https://github.com/conda-forge/miniforge#miniforge3
This should limit duplication of downloads, hopefully
| Environment Variable | Value |
|---|---|
CONDA_ENVS_PATH |
D:\conda\conda-envs |
CONDA_PKGS_DIRS |
D:\conda\conda-packages |
Change
D:to whatever drive you have on the workstation
conda foldericacls D:\conda /grant:r Users:(OI)(CI)F /T
In order to avoid models being downloaded for each user, set CELLPOSE_LOCAL_MODELS_PATH
| Environment Variable | Value |
|---|---|
CELLPOSE_LOCAL_MODELS_PATH |
D:\conda\extras\cellpose-models |
mamba create -n cellpose-3111 python=3.8 -y
mamba activate cellpose-3111
mamba install pytorch pytorch-cuda=11.8 -c pytorch -c nvidia -y
pip install cellpose==3.1.1.1 scikit-image
As per this referenced issue, cellpose currently has a bug when it comes to training using --all_channels. It cannot be used via the CLI.
This PR corrects the issue but has not been implemented. For now we can use the following to install a temporary version of Cellpose from our own GitHub fork
https://github.com/BIOP/cellpose/commit/3939d6a889debd1a6c73e5e2e2088a0ab7bb26eb
mamba create -n cellpose-308-fix python=3.8 -y
mamba activate cellpose-308-fix
mamba install pytorch pytorch-cuda=11.8 -c pytorch -c nvidia -y
pip install git+https://github.com/BIOP/cellpose.git@3939d6a889debd1a6c73e5e2e2088a0ab7bb26eb scikit-image
Follow the instructions in the ReadMe
Follow the instructions in the ReadMe
mamba create -n omnipose 'python==3.9.18'
mamba activate omnipose
mamba install pytorch torchvision pytorch-cuda=11.8 -c pytorch -c nvidia -y
pip install git+https://github.com/kevinjohncutler/omnipose.git@260e4d3f87a356d0d496e5db8febf80ccb2e48a7 aicsimageio torch_optimizer
Installing Pytorch via mamba seems to cause an issue, as we are calling Python and not mamba activate from QuPath. The following installation works, but is messier.
mamba create -n omnipose python=3.9 -y
mamba activate omnipose
pip install git+https://github.com/kevinjohncutler/omnipose.git@260e4d3f87a356d0d496e5db8febf80ccb2e48a7 aicsimageio torch_optimizer scikit-image
pip uninstall torch torchvision
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu118
mamba create -n empanada-023-gpu python=3.9 -y
mamba activate empanada-023-gpu
mamba install pytorch torchvision pytorch-cuda=11.8 -c pytorch -c nvidia -y
pip install "napari[all]" empanada-napari==0.2.3
A test image can be found ..\ptbiop-raw\public\0-Software\empanada\
conda create -n omero -c ome python=3.8 zeroc-ice36-python ipykernel
conda activate omero
python -m ipykernel install --user
conda install -c conda-forge omero-py
conda create -n ome_ngff python=3.9
conda activate ome_ngff
python.exe -m pip install --upgrade pip
pip install "napari[all]" napari-ome-zarr ome-zarr notebook
This ensures that the model weights are downloaded only once
| Environment Variable | Value |
|---|---|
SAMAPI_ROOT_DIR |
D:\conda\extras\sam-models |
mamba create -n samapi python=3.10 -y
mamba activate samapi
python -m pip install git+https://github.com/ksugar/samapi.git
pip uninstall torch torchvision
mamba install pytorch torchvision pytorch-cuda=11.8 -c pytorch -c nvidia
Activate SAM.bat in the Public Desktop with the following codecall C:\ProgramData\miniforge3\Library\bin\mamba.bat activate samapi
uvicorn samapi.main:app --workers 2
pause
To be able to "pin" the shortcut to the task bar , right-click > properties > target , modifiy so cmd.exe /C "path-to-your-batch"
mamba create -n stardist-085-gpu python=3.7 cudatoolkit=10.1.* cudnn=7.6.* -c nvidia -y
mamba activate stardist-085-gpu
pip install tensorflow==2.3.* stardist==0.8.5
dataset to test
TODO
From instructions on github, for Windows make sure to install Build Tools for Visual Studio
mamba create -n spotiflow python=3.9.* pytorch torchvision pytorch-cuda=11.8 -c pytorch -c nvidia -y
mamba activate spotiflow
mamba install napari[all] pyqt
pip install spotiflow napari-spotiflow
mamba create --name tarrow python=3.8 -y
mamba activate tarrow
mamba install pytorch torchvision pytorch-cuda=11.8 -c pytorch -c nvidia -y
pip install git+https://github.com/weigertlab/tarrow.git
mamba create -n wsinfer pytorch torchvision pytorch-cuda=11.8 -c pytorch -c nvidia -y
mamba activate wsinfer
TODO QuPath extension !!! ????