357 Jan 06, 2023
social humanoid robots with GPGPU and IoT

Social humanoid robots with GPGPU and IoT Social humanoid robots with GPGPU and IoT Paper Authors Mohsen Jafarzadeh, Stephen Brooks, Shimeng Yu, Balak

0 Jan 07, 2022
Get a Grip! - A robotic system for remote clinical environments.

Get a Grip! Within clinical environments, sterilization is an essential procedure for disinfecting surgical and medical instruments. For our engineeri

Jay Sharma 1 Jan 05, 2022
Official page of Patchwork (RA-L'21 w/ IROS'21)

Patchwork Official page of "Patchwork: Concentric Zone-based Region-wise Ground Segmentation with Ground Likelihood Estimation Using a 3D LiDAR Sensor

Hyungtae Lim 254 Jan 05, 2023
Energy consumption estimation utilities for Jetson-based platforms

This repository contains a utility for measuring energy consumption when running various programs in NVIDIA Jetson-based platforms. Currently TX-2, NX, and AGX are supported.

OpenDR 10 Jun 17, 2022
This is the pytorch implementation of the paper - Axiomatic Attribution for Deep Networks.

Integrated Gradients This is the pytorch implementation of "Axiomatic Attribution for Deep Networks". The original tensorflow version could be found h

Tianhong Dai 150 Dec 23, 2022
This is the source code for the experiments related to the paper Unsupervised Audio Source Separation Using Differentiable Parametric Source Models

Unsupervised Audio Source Separation Using Differentiable Parametric Source Models This is the source code for the experiments related to the paper Un

30 Oct 19, 2022
ExCon: Explanation-driven Supervised Contrastive Learning

ExCon: Explanation-driven Supervised Contrastive Learning Link to the paper: https://arxiv.org/pdf/2111.14271.pdf Contributors of this repo: Zhibo Zha

Zhibo (Darren) Zhang 18 Nov 01, 2022
Contrastive Learning Inverts the Data Generating Process

Official code to reproduce the results and data presented in the paper Contrastive Learning Inverts the Data Generating Process.

71 Nov 25, 2022
Tweesent-back - Tweesent backend uses fastAPI as the web framework

TweeSent Backend Tweesent backend. This repo uses fastAPI as the web framework.

0 Mar 26, 2022
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models

Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor

Li Yang 1.1k Dec 19, 2022
Official Implementation of "Transformers Can Do Bayesian Inference"

Official Code for the Paper "Transformers Can Do Bayesian Inference" We train Transformers to do Bayesian Prediction on novel datasets for a large var

AutoML-Freiburg-Hannover 103 Dec 25, 2022