Deepcell

Latest version: v0.12.9

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0.11.2

🧰 Maintenance

<details>
<summary>Update MultiplexSegmentation model msschwartz21 (592)</summary>

Update the mesmer model from model-registry15. I'll leave this PR as a draft until ngreenwald has a chance to test post-processing parameters and determine if any changes are needed.
</details>

<details>
<summary>Update tracking parameters and hashes for new models MekWarrior (589)</summary>

What
* The nuclear tracking model has been updated in the model registry. This PR redirects the current pointers to grab this new version. The division parameter has also been updated to match the result of the latest parameter sweep.

Why
* The applications should match the latest verified version from the model registry.

</details>


📚️ Documentation

<details>
<summary>Pin `jinja2<3.1` to restore functional docs builds msschwartz21 (590)</summary>

What
* Pins `jinja2<3.1` in `docs/requirements-docs.txt`

Why
* The new `jinja2` release deprecates functions that are required for `sphinx`.
</details>

<details>
<summary>Update license badge ("Modified Apache 2.0") joshmoore (586)</summary>

All-

Someone in the OME community recently ran into some confusion with the licensing of deepcell-tf. The license badge lists "Apache 2.0" but the LICENSE file states "Modified Apache 2.0". This proposes use of [![Modified Apache 2.0](https://img.shields.io/badge/license-Modified%20Apache%202-blue)](https://img.shields.io/badge/license-Modified%20Apache%202-blue) to increase the clarity.

All the best,
~Josh Moore

<details><summary><code>diff LICENSE-2.0.txt LICENSE</code></summary>


--- LICENSE-2.0.txt 2022-04-01 14:41:12.806279265 +0100
+++ LICENSE 2022-04-01 14:41:45.921931426 +0100
-1,7 +1,5
-
- Apache License
+ Modified Apache License
Version 2.0, January 2004
- http://www.apache.org/licenses/

TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION

-65,18 +63,19
subsequently incorporated within the Work.

2. Grant of Copyright License. Subject to the terms and conditions of
- this License, each Contributor hereby grants to You a perpetual,
- worldwide, non-exclusive, no-charge, royalty-free, irrevocable
- copyright license to reproduce, prepare Derivative Works of,
- publicly display, publicly perform, sublicense, and distribute the
- Work and such Derivative Works in Source or Object form.
+ this License, each Contributor hereby grants to You a non-commercial,
+ academic perpetual, worldwide, non-exclusive, no-charge, royalty-free,
+ irrevocable copyright license to reproduce, prepare Derivative Works
+ of, publicly display, publicly perform, sublicense, and distribute the
+ Work and such Derivative Works in Source or Object form. For any other
+ use, including commercial use, please contact: vanvalenlabgmail.com.

3. Grant of Patent License. Subject to the terms and conditions of
- this License, each Contributor hereby grants to You a perpetual,
- worldwide, non-exclusive, no-charge, royalty-free, irrevocable
- (except as stated in this section) patent license to make, have made,
- use, offer to sell, sell, import, and otherwise transfer the Work,
- where such license applies only to those patent claims licensable
+ this License, each Contributor hereby grants to You a non-commercial,
+ academic perpetual, worldwide, non-exclusive, no-charge, royalty-free,
+ irrevocable (except as stated in this section) patent license to make,
+ have made, use, offer to sell, sell, import, and otherwise transfer the
+ Work, where such license applies only to those patent claims licensable
by such Contributor that are necessarily infringed by their
Contribution(s) alone or by combination of their Contribution(s)
with the Work to which such Contribution(s) was submitted. If You
-174,6 +173,10
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.

+ 10. Neither the name of Caltech nor the names of its contributors may be
+ used to endorse or promote products derived from this software without
+ specific prior written permission.
+
END OF TERMS AND CONDITIONS

APPENDIX: How to apply the Apache License to your work.


</details>

</details>

0.11.1

Not secure
🐛 Bug Fixes

<details>
<summary>Updated `deepcell_tracking.utils` to `deepcell.data.tracking` for importing `Track` and `concat_tracks` ulisrael (565)</summary>

What
* Updated the tracking notebook so `Track` and `concat_tracks` were imported from `deepcell.data.tracking`

Why
* The location of these files changed in the latest version of deepcell

</details>


🧰 Maintenance

<details>
<summary>Bump version to 0.11.1 msschwartz21 (585)</summary>

* Update copyright in `deepcell/_version.py` to 2022
</details>

<details>
<summary>Add option for graph attention layer to tracking model msschwartz21 (584)</summary>

What
* Exposes an option to use the graph attention layer `GATConv` from `spektral`

Why
* Allows us to test the impact of different graph layers on the tracking model

</details>

<details>
<summary>Update nuclear and cytoplasm segmentation models from the data-registry msschwartz21 (580)</summary>

* Updates nuclear segmentation model with the version created by https://github.com/vanvalenlab/data-registry/pull/188
* Update cytoplasm segmentation model with the version created by https://github.com/vanvalenlab/data-registry/pull/164

The same models have been uploaded to the deepcell-models bucket in GCP for deployment through the kiosk.
</details>

<details>
<summary>Build a Docker image and run tests in the container. willgraf (575)</summary>

What
* Add a new GitHub workflow to build a docker image and run the unit tests inside it.

Why
* This ensures that the docker images work as expected rather than relying solely on the tests passing in the test-runner environment.

</details>

<details>
<summary>Update README with TissueNet publication ngreenwald (571)</summary>

What
* Update the ReadMe with the link for the paper

Why
* I'll merge this in tomorrow AM once the link goes live

</details>

<details>
<summary><s>Revert to TensorFlow 2.5.1. willgraf (570)</s></summary>

What
* Revert TensorFlow version from 2.5.2 to 2.5.1. The patch is already able to be installed via `setup.py` and `requirements.txt`.

Why
* No 2.5.2 docker images are available, the patch can be installed via pip.
* Fixes 568

</details>

<details>
<summary><s>Update tensorflow in requirements.txt willgraf (567)</s></summary>

What
* Fix bug in 566 with missing change in requirements.txt

Why
* Finish update of base TensorFlow version.

</details>

<details>
<summary><s>Bump TF_VERSION to 2.5.2. willgraf (566)</s></summary>

What
* Update TF_VERSION used to [2.5.2](https://github.com/tensorflow/tensorflow/releases/tag/v2.5.2)

Why
* Fixes several vulnerabilities

</details>

0.11.0

Not secure
🚀 Features

<details>
<summary>Move tracking data preprocessing into `deepcell.data.tracking` willgraf (554)</summary>

What
* Update the adjacency matrix data from to a sparse tensor to significantly reduce memory footprint.
* Move `Track` and `concat_tracks` functions from `deepcell-tracking` to `deepcell.data.tracking`. They are really just `.trk` preprocessing and are unnecessary outside of `prepare_data`.
* Update `temporal_slice` to not slice into padded frames.
* Bump `deepcell-tracking` to 0.5.0.

Why
* Continue to upgrade the tracking model to make it more usable.
* The `temporal_slice` fix should improve the precision metrics of the model by not training on padded data.

</details>

🐛 Bug Fixes

<details>
<summary>Update numpy version constraints in pyproject.toml willgraf (563)</summary>

What
* Update numpy version constraints to match setup.py.

Why
* Fixes 559.

</details>

<details>
<summary>Revert `deepcell.data.tracking.prepare_dataset` to process concatenated Tracks. willgraf (561)</summary>

What
* Revert the change to `prepare_dataset` that allows it to process .trks files.

Why
* This change caused complications downstream (primarily in using different train and val files) and is not useful.

</details>

<details>
<summary>Update the training a tracking model notebook. willgraf (558)</summary>

What
* Fix the `filter_and_flatten` function.
* Add the `graph_layer` argument to the model call.

Why
* This function was not filtering the padded data properly, fixing it resolves the training issues.
* Improve overall clarity of options for tracking models.
</details>


🧰 Maintenance

<details>
<summary>Bump the version to 0.11.0. willgraf (564)</summary>

What
* Update the package version to 0.11.0.

Why
* Getting ready for the next release.

</details>

<details>
<summary>Minor updates to README willgraf (562)</summary>

What
* Pin `docutils` to 0.16 to resolve readthedocs build failures
* Add a monthly downloads badge
* Clean up grammar and whitespace.

Why
* General improvement for the README

</details>

<details>
<summary>Update models to latest trained tracking model. willgraf (560)</summary>

What
* Retrain tracking models using SparseTensors

Why
* Provide the latest and greatest models in the next release.

</details>

0.11.0rc1

Not secure
🚀 Features

<details>
<summary>Move tracking data preprocessing into `deepcell.data.tracking` willgraf (554)</summary>

What
* Update the adjacency matrix data from to a sparse tensor to significantly reduce memory footprint.
* Move `Track` and `concat_tracks` functions from `deepcell-tracking` to `deepcell.data.tracking`. They are really just `.trk` preprocessing and are unnecessary outside of `prepare_data`.
* Update `temporal_slice` to not slice into padded frames.
* Bump `deepcell-tracking` to 0.5.0.

Why
* Continue to upgrade the tracking model to make it more usable.
* The `temporal_slice` fix should improve the precision metrics of the model by not training on padded data.

</details>

0.10.3

🐛 Bug Fixes

<details>
<summary>Pin `scikit-image` to < 0.19.0. willgraf (119)</summary>

Resolves a breaking change in the new release causing import issues.
</details>

0.10.2

Not secure
🐛 Bug Fixes

<details>
<summary>Update numpy version constraints in pyproject.toml willgraf (563)</summary>

What
* Update `numpy` version constraints to match `setup.py`.

Why
* Fixes Python 3.9 compatibility issue (559)

</details>

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