Tropical Cyclones Detection (CMCC)

The code is adapted from the CMCC use case’s repository and refers to a TensorFLow implementation. To know more on the interTwin tropical cyclones detection use case and its DT, please visit the published deliverables, D4.1, D7.1 and D7.3. You can find the relevant code in the use case’s folder on Github, or by consulting the use case’s README:

Integration author(s): Matteo Bunino (CERN), Roman Machacek (CERN), Mario Ruettgers (JSC)

The code is adapted from the CMCC use case’s repository.

Setup env

# After activating the environment
pip install -r requirements.txt

Dataset

If the automatic download from python does not work, try from the command line from within the virtual environment:

gdown https://drive.google.com/drive/folders/1TnmujO4T-8_j4bCxqNe5HEw9njJIIBQD -O data/tmp_data/trainval --folder

For more info visit the gdown repository.

Training

Launch training:

# # ONLY IF tensorflow>=2.16
# export TF_USE_LEGACY_KERAS=1

source ../../.venv-tf/bin/activate
python train.py -p pipeline.yaml

On JSC, the dataset is pre-downloaded and you can use the following command:

# # ONLY IF tensorflow>=2.16
# export TF_USE_LEGACY_KERAS=1

source ../../envAItf_hdfml/bin/activate
python train.py -p pipeline.yaml --data_path /p/project/intertwin/smalldata/cmcc

# Launch a job with SLURM
sbatch startscript.sh