This is the implementation for Deep High Dynamic Range Imaging with Large Foreground Motions, Shangzhe Wu, Jiarui Xu, Yu-Wing Tai, Chi-Keung Tang, in ECCV, 2018. More results can be found on our project page.
- Python 3.5
- Tensorflow 1.4.0
- OpenCV 3.4 (from conda-forge)
- Photomatix for tonemapping
- Clone this repo:
git clone https://github.com/elliottwu/DeepHDR.git
cd DeepHDR- Download pretrained model: (~60MB)
sh download_pretrained.shsh test.shGenerated HDR images are in .hdr format, which may not be properly displayed in your image viewer directly. You may use Photomatix for tonemapping:
- Download Photomatix free trial, which won't expire.
- Load the generated
.hdrfile in Photomatix. - Adjust the parameter settings. You may refer to pre-defined styles, such as
DetailedandPainterly2. - Save your final image in
.tifor.jpg.
- Download Kalantari's dataset: (~8GB)
cd dataset
sh download_dataset.sh
cd ..- Prepare TFRecord: (this takes ~10 minutes)
cd dataset
python convert_to_tfrecord.py
cd ..- Start training:
sh train.sh- To monitor training using Tensorboard, copy the following to your terminal and open
localhost:8888in your browser
tensorboard --logdir=logs --port=8888@InProceedings{Wu_2018_ECCV,
author = {Wu, Shangzhe and Xu, Jiarui and Tai, Yu-Wing and Tang, Chi-Keung},
title = {Deep High Dynamic Range Imaging with Large Foreground Motions},
booktitle = {The European Conference on Computer Vision (ECCV)},
month = {September},
year = {2018}
}