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
Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks

Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks Setup This implementation is based on PyTorch = 1.0.0. Smal

Weilin Cong 8 Oct 28, 2022
Automatically measure the facial Width-To-Height ratio and get facial analysis results provided by Microsoft Azure

fwhr-calc-website This project is to automatically measure the facial Width-To-Height ratio and get facial analysis results provided by Microsoft Azur

SoohyunPark 1 Feb 07, 2022
PyTorch Implement of Context Encoders: Feature Learning by Inpainting

Context Encoders: Feature Learning by Inpainting This is the Pytorch implement of CVPR 2016 paper on Context Encoders 1) Semantic Inpainting Demo Inst

321 Dec 25, 2022
Experiments for distributed optimization algorithms

Network-Distributed Algorithm Experiments -- This repository contains a set of optimization algorithms and objective functions, and all code needed to

Boyue Li 40 Dec 04, 2022
Toolbox to analyze temporal context invariance of deep neural networks

PyTCI A toolbox that estimates the integration window of a sensory response using the "Temporal Context Invariance" paradigm (TCI). The TCI method Int

4 Oct 23, 2022
A simple approach to emable dense segmentation with ViT.

Vision Transformer Segmentation Network This implementation of ViT in pytorch uses a super simple and straight-forward way of generating an output of

HReynaud 5 Jan 03, 2023
The official repository for our paper "The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization".

Codebase for learning control flow in transformers The official repository for our paper "The Neural Data Router: Adaptive Control Flow in Transformer

Csordás Róbert 24 Oct 15, 2022
Paper Code:A Self-adaptive Weighted Differential Evolution Approach for Large-scale Feature Selection

1. SaWDE.m is the main function 2. DataPartition.m is used to randomly partition the original data into training sets and test sets with a ratio of 7

wangxb 14 Dec 08, 2022
Supporting code for short YouTube series Neural Networks Demystified.

Neural Networks Demystified Supporting iPython notebooks for the YouTube Series Neural Networks Demystified. I've included formulas, code, and the tex

Stephen 1.3k Dec 23, 2022
ShuttleNet: Position-aware Fusion of Rally Progress and Player Styles for Stroke Forecasting in Badminton (AAAI 2022)

ShuttleNet: Position-aware Rally Progress and Player Styles Fusion for Stroke Forecasting in Badminton (AAAI 2022) Official code of the paper ShuttleN

Wei-Yao Wang 11 Nov 30, 2022
PyTorch Implementation of AnimeGANv2

PyTorch implementation of AnimeGANv2

4k Jan 07, 2023
OpenMMLab Image and Video Editing Toolbox

Introduction MMEditing is an open source image and video editing toolbox based on PyTorch. It is a part of the OpenMMLab project. The master branch wo

OpenMMLab 3.9k Jan 04, 2023
Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet

Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet, CVPR2021 安全AI挑战者计划第六期:ImageNet无限制对抗攻击 决赛第四名(team name: Advers)

51 Dec 01, 2022
ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.

ManimML ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.

259 Jan 04, 2023
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search

DropNAS: Grouped Operation Dropout for Differentiable Architecture Search DropNAS, a grouped operation dropout method for one-level DARTS, with better

weijunhong 4 Aug 15, 2022
PyTorch implementation of: Michieli U. and Zanuttigh P., "Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations", CVPR 2021.

Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations This is the official PyTorch implementation

Multimedia Technology and Telecommunication Lab 42 Nov 09, 2022
Real-time VIBE: Frame by Frame Inference of VIBE (Video Inference for Human Body Pose and Shape Estimation)

Real-time VIBE Inference VIBE frame-by-frame. Overview This is a frame-by-frame inference fork of VIBE at [https://github.com/mkocabas/VIBE]. Usage: i

23 Jul 02, 2022
Alphabetical Letter Recognition

DecisionTrees-Image-Classification Alphabetical Letter Recognition In these demo we are using "Decision Trees" Our database is composed by Learning Im

Mohammed Firass 4 Nov 30, 2021
Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing

Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing Paper Introduction Multi-task indoor scene understanding is widely considered a

62 Dec 05, 2022
Official implementation for "Symbolic Learning to Optimize: Towards Interpretability and Scalability"

Symbolic Learning to Optimize This is the official implementation for ICLR-2022 paper "Symbolic Learning to Optimize: Towards Interpretability and Sca

VITA 8 Dec 19, 2022