This is a first draft for adding Segger. There are current issues that can't be solved (spatialdata and segger dependency issue and cuda error when running on cpu)

Two main issues:

• When running the last step (segment) we run into a cuda issue (tested in dockercontainer on Mac M3), note that the training worked fine. Related issue: CUDA error when running predictions without GPU EliHei2/segger_dev#126
• The latest segger version is needed for (hopefully a future solution of) the cuda issue, and the support of other techs than xenium (no need for the "qv" column, see here Data sample save does not produce files EliHei2/segger_dev#125). However, there are dask und numpy version dependency conflicts between segger and spatialdata (see here Spatialdata and dask Comatibility EliHei2/segger_dev#123).

Environment

• For the docker container, note that the config.vsh.yaml gives the ideal solution (for future updated version of the danielunyi42/segger_dev container), however currently this doesn't work (see CUDA error when running predictions without GPU EliHei2/segger_dev#126 (comment)). Besides the docker container build that I posted there you also need to install:

git clone https://github.com/EliHei2/segger_dev.git
cd segger_dev
pip install .
pip install torch==2.5.0 
pip install lightning
pip install torchmetrics
pip install cupy-cuda12x
pip install distributed
pip install dask_geopandas

Other

• There are a few NOTEs and TODOs in the segger script that can be tackled when the upper issues are resolved

How to proceed

• Continue when the spatialdata segger dependency issue is resolved
• Hope that the cuda error is then also resolved