Time-stretch audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.

Related tags

Deep Learningtorch-time-stretch
Overview

Torch Time Stretch

Time-stretch audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.

View on PyPI / View Documentation

Publish to PyPI Run tests PyPI version Number of downloads from PyPI per month Python version support Code Style: Black

About

This package includes two main features:

  • Time-stretch audio clips quickly using PyTorch (with CUDA support)
  • Calculate efficient time-stretch targets (useful for augmentation, where speed is more important than precise time-stretches)

Also check out torch-pitch-shift, a sister project for pitch-shifting.

Installation

pip install torch-time-stretch

Usage

Example

Check out example.py to see torch-time-stretch in action!

Documentation

See the documentation page for detailed documentation!

Contributing

Please feel free to submit issues or pull requests!

You might also like...
Additional code for Stable-baselines3 to load and upload models from the Hub.

Hugging Face x Stable-baselines3 A library to load and upload Stable-baselines3 models from the Hub. Installation With pip Examples [Todo: add colab t

Hugging Face 34 Dec 10, 2022
BYOL for Audio: Self-Supervised Learning for General-Purpose Audio Representation
BYOL for Audio: Self-Supervised Learning for General-Purpose Audio Representation

BYOL for Audio: Self-Supervised Learning for General-Purpose Audio Representation This is a demo implementation of BYOL for Audio (BYOL-A), a self-sup

NTT Communication Science Laboratories 160 Jan 4, 2023
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

JAX: Autograd and XLA Quickstart | Transformations | Install guide | Neural net libraries | Change logs | Reference docs | Code search News: JAX tops

Google 21.3k Jan 1, 2023
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

JAX: Autograd and XLA Quickstart | Transformations | Install guide | Neural net libraries | Change logs | Reference docs | Code search News: JAX tops

Google 11.4k Feb 13, 2021
Extending JAX with custom C++ and CUDA code

Extending JAX with custom C++ and CUDA code This repository is meant as a tutorial demonstrating the infrastructure required to provide custom ops in

Dan Foreman-Mackey 237 Dec 23, 2022
Several simple examples for popular neural network toolkits calling custom CUDA operators.
Several simple examples for popular neural network toolkits calling custom CUDA operators.

Neural Network CUDA Example Several simple examples for neural network toolkits (PyTorch, TensorFlow, etc.) calling custom CUDA operators. We provide

WeiYang 798 Jan 1, 2023
Picasso: A CUDA-based Library for Deep Learning over 3D Meshes

The Picasso Library is intended for complex real-world applications with large-scale surfaces, while it also performs impressively on the small-scale applications over synthetic shape manifolds. We have upgraded the point cloud modules of SPH3D-GCN from homogeneous to heterogeneous representations, and included the upgraded modules into this latest work as well. We are happy to announce that the work is accepted to IEEE CVPR2021.

null 97 Dec 1, 2022
Code for "Learning Structural Edits via Incremental Tree Transformations" (ICLR'21)

Learning Structural Edits via Incremental Tree Transformations Code for "Learning Structural Edits via Incremental Tree Transformations" (ICLR'21) 1.

NeuLab 40 Dec 23, 2022
This Repo is the official CUDA implementation of ICCV 2019 Oral paper for CARAFE: Content-Aware ReAssembly of FEatures

Introduction This Repo is the official CUDA implementation of ICCV 2019 Oral paper for CARAFE: Content-Aware ReAssembly of FEatures. @inproceedings{Wa

Jiaqi Wang 42 Jan 7, 2023
Comments
  • RuntimeError: The size of tensor a (40264) must match the size of tensor b (173) at non-singleton dimension 1

    RuntimeError: The size of tensor a (40264) must match the size of tensor b (173) at non-singleton dimension 1

    I use same code in https://github.com/KentoNishi/torch-time-stretch/blob/master/example.py but get below error

    (librosa) ➜  torch-time-stretch git:(master) ✗ python example.py 
Traceback (most recent call last):
  File "/home/jackie/code/github/torch-time-stretch/example.py", line 48, in <module>
    test_time_stretch_2_up()
  File "/home/jackie/code/github/torch-time-stretch/example.py", line 20, in test_time_stretch_2_up
    up = time_stretch(sample, Fraction(1, 2), SAMPLE_RATE)
  File "/home/jackie/code/github/torch-time-stretch/torch_time_stretch/main.py", line 116, in time_stretch
    output = stretcher(output)
  File "/home/jackie/anaconda3/envs/librosa/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/jackie/anaconda3/envs/librosa/lib/python3.9/site-packages/torchaudio/transforms/_transforms.py", line 1059, in forward
    return F.phase_vocoder(complex_specgrams, rate, self.phase_advance)
  File "/home/jackie/anaconda3/envs/librosa/lib/python3.9/site-packages/torchaudio/functional/functional.py", line 743, in phase_vocoder
    phase = angle_1 - angle_0 - phase_advance
RuntimeError: The size of tensor a (40264) must match the size of tensor b (173) at non-singleton dimension 1
    opened by Jackiexiao 4
  • Example ratios are reversed.

    Example ratios are reversed.

    Love it, thanks for making this! Tiny thing: In the example test_time_stretch_2_up should use 1/2 as a ratio, not 2/1. test_time_stretch_2_down should use that 2/1 (it's stretching the clip length by 2x).

    opened by hdemmer 1
  • Does it with mono-channel wav files?

    Does it with mono-channel wav files?

    my audio clip is in mono 16khz audio, [ 0 0 0 ... 63 100 127], so it will throw

    ---> 15 down = time_stretch(sample, Fraction(2, 1), SAMPLE_RATE)
     16 wavfile.write(
     17     "./stretched_down_2.wav",
     18     SAMPLE_RATE,
     19     np.swapaxes(down.cpu()[0].numpy(), 0, 0).astype(dtype),
     20 )

File /opt/conda/envs/classify-audio/lib/python3.9/site-packages/torch_time_stretch/main.py:108, in time_stretch(input, stretch, sample_rate, n_fft, hop_length)
    106 if not hop_length:
    107     hop_length = n_fft // 32
--> 108 batch_size, channels, samples = input.shape
    109 # resampler = T.Resample(sample_rate, int(sample_rate / stretch)).to(input.device)
    110 output = input

ValueError: not enough values to unpack (expected 3, got 2)
    opened by ti3x 0
Releases(v1.0.3)
Owner
Kento Nishi
17-year-old programmer at Lynbrook High School, with strong interests in AI/Machine Learning. Open source developer and researcher at the Four Eyes Lab.
Kento Nishi
GitHub Repository
A simple and useful implementation of LPIPS.

lpips-pytorch Description Developing perceptual distance metrics is a major topic in recent image processing problems. LPIPS[1] is a state-of-the-art

So Uchida 121 Dec 24, 2022
pyspark🍒🥭 is delicious，just eat it!😋😋

如何用10天吃掉pyspark？ 🔥 🔥 《10天吃掉那只pyspark》 🚀

lyhue1991 578 Dec 30, 2022
Implementation of our recent paper, WOOD: Wasserstein-based Out-of-Distribution Detection.

WOOD Implementation of our recent paper, WOOD: Wasserstein-based Out-of-Distribution Detection. Abstract The training and test data for deep-neural-ne

8 Dec 24, 2022
Start-to-finish tutorial for interactive music co-creation in PyTorch and Tensorflow.js

Start-to-finish tutorial for interactive music co-creation in PyTorch and Tensorflow.js

Chris Donahue 98 Dec 14, 2022
HiddenMarkovModel implements hidden Markov models with Gaussian mixtures as distributions on top of TensorFlow

Class HiddenMarkovModel HiddenMarkovModel implements hidden Markov models with Gaussian mixtures as distributions on top of TensorFlow 2.0 Installatio

Susara Thenuwara 2 Nov 03, 2021
Implementation of Diverse Semantic Image Synthesis via Probability Distribution Modeling

Diverse Semantic Image Synthesis via Probability Distribution Modeling (CVPR 2021) Paper Zhentao Tan, Menglei Chai, Dongdong Chen, Jing Liao, Qi Chu,

tzt 45 Nov 17, 2022
Fast and Context-Aware Framework for Space-Time Video Super-Resolution (VCIP 2021)

Fast and Context-Aware Framework for Space-Time Video Super-Resolution Preparation Dependencies PyTorch 1.2.0 CUDA 10.0 DCNv2 cd model/DCNv2 bash make

Xueheng Zhang 1 Mar 29, 2022
CAMPARI: Camera-Aware Decomposed Generative Neural Radiance Fields

CAMPARI: Camera-Aware Decomposed Generative Neural Radiance Fields Paper | Supplementary | Video | Poster If you find our code or paper useful, please

26 Nov 29, 2022
Custom TensorFlow2 implementations of forward and backward computation of soft-DTW algorithm in batch mode.

Batch Soft-DTW(Dynamic Time Warping) in TensorFlow2 including forward and backward computation Custom TensorFlow2 implementations of forward and backw

19 Aug 30, 2022
Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning

Machine_Learning Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning This project is based on 2 case-studies:

Avnika Mehta 1 Jan 27, 2022
Geometric Vector Perceptrons --- a rotation-equivariant GNN for learning from biomolecular structure

Geometric Vector Perceptron Implementation of equivariant GVP-GNNs as described in Learning from Protein Structure with Geometric Vector Perceptrons b

Dror Lab 142 Dec 29, 2022
Half Instance Normalization Network for Image Restoration

HINet Half Instance Normalization Network for Image Restoration, based on https://github.com/megvii-model/HINet. Dependencies NumPy PyTorch, preferabl

Holy Wu 4 Jun 06, 2022
Codes for paper "Towards Diverse Paragraph Captioning for Untrimmed Videos". CVPR 2021

Towards Diverse Paragraph Captioning for Untrimmed Videos This repository contains PyTorch implementation of our paper Towards Diverse Paragraph Capti

Yuqing Song 61 Oct 11, 2022
This repository provides an unified frameworks to train and test the state-of-the-art few-shot font generation (FFG) models.

FFG-benchmarks This repository provides an unified frameworks to train and test the state-of-the-art few-shot font generation (FFG) models. What is Fe

Clova AI Research 101 Dec 27, 2022
Neural Radiance Fields Using PyTorch

This project is a PyTorch implementation of Neural Radiance Fields (NeRF) for reproduction of results whilst running at a faster speed.

Vedant Ghodke 1 Feb 11, 2022
A deep learning network built with TensorFlow and Keras to classify gender and estimate age.

Convolutional Neural Network (CNN). This repository contains a source code of a deep learning network built with TensorFlow and Keras to classify gend

Pawel Dziemiach 1 Dec 18, 2021
A library for uncertainty quantification based on PyTorch

Torchuq [logo here] TorchUQ is an extensive library for uncertainty quantification (UQ) based on pytorch. TorchUQ currently supports 10 representation

TorchUQ 96 Dec 12, 2022
A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.

Use this instead: https://github.com/facebookresearch/maskrcnn-benchmark A Pytorch Implementation of Detectron Example output of e2e_mask_rcnn-R-101-F

Roy 2.8k Dec 29, 2022
DPT: Deformable Patch-based Transformer for Visual Recognition (ACM MM2021)

DPT This repo is the official implementation of DPT: Deformable Patch-based Transformer for Visual Recognition (ACM MM2021). We provide code and model

CASIA-IVA-Lab 111 Dec 21, 2022
Scene-Text-Detection-and-Recognition (Pytorch)

Scene-Text-Detection-and-Recognition (Pytorch) Competition URL: https://tbrain.t

Gi-Luen Huang 9 Jan 02, 2023