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Machine learning-based photo color enhancement system [CHI 2016]

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SelPh

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A machine-learning-based photo color enhancement system that implicitly learns users' preference.

Publication

Yuki Koyama, Daisuke Sakamoto, and Takeo Igarashi. 2016. SelPh: Progressive Learning and Support of Manual Photo Color Enhancement. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '16), pp.2520--2532. DOI: http://dx.doi.org/10.1145/2858036.2858111

Project Page

Please visit our project page for details: http://koyama.xyz/project/SelPh/

Languages and Runtime Environments

Main functionality is written in C++11. Real-time photo color enhancement is written in programmable shaders, which require support of both OpenGL 3.2 Core Profile and GLSL 3.3.

Set Up

macOS

This software has been written for and tested on macOS (x86_64). Other platforms (e.g., Windows, Linux) are currently not supported. If you want to build this software on other platforms, you might need to modify several parts (e.g., header paths). Pull requests welcome.

Build using CMake

We use cmake https://cmake.org/ for building source codes.

git clone https://github.com/yuki-koyama/selph.git --recursive
cd selph
mkdir build
cd build
cmake ../
make

License

The source codes are released under the MIT License; see LICENSE.txt.

Dependencies

Test Photographs

This repository includes a photo album for testing the software. These photographs were taken by Yuki Koyama, and licensed under CC BY. If you want higher resolution photographs, please contact us.

Developer/Contact

Yuki Koyama - yuki@koyama.xyz

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Machine learning-based photo color enhancement system [CHI 2016]

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