Pytorch implementation of forward and inverse Haar Wavelets 2D

Last update: Oct 30, 2022

Overview

haar_pytorch: Pytorch implementation of forward and inverse Haar Wavelets 2D

A simple library that implements differentiable forward and inverse Haar Wavelets.

Install package

pip install haar_pytorch

Install the latest version

pip install --upgrade git+https://github.com/bes-dev/haar_pytorch.git

Example

import torch
from haar_pytorch import HaarForward, HaarInverse

haar = HaarForward()
ihaar = HaarInverse()

img = torch.randn(5, 4, 64, 64)
wavelets = haar(img)
img_reconstructed = ihaar(wavelets)

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Releases(2021.11.16.0)

2021.11.16.0(Nov 16, 2021)

Add implementation of the HaarForward and HaarInverse
Source code(tar.gz)
Source code(zip)

Owner

Sergei Belousov

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