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mlomnitz / diffjpeg Goto Github PK

License: MIT License

Python 100.00%

diffjpeg's Introduction

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)

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diffjpeg's Issues

What if the size of image is odd?

run in cuda

I find it could not run in cuda,and it hard for me to rebulid the code.

Opensource?

Hi @mlomnitz

I was wondering if your repository could be open sourced.

If so, please add the MIT license to the root folder.

Feel free to ask me question.

there may be a small bug when the quality is 100

thank you for your work.
when i train my net in watermark,it gets NaN when the quality setted to be 100.However, it is just a small bug,and not affect the whole.

Can I use it for a jpg file decoding?

y_table and c_table transposes?

How confident are you that the transposes on the y_table and c_table are correct? To me, they don't seem correct, and depending on the quality level you can get the average error between the output and OpenCV's result by not transposing them.

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