PyJAMAS is Just A More Awesome SIESTA
PyJAMAS is Just A More Awesome Siesta.
A note on the Python interpreter
PyJAMAS does NOT work with Python 2.
MacOS and Linux
Open a terminal. If you had previously installed PyJAMAS, we recommend uninstalling the previous version:
To install PyJAMAS, type:
$ python3 -m pip install --no-cache-dir -U pyjamas-rfglab
To run PyJAMAS, type:
at the user prompt.
If the executable fails to run, you can also try to execute PyJAMAS by opening a terminal and typing:
$ python3 -m pyjamas.pjscore
$ conda install -c apple tensorflow
Then install Jupyter:
$ conda install -c conda-forge jupyter jupyterlab
And finally install the rest of packages necessary for PyJAMAS to run:
$ conda install openblas pyqt joblib lxml pandas scikit-image scikit-learn seaborn shapely opencv
The last step is to install PyJAMAS:
$ python -m pip install --no-deps pyjamas-rfglab
GPU support on the Apple M1
PyJAMAS supports the use of the GPU on the M1 chip. To do this, install tensorflow-metal (version 0.2 if you are on Big Sur - OSX 11, version 0.3 if you are on Monterey - OSX 12). For example, on Big Sur:
$ python -m pip install tensorflow-metal==0.2
Before installing PyJAMAS, you will need to install Shapely, a package used in PyJAMAS to represent geometric objects such as points or polygons. Under Windows, Shapely fails to install with the PyJAMAS PyPi package. It is recommended to start by manually installing Shapely. To that end, download the appropriate Shapely version from this link. For example, use Shapely‑1.6.4.post2‑cp37‑cp37m‑win_amd64.whl for a 64-bit machine running Python 3.7. Open a command prompt and navigate to the folder that contains the downloaded .whl file using the cd command. Complete the installation of Shapely by typing:
$ python -m pip install Shapely‑1.6.4.post2‑cp37‑cp37m‑win_amd64.whl
$ python -m pip install --no-cache-dir -U pyjamas-rfglab
To run PyJAMAS type:
at the user prompt.
If the executable fails to run, you can also try to execute PyJAMAS by opening a command prompt and typing:
$ python -m pyjamas.pjscore
GPU support under Windows
Download and install the NVIDIA GPU drivers.
Download and install the CUDA Toolkit.
Download and install the cuDNN SDK (https://developer.nvidia.com/cudnn and https://docs.nvidia.com/deeplearning/cudnn/install-guide/index.html).
Known problems: CUDA and cuDNN are picky with the version of each other that they talk to. If PyJAMAS displays an error that cusolver64_10.dll is not found:
Go to the folder C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\V11.2\bin (replacing V11.2 by whichever version you installed).
Create a copy of the file cusolver64_11.dll.
Rename the copy as cusolver64_10.dll.
If you use PyJAMAS, please cite:
Fernandez-Gonzalez R, Balaghi N, Wang K, Hawkins R, Rothenberg K, McFaul C, Schimmer C, Ly M, do Carmo A, Scepanovic G, Erdemci-Tandogan G, Castle V. PyJAMAS: open-source, multimodal segmentation and analysis of microscopy images. Bioinformatics. 2021 Aug 13:btab589. doi: 10.1093/bioinformatics/btab589.
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