Merge branch 'main' into cy/v0.2.0

Author: C-Achard

.github/workflows/test_and_deploy.yml

@@ -7,7 +7,6 @@ on:
   push:
     branches:
       - main
-      - cy/training
     tags:
       - "v*" # Push events to matching v*, i.e. v1.0, v20.15.10
   pull_request:

.gitignore

@@ -126,6 +126,7 @@ wandb/
 !napari_cellseg3d/_tests/res/wnet_test/*.tif
 !napari_cellseg3d/_tests/res/wnet_test/lab/*.tif
 !napari_cellseg3d/_tests/res/wnet_test/vol/*.tif
+!examples/*
 
 #include docs images
 !docs/source/logo/*

.napari/DESCRIPTION.md

@@ -117,7 +117,7 @@ this information here.
 ## Getting Help
 
 If you would like to report an issue with the plugin,
-please open an [issue on Github](https://github.com/AdaptiveMotorControlLab/CellSeg3d/issues)
+please open an [issue on Github](https://github.com/AdaptiveMotorControlLab/CellSeg3D/issues)
 <!--
 This section should point users to your preferred support tools, whether this be raising
 an issue on GitHub, asking a question on image.sc, or using some other method of contact.

.napari/config.yml

@@ -2,11 +2,11 @@ visibility: public
 # note : remember to add napari-hub preview app to repo
 
 project_urls:
-  Bug Tracker: https://github.com/AdaptiveMotorControlLab/CellSeg3d/issues
-  Documentation: https://adaptivemotorcontrollab.github.io/CellSeg3d/res/welcome.html
-  Source Code: https://github.com/AdaptiveMotorControlLab/CellSeg3d
-  Project Site: https://github.com/AdaptiveMotorControlLab/CellSeg3d
-  User Support: https://github.com/AdaptiveMotorControlLab/CellSeg3d/issues
+  Bug Tracker: https://github.com/AdaptiveMotorControlLab/CellSeg3D/issues
+  Documentation: https://adaptivemotorcontrollab.github.io/CellSeg3D/res/welcome.html
+  Source Code: https://github.com/AdaptiveMotorControlLab/CellSeg3D
+  Project Site: https://github.com/AdaptiveMotorControlLab/CellSeg3D
+  User Support: https://github.com/AdaptiveMotorControlLab/CellSeg3D/issues
 
 # Add labels from the EDAM Bioimaging ontology
 labels:

CODE_OF_CONDUCT.md

@@ -0,0 +1,76 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+In the interest of fostering an open and welcoming environment, we as
+contributors and maintainers pledge to making participation in our project and
+our community a harassment-free experience for everyone, regardless of age, body
+size, disability, ethnicity, sex characteristics, gender identity and expression,
+level of experience, education, socio-economic status, nationality, personal
+appearance, race, religion, or sexual identity and orientation.
+
+## Our Standards
+
+Examples of behavior that contributes to creating a positive environment
+include:
+
+* Using welcoming and inclusive language
+* Being respectful of differing viewpoints and experiences
+* Gracefully accepting constructive criticism
+* Focusing on what is best for the community
+* Showing empathy towards other community members
+
+Examples of unacceptable behavior by participants include:
+
+* The use of sexualized language or imagery and unwelcome sexual attention or
+ advances
+* Trolling, insulting/derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or electronic
+ address, without explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+ professional setting
+
+## Our Responsibilities
+
+Project maintainers are responsible for clarifying the standards of acceptable
+behavior and are expected to take appropriate and fair corrective action in
+response to any instances of unacceptable behavior.
+
+Project maintainers have the right and responsibility to remove, edit, or
+reject comments, commits, code, wiki edits, issues, and other contributions
+that are not aligned to this Code of Conduct, or to ban temporarily or
+permanently any contributor for other behaviors that they deem inappropriate,
+threatening, offensive, or harmful.
+
+## Scope
+
+This Code of Conduct applies both within project spaces and in public spaces
+when an individual is representing the project or its community. Examples of
+representing a project or community include using an official project e-mail
+address, posting via an official social media account, or acting as an appointed
+representative at an online or offline event. Representation of a project may be
+further defined and clarified by project maintainers.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported by contacting the project team at [email protected]. All
+complaints will be reviewed and investigated and will result in a response that
+is deemed necessary and appropriate to the circumstances. The project team is
+obligated to maintain confidentiality with regard to the reporter of an incident.
+Further details of specific enforcement policies may be posted separately.
+
+Project maintainers who do not follow or enforce the Code of Conduct in good
+faith may face temporary or permanent repercussions as determined by other
+members of the project's leadership.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
+available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
+
+[homepage]: https://www.contributor-covenant.org
+
+For answers to common questions about this code of conduct, see
+https://www.contributor-covenant.org/faq

README.md

@@ -5,9 +5,9 @@
 [![PyPI](https://img.shields.io/pypi/v/napari-cellseg3d.svg?color=green)](https://pypi.org/project/napari-cellseg3d)
 [![Downloads](https://static.pepy.tech/badge/napari-cellseg3d)](https://pepy.tech/project/napari-cellseg3d)
 [![Downloads](https://static.pepy.tech/badge/napari-cellseg3d/month)](https://pepy.tech/project/napari-cellseg3d)
-[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/AdaptiveMotorControlLab/CellSeg3d/raw/main/LICENSE)
+[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/AdaptiveMotorControlLab/CellSeg3D/raw/main/LICENSE)
 [![Python Version](https://img.shields.io/pypi/pyversions/napari-cellseg-annotator.svg?color=green)](https://python.org)
-[![codecov](https://codecov.io/gh/AdaptiveMotorControlLab/CellSeg3d/branch/main/graph/badge.svg?token=hzUcn3XN8F)](https://codecov.io/gh/AdaptiveMotorControlLab/CellSeg3d)
+[![codecov](https://codecov.io/gh/AdaptiveMotorControlLab/CellSeg3D/branch/main/graph/badge.svg?token=hzUcn3XN8F)](https://codecov.io/gh/AdaptiveMotorControlLab/CellSeg3D)
 [![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-cellseg3d)](https://www.napari-hub.org/plugins/napari-cellseg3d)
 
 - A napari plugin for 3D cell segmentation: training, inference, and data review. In particular, this project was developed for analysis of mesoSPIM-acquired (cleared tissue + lightsheet) datasets.
@@ -20,7 +20,7 @@
 
 ## Documentation
 
-📚 A lot of documentation is available at https://AdaptiveMotorControlLab.github.io/CellSeg3d
+📚 A lot of documentation is available at https://AdaptiveMotorControlLab.github.io/CellSeg3D
 
 You can also generate docs by running ``make html`` in the docs/ folder.
 
@@ -62,39 +62,48 @@ Previous additions :
 
 
 
-### Install note for M1/M2 Mac users
+### Install note for ARM64 (Silicon) Mac users
 
 To avoid issues when installing on the ARM64 architecture, please follow these steps.
 
-1) Create a new conda env using the provided conda/napari_cellseg3d_m1.yml file :
+1) Create a new conda env using the provided conda/napari_CellSeg3D_ARM64.yml file :
 
         git clone https://github.com/AdaptiveMotorControlLab/CellSeg3d.git
         cd CellSeg3d
-        conda env create -f conda/napari_cellseg3d_m1.yml
-        conda activate napari_cellseg3d_m1
+        conda env create -f conda/CellSeg3D_ARM64.yml
+        conda activate napari_CellSeg3D_ARM64
 
-2) Install the plugin.
-   From repository root folder, run :
 
-        pip install -e .
-   OR directly via PyPi :
+2) Install a Qt backend (PySide or PyQt5)
+3) Launch napari, the plugin should be available in the plugins menu.
 
-        pip install napari-cellseg3d
-
-   OR directly via [napari-hub] (see Installation section above)
 
 
 ## Requirements
 
 **Python 3.8 or 3.9 required.**
 Requires **[napari]**, **[PyTorch]** and **[MONAI]**.
+Compatible with Windows, MacOS and Linux.
+Installation should not take more than 30 minutes, depending on your internet connection.
 
 For PyTorch, please see [the PyTorch website for installation instructions].
 
 A CUDA-capable GPU is not needed but very strongly recommended, especially for training.
 
 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.
 
+## Quick demo
+
+After installation, you can run the plugin by running:
+
+        napari
+
+and launching the plugin from the Plugins menu.
+You may use the test volume in the `examples` folder to test the inference and review tools.
+This should run in far less than five minutes on a modern computer.
+
+You may also find a demo Colab notebook in the `notebooks` folder.
+
 ## Issues
 
 **Help us make the code better by reporting issues and adding your feature requests!**
@@ -134,7 +143,7 @@ Distributed under the terms of the [MIT] license.
 
 [napari-hub]: https://www.napari-hub.org/plugins/napari-cellseg3d
 
-[file an issue]: https://github.com/AdaptiveMotorControlLab/CellSeg3d/issues
+[file an issue]: https://github.com/AdaptiveMotorControlLab/CellSeg3D/issues
 [napari]: https://github.com/napari/napari
 [Cookiecutter]: https://github.com/audreyr/cookiecutter
 [@napari]: https://github.com/napari
@@ -143,7 +152,7 @@ Distributed under the terms of the [MIT] license.
 [tox]: https://tox.readthedocs.io/en/latest/
 [pip]: https://pypi.org/project/pip/
 [PyPI]: https://pypi.org/
-[Installation page]: https://adaptivemotorcontrollab.github.io/CellSeg3d/source/guides/installation_guide.html
+[Installation page]: https://adaptivemotorcontrollab.github.io/CellSeg3D/source/guides/installation_guide.html
 [the PyTorch website for installation instructions]: https://pytorch.org/get-started/locally/
 [PyTorch]: https://pytorch.org/get-started/locally/
 [MONAI's optional dependencies]: https://docs.monai.io/en/stable/installation.html#installing-the-recommended-dependencies

conda/napari_cellseg3d_m1.yml renamed to conda/napari_CellSeg3D_ARM64.yml

@@ -1,4 +1,4 @@
-name: napari_cellseg3d_m1
+name: napari_CellSeg3D_ARM64
 channels:
   - anaconda
   - conda-forge
@@ -11,18 +11,14 @@ dependencies:
     - pip:
         - numpy
         - napari>=0.4.14
-        # - opencv-python>=4.5.5
         - scikit-image>=0.19.2
         - matplotlib>=3.4.1
         - tifffile>=2022.2.9
-        # - imageio-ffmpeg>=0.4.5
         - torch>=1.11
         - monai[nibabel, einops]>=0.9.0
         - tqdm
-        # - nibabel
         - scikit-image
-        # - pillow
         - pyclesperanto-prototype
         - tqdm
         - matplotlib
-        # - vispy>=0.9.6
+        - napari_cellseg3d

docs/_config.yml

@@ -21,7 +21,7 @@ bibtex_bibfiles:
 
 # Information about where the book exists on the web
 repository:
-  url: https://github.com/AdaptiveMotorControlLab/CellSeg3d  # Online location of your book
+  url: https://github.com/AdaptiveMotorControlLab/CellSeg3D  # Online location of your book
   path_to_book: docs  # Optional path to your book, relative to the repository root
   branch: main  # Which branch of the repository should be used when creating links (optional)
 

docs/source/guides/custom_model_template.rst

@@ -31,4 +31,4 @@ To add a custom model, you will need a **.py** file with the following structure
 .. note::
     **WIP** : Currently you must modify :doc:`model_framework.py <../code/_autosummary/napari_cellseg3d.code_models.model_framework>` as well : import your model class and add it to the ``model_dict`` attribute
 
-.. _file an issue: https://github.com/AdaptiveMotorControlLab/CellSeg3d/issues
+.. _file an issue: https://github.com/AdaptiveMotorControlLab/CellSeg3D/issues

docs/source/guides/detailed_walkthrough.rst

@@ -32,6 +32,11 @@ For quick model checks, check the "Inference" sections in our docs.
   If you need to start labeling volumes from scratch or correct initial labels, we recommend consulting the sections on :ref:`Review<walkthrough_reviewing>` section right after :ref:`Cropping <walkthrough_cropping>`.
 
 
+Launching the plugin
+************************
+
+See `Usage section <https://adaptivemotorcontrollab.github.io/CellSeg3D/welcome.html#usage>`_ for instructions on launching the plugin.
+
 Cropping
 *********
 .. _walkthrough_cropping:
@@ -202,7 +207,7 @@ To visualise some of the results when running on a folder, you can leave the **V
 .. note::
     Too plot your results, check out the `provided notebooks`_
 
-.. _provided notebooks: https://github.com/AdaptiveMotorControlLab/CellSeg3d/tree/main/notebooks
+.. _provided notebooks: https://github.com/AdaptiveMotorControlLab/CellSeg3D/tree/main/notebooks
 
 
 You can then launch inference and the results will be saved in your specified folder.
@@ -266,6 +271,6 @@ for the plots to work.
    Example of the plot present in the notebooks.
    Coordinates are based on centroids, the size represents the volume, the color, and the sphericity.
 
-.. _notebooks folder of the repository: https://github.com/AdaptiveMotorControlLab/CellSeg3d/tree/main/notebooks
+.. _notebooks folder of the repository: https://github.com/AdaptiveMotorControlLab/CellSeg3D/tree/main/notebooks
 
 With this complete, you can repeat the workflow as needed.

docs/source/guides/inference_module_guide.rst

@@ -11,6 +11,9 @@ Inference📊
 **Inference** allows you to use pre-trained segmentation algorithms, written in Pytorch,
 to automatically label cells in 3D volumes.
 
+See `Usage section <https://adaptivemotorcontrollab.github.io/CellSeg3d/welcome.html#usage>`_ for instructions on launching the plugin.
+See :ref:`training_module_guide` for instructions on training your own models before inference.
+
 .. important::
     Currently, the module supports inference on **3D volumes**. When running on folders, make sure that your image folder
     only contains a set of **3D image files** saved with the **`.tif`** extension.