Closed Eddymorphling closed 8 months ago
Hi @Eddymorphling I think you may have an old version of brainmapper (sorry, things are moving fairly quickly at the moment). Could you try pip install brainglobe-workflows brainglobe-utils -U
?
Hi @adamltyson I did try that and it seems that these two packages are up to date. Here is my pip list just in case. Also the braingmapper CLI shows me the same error when I use the inbuilt cellfinder model. I tried this on a fresh conda env.
Package Version
----------------------------- ------------
absl-py 2.0.0
alabaster 0.7.16
app-model 0.2.4
appdirs 1.4.4
asttokens 2.4.1
astunparse 1.6.3
attrs 23.2.0
Babel 2.14.0
beautifulsoup4 4.12.2
bg-atlasapi 1.0.2
bg_space 0.6.0
blessed 1.20.0
blosc2 2.4.0
brainglobe 1.0.0
brainglobe-heatmap 0.5.2
brainglobe-napari-io 0.3.2
brainglobe-segmentation 1.2.0
brainglobe-utils 0.3.4
brainglobe-workflows 1.1.0
brainreg 1.0.3
brainrender 2.1.3
brainrender-napari 0.0.2
bs4 0.0.1
build 1.0.3
cachetools 5.3.2
cachey 0.2.1
cellfinder 1.1.0
certifi 2023.11.17
charset-normalizer 3.3.2
click 8.1.7
cloudpickle 3.0.0
comm 0.2.1
configobj 5.0.8
contourpy 1.2.0
cycler 0.12.1
dask 2023.12.1
debugpy 1.8.0
decorator 5.1.1
Deprecated 1.2.14
docstring-parser 0.15
docutils 0.17.1
exceptiongroup 1.2.0
executing 2.0.1
fancylog 0.3.0
flatbuffers 23.5.26
fonttools 4.47.2
freetype-py 2.4.0
fsspec 2023.12.2
gast 0.4.0
google 3.0.0
google-auth 2.26.2
google-auth-oauthlib 0.4.6
google-pasta 0.2.0
grpcio 1.60.0
h5py 3.10.0
HeapDict 1.0.1
hsluv 5.0.4
idna 3.6
imagecodecs 2024.1.1
imageio 2.33.1
imagesize 1.4.1
imio 0.3.0
importlib-metadata 7.0.1
in-n-out 0.1.9
ipykernel 6.28.0
ipython 8.20.0
ipywidgets 8.1.1
jedi 0.19.1
Jinja2 3.1.3
joblib 1.3.2
jsonschema 4.20.0
jsonschema-specifications 2023.12.1
jupyter_client 8.6.0
jupyter_core 5.7.1
jupyterlab-widgets 3.0.9
k3d 2.16.1
keras 2.11.0
kiwisolver 1.4.5
lazy_loader 0.3
libclang 16.0.6
llvmlite 0.41.1
locket 1.0.0
loguru 0.7.2
magicgui 0.8.1
Markdown 3.5.2
markdown-it-py 3.0.0
MarkupSafe 2.1.3
matplotlib 3.8.2
matplotlib-inline 0.1.6
mdurl 0.1.2
meshio 5.3.4
morphapi 0.2.1
MorphIO 3.3.7
msgpack 1.0.7
multiprocessing-logging 0.3.4
mypy-extensions 1.0.0
myterial 1.2.1
napari 0.4.18
napari-console 0.0.9
napari-ndtiffs 0.2.1
napari-plugin-engine 0.2.0
napari-plugin-manager 0.1.0a2
napari-svg 0.1.10
natsort 8.4.0
ndindex 1.7
nest-asyncio 1.5.8
networkx 3.2.1
neurom 3.2.5
nibabel 5.2.0
npe2 0.7.3
nptyping 2.5.0
numba 0.58.1
numexpr 2.8.8
numpy 1.26.3
numpydoc 1.5.0
nvidia-ml-py 12.535.133
oauthlib 3.2.2
opt-einsum 3.3.0
packaging 23.2
pandas 2.1.4
parso 0.8.3
partd 1.4.1
pexpect 4.9.0
pillow 10.2.0
Pint 0.23
pip 23.3.2
platformdirs 4.1.0
pooch 1.8.0
prompt-toolkit 3.0.43
protobuf 3.19.6
psutil 5.9.7
psygnal 0.9.5
ptyprocess 0.7.0
pure-eval 0.2.2
py 1.11.0
py-cpuinfo 9.0.0
pyasn1 0.5.1
pyasn1-modules 0.3.0
pyconify 0.1.6
pydantic 1.10.13
pydantic-compat 0.1.2
Pygments 2.17.2
pyinspect 0.1.0
pynrrd 1.0.0
PyOpenGL 3.1.7
pyparsing 3.1.1
pyproject_hooks 1.0.0
PyQt5 5.15.10
PyQt5-Qt5 5.15.2
PyQt5-sip 12.13.0
python-dateutil 2.8.2
pytz 2023.3.post1
PyYAML 6.0.1
pyzmq 25.1.2
qtconsole 5.5.1
QtPy 2.4.1
referencing 0.32.1
requests 2.31.0
requests-oauthlib 1.3.1
retry 0.9.2
rich 13.7.0
rpds-py 0.16.2
rsa 4.9
scikit-image 0.22.0
scikit-learn 1.3.2
scipy 1.11.4
setuptools 69.0.3
six 1.16.0
slurmio 0.1.1
snowballstemmer 2.2.0
soupsieve 2.5
Sphinx 4.5.0
sphinxcontrib-applehelp 1.0.4
sphinxcontrib-devhelp 1.0.2
sphinxcontrib-htmlhelp 2.0.1
sphinxcontrib-jsmath 1.0.1
sphinxcontrib-qthelp 1.0.3
sphinxcontrib-serializinghtml 1.1.5
stack-data 0.6.3
superqt 0.6.1
tables 3.9.2
tensorboard 2.11.2
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.1
tensorflow 2.11.1
tensorflow-estimator 2.11.0
tensorflow-io-gcs-filesystem 0.35.0
termcolor 2.4.0
threadpoolctl 3.2.0
tifffile 2023.12.9
tomli 2.0.1
tomli_w 1.0.0
toolz 0.12.0
tornado 6.4
tqdm 4.66.1
traitlets 5.14.1
traittypes 0.2.1
treelib 1.7.0
typer 0.9.0
typing_extensions 4.9.0
tzdata 2023.4
urllib3 2.1.0
vedo 2023.5.0
vispy 0.12.2
vtk 9.3.0
wcwidth 0.2.13
Werkzeug 3.0.1
wheel 0.42.0
widgetsnbextension 4.0.9
wrapt 1.16.0
zipp 3.17.0
Hi @Eddymorphling,
It looks like something went wrong with our release process. This was fixed in the latest version, but that version wasn't actually released on PyPI! I'm in the process of releasing v1.1.2
and this should be on PyPI in the next hour. Could you test with pip install brainglobe-workflows -U
when you get a chance?
Hi @adamltyson . Thanks for letting me know. I did update brainglobe-workflows
and currently sit on v1.1.3. But when I run the same CLI for brainmapper
, I do get another import error as below:
ImportError: cannot import name 'check_unique_list' from 'brainglobe_utils.general.list' (/home/conda/envs/brainglobe_v1/lib/python3.10/site-packages/brainglobe_utils/general/list.py)
Can you try pip install brainglobe-utils -U
?
In general I think (hope) many of these issues can be solved with a fresh installation in a new environment. Please bear with us while we shuffle things around.
Not a problem at all, I hope my posts are not bothering you too much! Yes, updating brainglobe-utils
works. I will keep an eye out for PyPI updates moving forwards. Thanks again!
Not a problem at all, I hope my posts are not bothering you too much!
Not at all! Please raise any and all issues you find. There's always something that slips through the net.
@adamltyson Just a naive q about the brainmapper
CLI command line. If I am using a self-trained model during cell detection using the brainmapper
CLI, how do I tell the job to use "pre-trained weights" during cell detection/classification. Similar to the "use-pretrained-weights" option in the cellfinder-napari interface (screenshot below)
If you've trained a model, you just use that. Using pre-trained weights means using the default model the software ships with.
As an aside, if you have new questions (rather than a bug report), could you ask on the image.sc forum, tagging your post with brainglobe
? This way others who may have a similar question can more easily find the answer. Thanks!
Hi folks, I am trying to use the the new
brainmapper
CLI tool that uses a ResNet model that I generated withcellfinder
. Here is the CLI I use to run brainmapperNow everytime I run this only the registration step works well but the cell classification fails with the following error
If I run the same ResNet model using cellfinder in napari, everything works out well but not using the brainmapper CLI. Any clue what could be the issue here? Thank you.