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A Python Re-implementation of the paper "Recovering High Dynamic Range Radiance Maps from Photographs"

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Deep HDR Imaging

The Keras Implementation of the Recovering High Dynamic Range Radiance Maps from Photographs - SIGGRAPH 97

Content

Getting Started

  • Clone the repository

Prerequisites

  • PIL
  • numpy
  • opencv

Running

```
python main.py --tonemap 'gamma' --cmap True
```

Usage

Training

usage: main.py [-h] [--test_path] 
                    [--tonemap] 
                    [--cmap]
optional arguments: -h, --help  show this help message and exit
                    --test_path path to test images
                    --tonemap   choose tonemap method
                    --cmap      save radiance map

Result

DEMO

License

This project is licensed under the MIT License - see the LICENSE file for details

References

[1] Recovering High Dynamic Range Radiance Maps from Photographs link - SIGGRAPH 97

[3] Test data - link

Citation

    @inproceedings{10.1145/258734.258884,
                    author = {Debevec, Paul E. and Malik, Jitendra},
                    title = {Recovering High Dynamic Range Radiance Maps from Photographs},
                    year = {1997},
                    isbn = {0897918967},
                    publisher = {ACM Press/Addison-Wesley Publishing Co.},
                    address = {USA},
                    url = {https://doi.org/10.1145/258734.258884},
                    doi = {10.1145/258734.258884},
                    booktitle = {Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques},
                    pages = {369–378},
                    numpages = {10},
                    series = {SIGGRAPH '97}
    }

Acknowledgments

  • Any ideas on updating or misunderstanding, please send me an email: [email protected]
  • If you find this repo helpful, kindly give me a star.

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A Python Re-implementation of the paper "Recovering High Dynamic Range Radiance Maps from Photographs"

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