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[ICLR2021] Learning Accurate Entropy Model with Global Reference for Image CompressionThe official repository for Learning Accurate Entropy Model with Global Reference for Image Compression.
Pipeline
Kodak Dataset
Evaluation onRequirements
Prerequisites
Clone the repo and create a conda environment as follows:
conda create --name ref python=3.6
conda activate ref
conda install pytorch=1.1 torchvision cudatoolkit=10.0
(We use PyTorch 1.1, CUDA 10.1.)
Test Datasets
Kodak Dataset
kodak
├── image1.jpg
├── image2.jpg
└── ...
Evaluation & Comress & Decompress
Evaluation:
# Kodak
sh test.sh [/path/to/kodak] [model_path]
Compress:
sh compress.sh original.png [model_path]
Decompress:
sh decompress.sh original.bin [model_path]
Trained Models
Download the pre-trained models optimized by MSE.
Note: We reorganize code and the performances are slightly different from the paper's.
Acknowledgement
Codebase from L3C-image-compression , torchac
Citation
If you find this code useful for your research, please cite our paper
@InProceedings{Yichen_2021_ICLR,
author = {Qian, Yichen and Tan, Zhiyu and Sun, Xiuyu and Lin, Ming and Li, Dongyang and Sun, Zhenhong and Li, Hao and Jin, Rong},
title = {Learning Accurate Entropy Model with Global Reference for Image Compression},
booktitle = {International Conference on Learning Representations},
month = {May},
year = {2021},
}