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
Self-driving car env with PPO algorithm from stable baseline3

Self-driving car with RL stable baseline3 Most of the project develop from https://github.com/GerardMaggiolino/Gym-Medium-Post Please check it out! Th

Sornsiri.P 7 Dec 22, 2022
Language Models Can See: Plugging Visual Controls in Text Generation

Language Models Can See: Plugging Visual Controls in Text Generation Authors: Yixuan Su, Tian Lan, Yahui Liu, Fangyu Liu, Dani Yogatama, Yan Wang, Lin

Yixuan Su 195 Dec 22, 2022
Educational 2D SLAM implementation based on ICP and Pose Graph

slam-playground Educational 2D SLAM implementation based on ICP and Pose Graph How to use: Use keyboard arrow keys to navigate robot. Press 'r' to vie

Kirill 19 Dec 17, 2022
You Only Look One-level Feature (YOLOF), CVPR2021, Detectron2

You Only Look One-level Feature (YOLOF), CVPR2021 A simple, fast, and efficient object detector without FPN. This repo provides a neat implementation

qiang chen 273 Jan 03, 2023
Pytorch Implementation for (STANet+ and STANet)

Pytorch Implementation for (STANet+ and STANet) V2-Weakly Supervised Visual-Auditory Saliency Detection with Multigranularity Perception (arxiv), pdf:

GuotaoWang 14 Nov 29, 2022
[CVPR 2019 Oral] Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation

SelectionGAN for Guided Image-to-Image Translation CVPR Paper | Extended Paper | Guided-I2I-Translation-Papers Citation If you use this code for your

Hao Tang 424 Dec 02, 2022
PPO Lagrangian in JAX

PPO Lagrangian in JAX This repository implements PPO in JAX. Implementation is tested on the safety-gym benchmark. Usage Install dependencies using th

Karush Suri 2 Sep 14, 2022
This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures using receptive field analysis (RFA) and create graph visualizations of your architecture.

ReceptiveFieldAnalysisToolbox This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures usin

84 Nov 23, 2022
Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.

Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.

zshicode 1 Nov 18, 2021
Implementation of the Point Transformer layer, in Pytorch

Point Transformer - Pytorch Implementation of the Point Transformer self-attention layer, in Pytorch. The simple circuit above seemed to have allowed

Phil Wang 501 Jan 03, 2023
Replication attempt for the Protein Folding Model

RGN2-Replica (WIP) To eventually become an unofficial working Pytorch implementation of RGN2, an state of the art model for MSA-less Protein Folding f

Eric Alcaide 36 Nov 29, 2022
Deep Compression for Dense Point Cloud Maps.

DEPOCO This repository implements the algorithms described in our paper Deep Compression for Dense Point Cloud Maps. How to get started (using Docker)

Photogrammetry & Robotics Bonn 67 Dec 06, 2022
RoboDesk A Multi-Task Reinforcement Learning Benchmark

RoboDesk A Multi-Task Reinforcement Learning Benchmark If you find this open source release useful, please reference in your paper: @misc{kannan2021ro

Google Research 66 Oct 07, 2022
Reinforcement Learning for finance

Reinforcement Learning for Finance We apply reinforcement learning for stock trading. Fetch Data Example import utils # fetch symbols from yahoo fina

Tomoaki Fujii 159 Jan 03, 2023
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!

Robust Video Matting (RVM) English | 中文 Official repository for the paper Robust High-Resolution Video Matting with Temporal Guidance. RVM is specific

flow-dev 2 Aug 21, 2022
Official implementation of "Generating 3D Molecules for Target Protein Binding"

Generating 3D Molecules for Target Protein Binding This is the official implementation of the GraphBP method proposed in the following paper. Meng Liu

DIVE Lab, Texas A&M University 74 Dec 07, 2022
Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018)

CDAN Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018) New version: https://github.com/thuml/Transfer-Learning-Library Dataset

THUML @ Tsinghua University 363 Dec 20, 2022
WHENet - ONNX, OpenVINO, TFLite, TensorRT, EdgeTPU, CoreML, TFJS, YOLOv4/YOLOv4-tiny-3L

HeadPoseEstimation-WHENet-yolov4-onnx-openvino ONNX, OpenVINO, TFLite, TensorRT, EdgeTPU, CoreML, TFJS, YOLOv4/YOLOv4-tiny-3L 1. Usage $ git clone htt

Katsuya Hyodo 49 Sep 21, 2022
百度2021年语言与智能技术竞赛机器阅读理解Pytorch版baseline

项目说明: 百度2021年语言与智能技术竞赛机器阅读理解Pytorch版baseline 比赛链接:https://aistudio.baidu.com/aistudio/competition/detail/66?isFromLuge=true 官方的baseline版本是基于paddlepadd

周俊贤 54 Nov 23, 2022
OREO: Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning (NeurIPS 2021)

OREO: Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning (NeurIPS 2021) Video demo We here provide a video demo from co

20 Nov 25, 2022