In 2017, Gharbi et al. published the paper 'Deep Bilateral Learning for Real-Time Image Enhancement' in SIGGRAPH 2017 (vol 36). The paper is about reconstructing image filters and human retouchment using deep neural networks. An implementation of the neural network architecture using Tensorflow 1.1 can be found at: https://github.com/mgharbi/hdrnet
This application is a webcam viewer application using OpenGL and the TensorFlow C++ API for network models learned by that network architecture implementation. It is in no way endorsed by Gharbi et al.
Prerequisites (build currently only supported on Linux):
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OpenCV 2
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Tensorflow 1.1 C++ API headers & library, expected to be in installed in the directory /usr/local
The standard Python package of Tensorflow is not sufficient to build the application! You can read more about compiling the Tensorflow C++ API here: https://github.com/FloopCZ/tensorflow_cc
Please note that the shared build of TensorflowCC is required, as the application uses broad parts of the TensorFlow C++ API.
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sgl: https://github.com/chrismile/sgl (use sudo make install to install this library on your system)
Please note that pre-learned image filters are not included in this repository. The original implementation contains multiple pre-learned models. Please get them from https://github.com/mgharbi/hdrnet and put them into the folder "Data/pretrained_models".