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.github/workflows/build_docs.yml

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# Standard drop-in approach that should work for most people.
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- uses: ammaraskar/sphinx-action@master
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with:
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pre-build-command: "pip install -r dev.requirements.txt"
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pre-build-command: "pip install -r requirements.txt"
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docs-folder: "docs/"
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- name: GitHub Pages action
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uses: peaceiris/[email protected]
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with:
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github_token: ${{ secrets.GITHUB_TOKEN }}
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publish_dir: ./docs/_build/html
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publish_dir: ./docs/_build/html
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# This workflows will upload a Python Package using Twine when a release is created
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# For more information see: https://help.github.com/en/actions/language-and-framework-guides/using-python-with-github-actions#publishing-to-package-registries
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#name: tests
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#
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#on:
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# push:
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# branches:
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# - main
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# - npe2
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# tags:
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# - "v*" # Push events to matching v*, i.e. v1.0, v20.15.10
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# pull_request:
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# branches:
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# - main
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# - npe2
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# workflow_dispatch:
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#
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#jobs:
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# test:
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# name: ${{ matrix.platform }} py${{ matrix.python-version }}
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# runs-on: ${{ matrix.platform }}
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# strategy:
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# matrix:
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# platform: [windows-latest]
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# python-version: [3.8]
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#
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# steps:
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# - uses: actions/checkout@v2
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#
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# - name: Set up Python ${{ matrix.python-version }}
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# uses: actions/setup-python@v2
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# with:
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# python-version: ${{ matrix.python-version }}
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#
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# # these libraries enable testing on Qt on linux
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# - uses: tlambert03/setup-qt-libs@v1
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#
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# # strategy borrowed from vispy for installing opengl libs on windows
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# - name: Install Windows OpenGL
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# if: runner.os == 'Windows'
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# run: |
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# git clone --depth 1 https://github.com/pyvista/gl-ci-helpers.git
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# powershell gl-ci-helpers/appveyor/install_opengl.ps1
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#
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# # note: if you need dependencies from conda, considering using
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# # setup-miniconda: https://github.com/conda-incubator/setup-miniconda
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# # and
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# # tox-conda: https://github.com/tox-dev/tox-conda
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# - name: Install dependencies
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# run: |
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# python -m pip install --upgrade pip
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# python -m pip install setuptools tox tox-gh-actions
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#
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# # this runs the platform-specific tests declared in tox.ini
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# - name: Test with tox
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# uses: GabrielBB/xvfb-action@v1
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# with:
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# run: python -m tox
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# env:
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# PLATFORM: ${{ matrix.platform }}
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#
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# - name: Coverage
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# uses: codecov/codecov-action@v2
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#
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# deploy:
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# # this will run when you have tagged a commit, starting with "v*"
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# # and requires that you have put your twine API key in your
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# # github secrets (see readme for details)
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# needs: [test]
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# runs-on: ubuntu-latest
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# if: contains(github.ref, 'tags')
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# steps:
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# - uses: actions/checkout@v2
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# - name: Set up Python
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# uses: actions/setup-python@v2
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# with:
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# python-version: "3.8"
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# - name: Install dependencies
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# run: |
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# python -m pip install --upgrade pip
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# pip install -U setuptools setuptools_scm wheel twine build
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# - name: Build and publish
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# env:
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# TWINE_USERNAME: __token__
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# TWINE_PASSWORD: ${{ secrets.TWINE_API_KEY }}
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# run: |
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# git tag
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# python -m build .
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# twine upload dist/*
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#
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name: tests
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on:
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push:
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branches:
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- main
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- npe2
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tags:
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- "v*" # Push events to matching v*, i.e. v1.0, v20.15.10
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pull_request:
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branches:
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- main
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- npe2
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workflow_dispatch:
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jobs:
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test:
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name: ${{ matrix.platform }} py${{ matrix.python-version }}
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runs-on: ${{ matrix.platform }}
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strategy:
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matrix:
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platform: [ubuntu-latest, windows-latest, macos-latest]
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python-version: [3.8, 3.9, "3.10"]
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.python-version }}
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# these libraries enable testing on Qt on linux
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- uses: tlambert03/setup-qt-libs@v1
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# strategy borrowed from vispy for installing opengl libs on windows
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- name: Install Windows OpenGL
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if: runner.os == 'Windows'
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run: |
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git clone --depth 1 https://github.com/pyvista/gl-ci-helpers.git
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powershell gl-ci-helpers/appveyor/install_opengl.ps1
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if (Test-Path -Path "C:\Windows\system32\opengl32.dll" -PathType Leaf) {Exit 0} else {Exit 1}
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# note: if you need dependencies from conda, considering using
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# setup-miniconda: https://github.com/conda-incubator/setup-miniconda
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# and
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# tox-conda: https://github.com/tox-dev/tox-conda
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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python -m pip install setuptools tox tox-gh-actions
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# this runs the platform-specific tests declared in tox.ini
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- name: Test with tox
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uses: GabrielBB/xvfb-action@v1
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with:
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run: python -m tox
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env:
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PLATFORM: ${{ matrix.platform }}
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- name: Coverage
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uses: codecov/codecov-action@v2
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deploy:
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# this will run when you have tagged a commit, starting with "v*"
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# and requires that you have put your twine API key in your
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# github secrets (see readme for details)
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needs: [test]
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runs-on: ubuntu-latest
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if: contains(github.ref, 'tags')
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python
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uses: actions/setup-python@v2
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with:
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python-version: "3.x"
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install -U setuptools setuptools_scm wheel twine build
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- name: Build and publish
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env:
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TWINE_USERNAME: __token__
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TWINE_PASSWORD: ${{ secrets.TWINE_API_KEY }}
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run: |
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git tag
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python -m build .
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twine upload dist/*

LICENSE

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The MIT License (MIT)
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Copyright (c) 2022 Cyril Achard, Maxime Vidal
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Copyright (c) 2022 Cyril Achard, Maxime Vidal, Mackenzie Mathis
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal

README.md

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<a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
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[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/AdaptiveMotorControlLab/CellSeg3d/raw/main/LICENSE)
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[![PyPI](https://img.shields.io/pypi/v/napari-cellseg-annotator.svg?color=green)](https://pypi.org/project/napari-cellseg-annotator)
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[![PyPI](https://img.shields.io/pypi/v/napari-cellseg3d.svg?color=green)](https://pypi.org/project/napari-cellseg3d)
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[![Python Version](https://img.shields.io/pypi/pyversions/napari-cellseg-annotator.svg?color=green)](https://python.org)
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[![codecov](https://codecov.io/gh/AdaptiveMotorControlLab/napari-cellseg3d/branch/main/graph/badge.svg)](https://codecov.io/gh/AdaptiveMotorControlLab/CellSeg3d)
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[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-cellseg3d)](https://napari-hub.org/plugins/CellSeg3d)
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## Documentation
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Available at https://AdaptiveMotorControlLab.github.io/cellseg3d-docs
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Available at https://AdaptiveMotorControlLab.github.io/CellSeg3d
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You can also generate docs by running ``make html`` in the docs folder.
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## Requirements
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**Python >= 3.8 required**
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Requires manual installation of **pytorch** and **MONAI**.
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Requires **pytorch** and **MONAI**.
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For PyTorch, please see [PyTorch's website for installation instructions].
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A CUDA-capable GPU is not needed but very strongly recommended, especially for training.
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If you get errors from MONAI regarding missing readers, please see [MONAI's optional dependencies] page for instructions on getting the readers required by your images.
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dev.requirements.txt

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requirements.txt

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black
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coverage
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isort
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pytest
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pytest-qt
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sphinx
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sphinx-autodoc-typehints
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sphinx-rtd-theme
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tox
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twine
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numpy
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napari>=0.4.14
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PyQt5>=5.15.6
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opencv-python>=4.5.5.62
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dask-image>=0.6.0
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scikit-image>=0.19.2
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matplotlib>=3.4.1
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tifffile>=2022.2.9
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imageio-ffmpeg>=0.4.5
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torch==1.11
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monai==0.8.1
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nibabel
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pillow
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itk==5.2.0.post1
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vispy>=0.9.6

tox.ini

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# For more information about tox, see https://tox.readthedocs.io/en/latest/
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[tox]
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envlist = py{38,39}-{linux,macos,windows}
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envlist = py{38}-{windows}
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isolated_build=true
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[gh-actions]
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python =
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; 3.8: py38
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3.9: py39
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; 3.10: py310
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3.8: py38
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[gh-actions:env]
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PLATFORM =
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ubuntu-latest: linux
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macos-latest: macos
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; ubuntu-latest: linux
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; macos-latest: macos
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windows-latest: windows
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[testenv]
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platform =
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macos: darwin
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linux: linux
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; macos: darwin
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; linux: linux
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windows: win32
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passenv =
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CI
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NUMPY_EXPERIMENTAL_ARRAY_FUNCTION
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PYVISTA_OFF_SCREEN
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deps =
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-rrequirements.txt
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pytest # https://docs.pytest.org/en/latest/contents.html
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pytest-cov # https://pytest-cov.readthedocs.io/en/latest/
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; # you can remove these if you don't use them

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