IQA-pytorch 0.1

IQA models in PyTorch

Image Quality Assessment (IQA) Models in PyTorch

This is a repository to re-implement the existing IQA models with PyTorch, including

• SSIM, MS-SSIM, CW-SSIM,
• FSIM, VSI,GMSD,
• NLPD, MAD,
• VIF,
• LPIPS, DISTS.

Note: The reproduced results may be a little different from the original matlab version.

Installation:

• pip install IQA_pytorch

Requirements:

• Python>=3.6
• Pytorch>=1.2

Usage:

from IQA_pytorch import SSIM, GMSD, LPIPSvgg, DISTS
D = SSIM()
# Calculate score of the image X with the reference Y
# X: (N,3,H,W) 
# Y: (N,3,H,W) 
# Tensor, data range: 0~1
score = D(X, Y, as_loss=False) 
# set 'as_loss=True' to get a value as loss for optimizations.
loss = D(X, Y)
loss.backward()