Deep Illuminator

Deep Illuminator is a data augmentation tool designed for image relighting. It can be used to easily and efficiently generate a wide range of illumination variants of a single image. It has been tested with several datasets and models and has been shown to succesfully improve performance. It has a built in visualizer created with Streamlit to preview how the target image can be relit.

Example Augmentations

Usage

The simplest method to use this tool is through Docker Hub:

docker pull kartvel/deep-illuminator

Visualizer

Once you have the Deep Illuminator image run the following command to launch the visualizer:

docker run -it --rm  --gpus all \
-p 8501:8501 --entrypoint streamlit \ 
kartvel/deep-illuminator run streamlit/streamlit_app.py

You will be able to interact with it on localhost:8501. Note: If you do not have NVIDIA gpu support enabled for docker simply remove the --gpus all option.

Generating Variants

It is possible to quickly generate multiple variants for images contained in a directory by using the following command:

docker run -it --rm --gpus all \                                                                                               ─╯
-v /path/to/input/images:/app/probe_relighting/originals \
-v /path/to/save/directory:/app/probe_relighting/output \
kartvel/deep-illuminator --[options]

Options

Buidling Docker image or running without a container

Please read the following for other options: instructions

Benchmarks

Improved performance of R2D2 for MMA@3 on HPatches

Improved performance of R2D2 for the Long-Term Visual Localization challenge on Aachen v1.1

Acknowledgment

The developpement of the VAE for the visualizer was made possible by the PyTorch-VAE repository.