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LIC360

Dateset and codes of "End-to-end optimized 360-degree image compression"

Dataset:

Requirmed packages:

  • pytorch
  • cv2 (python-opencv)
  • numpy

Install:

  • python setup.py install
  • cd coder & python setup_linux.py install

Running the codec for 360-degree images:

  • Encoding:
    • python ./test/lic360_demo.py --enc --img-file image_names.txt --code-file code_names.txt --model-idx 3 --ssim
    • python ./test/lic360_demo.py --enc --img-list a.png b.png --code-list code_a code_b --model-idx 3 --ssim
  • Decoding:
    • python ./test/lic360_demo.py --dec --out-file decoded_image_names.txt --code-file code_names.txt --model-idx 3 --ssim
    • python ./test/lic360_demo.py --dec --out-list a_dec.png b_dec.png --code-list code_a code_b --model-idx 3 --ssim
  • Testing (Decoding and evaluate the performance):
    • python ./test/lic360_demo.py --test --img-file source_image_names.txt --code-file code_names.txt --model-idx 3 --ssim
    • python ./test/lic360_demo.py --test --img-list a.png b.png --code-list code_a code_b --model-idx 3 --ssim
    • python ./test/lic360_demo.py --test --img-list a.png b.png --code-list code_a code_b --model-idx 3 --ssim

@article{li2022end,
  title={End-to-End Optimized 360° Image Compression},
  author={Li, Mu and Li, Jinxing and Gu, Shuhang and Wu, Feng and Zhang, David},
  journal={IEEE Transactions on Image Processing},   volume={31},
  pages={6267--6281},
  year={2022},
  publisher={IEEE}
}

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