README.md

Simple PyTorch Image Quality

This package is a collection of measures and metrics for image quality assessment in various image processing tasks such as denoising, super-resolution, image interpolation, etc. It relies heavily on PyTorch and takes advantage of its efficiency and automatic differentiation.

It should noted that spiq is directly inspired from the piq project. However, it focuses on the conciseness, readability and understandability of its (sub-)modules, such that anyone can freely and easily reuse and/or adapt them to its needs.

Installation

To install the current version of spiq,

git clone https://github.com/francois-rozet/spiq
cd spiq
python setup.py install

You can also copy the package directly to your project.

git clone https://github.com/francois-rozet/spiq
cd spiq
cp -R spiq <path/to/project>/spiq

Getting started

import torch
import spiq.psnr as psnr
import spiq.ssim as ssim

x = torch.rand(3, 3, 256, 256)
y = torch.rand(3, 3, 256, 256)

# PSNR function
l = psnr.psnr(x, y)

# SSIM instantiable object
criterion = ssim.SSIM().cuda()
l = criterion(x, y)

Documentation

The documentation of this package is generated automatically using pdoc.

pdoc spiq --html --config "git_link_template='https://github.com/francois-rozet/spiq/blob/{commit}/{path}#L{start_line}-L{end_line}'"