Python functionality for the bioimage model zoo
Project description
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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for bioimageio.core-0.4.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 62a51504a282df55045b77f1e659b8aad5597281afde431d5bc4b949f1a9a8bf |
|
MD5 | 93628c5fb758570d90bbf66357a9fcff |
|
BLAKE2b-256 | 1a0ca710fc5d7b8f7c1f98f2bad946700e8504700cec1c0bba6a54ca359bd505 |