Closed tylerreekes closed 10 hours ago
Hi @tylerreekes, thanks for posting the problem here :+1:
Can you let me know how you create the environment and installed the python version? The tensorflow version does not comply with the versions specified in the setup.py (i.e. < 2.16), so I am curious how it's possible that the installation is using a higher version. Did you have any other environments activated while created the venv? Did the installation succeed or were there any error messages?
Best, Julian
We create and source the virtual environment in the same way as described in steps 2 and 3. python3 -m venv /Users/tylerreekes/lst_env source /Users/tylerreekes/lst_env/bin/activate
From here we pip installed LST-AI and HD-BET. We then compiled the greedy binaries as instructed in ~/bin.
In the virtual environment, we pip/brew installed tensor flow. Both installations were successful.
We were able to run and get results with the following steps. We downloaded an older version of python (3.9) and that allowed for older versions of numpy and tensorflow not available in the current version(s) (>3.12).
brew install python@3.9
mkdir lst_directory cd lst_directory
python3.9 -m venv /Users/tylerreekes/lst_env source /Users/tylerreekes/lst_env/bin/activate
git clone https://github.com/CompImg/LST-AI/ cd LST-AI pip install -e . cd ..
git clone https://github.com/MIC-DKFZ/HD-BET
cd HD-BET
pip install -e .
cd ..
sudo /Applications/ITK-SNAP.app/Contents/bin/install_cmdl.sh ~/bin
export PATH=/Applications/ITK-SNAP.app/Contents/bin:$PATH
cd LST-AI
pip install -r requirements.txt
lst --t1 /path/to/T1/.nii.gz --flair /path/to/FLAIR/.nii.gz --temp /path/to/temporary/directory --output /path/to/results/folder
Fantastic @tylerreekes ! 🙂
I hope the rest works seamlessly! Let us know if you encounter any other problems, and thanks for reporting back!
I will add this issue to our future release issues #27. Adding this as a note to our future development efforts:
@twiltgen lets look if we can find a way of supporting newer versions of python, or if we need to limit this in setup.py as well, soon or later we might need to change the model format to incorporate more recent tf releases as well.
Cheers,
Julian
When running the segmentation, the following TypeError message is returned: Exception encountered: Unrecognized keyword arguments passed to Conv3DTranspose: {'groups': 1}
We installed the software via the python recommended steps with the following exception: -downloaded greedy binaries from ITK-SNAP instead of wget (6.1.i) MacBook M3 - macOS Sonoma 14.6.1
TensorFlow Version: 2.18.0