nucleaizer-backend 0.1.6

Backend for the napari_nucleaizer plugin

nucleaizer-backend

Use in headless mode

• Install MATLAB Runtime v99.

• If ready, do not forget to set the LD_LIBRARY_PATH: the install prints out. OR set the MATLAB_RUNTIME_PATHS variable: e.g.:

  MATLAB_RUNTIME=/MATLAB/MATLAB_Runtime
  export MATLAB_RUNTIME_PATHS=$MATLAB_RUNTIME/v99/runtime/glnxa64:$MATLAB_RUNTIME/v99/bin/glnxa64:$MATLAB_RUNTIME/v99/sys/os/glnxa64:$MATLAB_RUNTIME/v99/extern/bin/glnxa64

• Install the stuff locally in a virtual environment:

  python -m venv venv
  source venv/bin/activate (or .\Scripts\activate or something on Win)
  python -m pip install --upgrade pip
  python -m pip install -r requirements.txt
  python -m pip install -e .

• If the install is readly, then one should create the nucleaizer_backend/cli_config.py file and setup the config values needed:

  • nucleaizer_dir: the directory where the models (.h5) files, configs, etc are staying. Prepare this dir first. Example: .nucleaizer_data_example in the shared distribution.

  • workflow_dir: a directory where the pipeline puts the intermediate results. May be empty or a result of a previous run.

  • inputs_dir: the input should go here with the subdirs train, val, test. Consult the training.py for the details. Example: nucleaizer_dataset in the shared distribution.

• Then, call the entry point: python -m nucleaizer_backend.run_cli. See the corresponding script for the details.

• Free software: MIT license

• Documentation: https://nucleaizer-backend.readthedocs.io.

Features

• TODO

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

History

0.1.0 (2021-02-03)

• First release on PyPI.