Climate Informatics 2020 Data Challenge

In the context of the Climate Informatics 2020 conference data challenge, we attempt to predict visible imagery at night using thermal infra-red observation. More details on the challenge and datasets in here. In this work, we propose to train a pix2pix-like cGANs at spectral domain translation.

Getting started

From command line

Setup a configuration file specifying experiment hyperparameters, templates provided here.

Then run

$ python run_training.py --cfg=path_to_config_file --o=path_to_logs_directory --device=gpu_id

To reproduce the experiment submitted to the hackathon, one should use configurations specfied by config/base_unet.yaml

From a notebook

See demonstration notebook on how to run an experiment.

Results

Example of predicted visible images from nightly infrared inputs

Installation

Code implemented in Python 3.8

Setting up environment

Clone and go to repository

$ git clone https://github.com/shahineb/ci-hackathon.git
$ cd ci-hackathon

Create and activate environment

$ pyenv virtualenv 3.8.2 hackathon
$ pyenv activate hackathon
$ (hackathon)

Install dependencies

$ (hackathon) pip install -r requirements.txt