Deep Bilateral Learning for Real-Time Image Enhancements

Unofficial PyTorch implementation of 'Deep Bilateral Learning for Real-Time Image Enhancement', SIGGRAPH 2017 https://groups.csail.mit.edu/graphics/hdrnet/

Python 3.6

Dependencies

To install the Python dependencies, run:

pip install -r requirements.txt

Datasets

Adobe FiveK - https://data.csail.mit.edu/graphics/fivek/

Usage

To train a model, run the following command:

python train.py --test-image=./DSC_1177.jpg --dataset=/dataset_path --lr=0.0001

To get all train params run:

python train.py -h

To test image run:

python test.py --checkpoint=./ch/ckpt_0_4000.pth --input=./DSC_1177.jpg --output=out.png

Known issues

• Only PointwiseNN implemented currently
• Dataset has no augmentation which making training difficult
• No raw HDR input