yael-vinker/unpaired_hdr_tmo

Unpaired Learning for High Dynamic Range Image Tone Mapping

Pytorch implementation of our method for HDR image tome mapping using GAN.

Project | Paper

Installation

Installation via Docker [Recommended]

We provide a docker that contains the code and all the necessary libraries. It's simple to install and run.

docker build -t unpaired_tmo .
docker run --name unpaired_tmo -it -p 8888:8888 unpaired_tmo /bin/bash

Installation via Pip/Conda/Virtualenv

1. Clone the repo:

git clone https://github.com/yael-vinker/unpaired_hdr_tmo.git
cd unpaired_hdr_tmo

2. Create a new environment and install the libraries:

python3.6 -m venv hdr_venv
source hdr_venv/bin/activate
pip install -r requirements.txt

Quickstart (Run Demo Locally)

Run a model on your own image

To run the trained model of a task on a specific image:

cd activate_trained_model
python run_trained_model.py

Specify the path to a folder containing the input images using --input_images_path, the tone mapped images will be saved to the folder under --output_path.