Data Science Bowl 2018
Lucas U-Net Instructions:
- SSH into the server, using your own account
- Clone this repository into your folder
source activate dsb(shared conda environment)
python train.py: this should create a .csv file that you can then submit on Kaggle.
(You might have to create an empty folder called numpy_dumps in "DSB_2018" if it gives you an error about the directory being non-existent. This is where the pre-processed data gets stored for later use.)
The raw data itself is stored at