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Set up LION from own github fork on the gpu-server
git clone https://github.com/_CambridgeCIA_/LION.git (_or your own fork_)
cd LION
git submodule update --init --recursive
conda env create --file=env.yml
pip install git+https://github.com/ahendriksen/ts_algorithms.git **(because it fails before)**
conda activate LION
Change the paths in LION/LION/utils/paths.py and then move back to LION/ base
pip install -e .
Run the download.py file in LION/LION/data_loaders/2DeteCT/
Maybe the paths in paths.py can be even set by default in reference to the installation folder
In addition, I think it should include a path parameter for saving trained models and one for saving evaluations
The last two mentioned paths could then be used in the standard templates for benchmarking and evaluation
This streamlines the individual usage of the toolbox where you only need to change a path in one location and not in many files.
The text was updated successfully, but these errors were encountered:
I am hoping that we can have something like pip install -e , -path:"somepath", or something like this in the future, but this is good info in the meanwhile!
Your extra points are also noted, may be the way to go. Thanks!
I think it would be recommendable to write a short instruction on how to set up LION with changed paths:
Install conda environment
Set up LION from own github fork on the gpu-server
Change the paths in LION/LION/utils/paths.py and then move back to LION/ base
pip install -e .
Run the download.py file in LION/LION/data_loaders/2DeteCT/
This streamlines the individual usage of the toolbox where you only need to change a path in one location and not in many files.
The text was updated successfully, but these errors were encountered: