bioimageio.core 0.4.0

Python functionality for the bioimage model zoo

python-bioimage-io core

Python specific core utilities for working with the BioimageIO model zoo.

Installation

Via Conda

The bioimageio.core package supports various back-ends for running BioimageIO networks:

• Pytorch/Torchscript:

  # cpu installation (if you don't have an nvidia graphics card)
  conda install -c pytorch -c conda-forge -c ilastik-forge bioimageio.core pytorch torchvision cpuonly
  
  # gpu installation
  conda install -c pytorch -c conda-forge -c ilastik-forge bioimageio.core pytorch torchvision cudatoolkit
  

• Tensorflow

  # currently only cpu version supported
  conda install -c conda-forge -c ilastik-forge bioimageio.core tensorflow
  

• ONNXRuntime

  # currently only cpu version supported
  conda install -c conda-forge -c ilastik-forge bioimageio.core onnxruntime
  

Set up Development Environment

To set up a development conda environment run the following commands:

conda env create -f dev/environment-base.yaml
conda activate bio-core-dev
pip install -e . --no-deps

There are different environment files that only install tensorflow or pytorch as dependencies available.

Command Line

You can list all the available command line options:

bioimageio

Test a model:

bioimageio test -m <MODEL>

Run prediction:

bioimageio predict -m <MODEL> -i <INPUT> -o <OUTPUT>

This is subject to change, see https://github.com/bioimage-io/python-bioimage-io/issues/87.

Running network predictions:

TODO

Model Specification

The model specification and its validation tools can be found at https://github.com/bioimage-io/spec-bioimage-io.