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DiffJPEG: A PyTorch implementation

This is a pytorch implementation of differentiable jpeg compression algorithm. This work is based on the discussion in this paper. The work relies heavily on the tensorflow implementation in this repository

Requirements

  • Pytorch 1.0.0
  • numpy 1.15.4

Use

DiffJPEG functions as a standard pytorch module/layer. To use, first import the layer and then initialize with the desired parameters:

  • differentaible(bool): If true uses custom differentiable rounding function, if false uses standrard torch.round
  • quality(float): Quality factor for jpeg compression scheme.
from DiffJPEG import DiffJPEG
jpeg = DiffJPEG(hieght=224, width=224, differentiable=True, quality=80)

image

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  • Python 100.0%