QuPath v0.4.0 Flavored Release

This release implements the awesome new changes that came with the release of QuPath 0.4.0 and the updated StarDist extension for it.

And this has also led to a couple of small modifications

1. Some Cellpose builder methods were removed in favor or a more flexible way of passing parameters
2. The new version of the extension only supports Cellpose versions above 2.0
3. You can now add any cellpose parameter using addParameter() in the builder
4. There is now a possibility for global normalization!

Check out the updated readme for further information and do not hesitate to go to https://forum.image.sc to discuss usage issues.

Object overlap, quality of life updates and new training option

This update fixes an issue in the way objects were being detected and re-added to QuPath.

It now follows much more closely what is done in the StarDist Extension and should result in fewer issues.

Now the Z and T positions are also appended to the names of the exported images. Useful for 3D and T stacks

Adds the min_training_masks option to help avoid cellpose from excluding images with less than 5 annotations during training

Finally, it adds a bit more verbosity. The full command used to run or train is output in such a way that it can be run from the command line by copy-paste

You should unzip the contents of the file below into your extensions directory

Improved Integrated Quality Control

This release builds on v0.4.0 #7365020 following comments by @romainGuiet to integrate the whole QC directly rather than run it separately (Which no-one will ever do until it's too late 😅).

Improvements

Quality control is perfomed after training provided that:

1. You added the scikit-image dependency to your cellpose installation
2. You copy run-cellpose-qc.py into your QuPath extensions folder

Read the updated ReadMe to see how to do these installation steps.
Here is an example gif in real time (only 100 epochs though)

Possibility to save the training graph as a PNG in your QuPath project's QC folder

On top of showing you the training graph if you request it after training using showTrainingGraph(),
you can also choose to save it but not show it using showTrainingGraph(boolean show, boolean save)

Updated JavaDoc and ReadMe to account for the new features

As ususal, JavaDoc is here: https://biop.github.io/qupath-extension-cellpose/qupath/ext/biop/cellpose

Always happy to receive comments and suggestions!

Adds Quality Control Notebook and Training now also saves Validation Predictions

Please see the forum post for more information
https://forum.image.sc/t/qupath-extension-cellpose-update-validation/71320

Also adds a fix to how the QuPath Proejct is recovered when training from another thread (Like when creating a button dynamically)

Project path inference update

Following the discussions on the Image.sc forum
https://forum.image.sc/t/create-a-shortcut-button-to-run-a-script/71195

And the PR #14 by @zindy, a better way to figure out where the project directory has been implemented.

This release corrects an incorrect overlap being set to 0 instead of the default due to my messing up boxed and unboxed doubles and ints.

Improved documentation, the return of normalization

This release tackles the following aspects

• Erroneous message informing that an unimplemented 'global normalization' was being performed on downsampled data
• Update to documentation with Cellpose installation instructions and practical information
• Adds an updated JavaDoc
• Adds the option to normalize in QuPath by clipping values below 0.0 and above 1.0 after calling normalizePercentiles(double min, double max) in the builder.

Note
This implies that the order of normalizePercentiles(double min, double max) and preprocess() is important. Always finish with the normalization if using `preprocess()

Please read the updated documentation for some more small details

New Way to call cellpose

Inspired by the TrackMate-Cellpose and the following issue #12

This update adds the possibility to simply add the complete path to your python executable in order to run cellpose.

This also includes a fix that allows QuPath projects to have whitespaces in their path on Linux/MacOS .

Cellpose 2.0, with fewer bugs

Thanks to the community some bugs were spotted and fixed.

Improved training verbose support

This fixes training when using cellpose 1.0 as there was no output

Support for Cellpose 1.0

Adds option to Cellpose preferences for cellpose 1.0
Adds --verbose flag when using cellpose 1.0
Removes --resample flag