This is our solution to the Weather4cast 2022 competition, we achieved 1st place in the Core Challenge. For more info about the competition, description of the used data and a baseline starter kit, please see iarai/weather4cast-2022. The related paper is WeatherFusionNet: Predicting Precipitation from Satellite Data at https://arxiv.org/abs/2211.16824.
- Download the data (see link above) and extract it into the
data
subfolder, or editmodels/configurations/config.yaml
to point to the right folder. - Install dependencies with
conda env create -f environment.yml conda activate weather4cast
- Download trained weights from Releases.
The predict-submission.py
script generates a submission zip file for a given challenge and split. For example:
python predict-submission.py --challenge core --split test --gpus 0
or
python predict-submission.py --challenge transfer --split heldout --gpus 0
You can find the result in submission/submission.zip
.
See python predict-submission.py --help
for more info on the arguments.