Empanada-napari

First official release of the empanada-napari code on Zenodo.

New Features

- Added "Apply in 3D" option to proofreading tools. This enables faster proofreading of stacks of 2D images and flipbooks.
- Added merging from line and path shapes.
- Metadata generated for instance segmentations (like number of voxels and bounding boxes) are now attached for model predictions.
- Added tiled 2D inference for processing very large 2D images and "viewport" inference for testing models on small ROIs of much larger images.
- More operations now support multiscale datasets with scale and translation metadata.
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Bug Fixes

- Fixed bug that prevent export of models trained and fine-tuned on CPU.
- Fixed bug in the "Use points as markers" split option that caused inconsistent results when applied to 2D images translated in 3D.

**Full Changelog**: https://github.com/volume-em/empanada-napari/compare/v0.2.0...v0.2.1

What's Changed
* Finetuning support by conradry in https://github.com/volume-em/empanada-napari/pull/12
**Full Changelog**: https://github.com/volume-em/empanada-napari/compare/v0.1.4...v0.2.0

New tutorials and detailed usage notes at: https://empanada.readthedocs.io/en/latest/empanada-napari.html

New Features

- Added the MitoNet_v1_mini model which uses BiFPN modules for parameter efficiency.
- Added support to easily pick training data from an individual or stack of 2D images and 3D volumes (isotropic and anisotropic). Allows manual selection of ROIs from dropped points.
- Added module to store annotated training data in the directory format expected by empanada.
- Added support for fine-tuning any existing models.
- Added module to print out descriptions of any registered models to aid in the preparation of fine-tuning datasets.
- Added support for training panoptic segmentation models from scratch or from CEM1.5M pre-trained weights.
- Updated the Register new model module to allow for remote (URL) model files. Switched from requiring a zip file to model config and paths to torch scripted models.
- Modified model config files to include a FINETUNE section with relevant (hyper)parameters.

Bug Fixes

- Fixed SIGABRT during multi-gpu inference.

New Features

- More stable multi-gpu inference.
- Improved integration with the empanada library
- Default instance splitting uses distance watershed instead of marker watershed
- Jump to labels module to move slider to first slice where a particular object id appears
- Improved postprocessing of semantic and instance segmentation classes after panoptic segmentation
- Added option to choose inference axis in 3D (i.e., xy, xz, or yz)

Bug Fixes

- Hard-coded merge_iou_thr and merge_ioa_thr. Removed from the update_params method on Engine3d.

New Features

- Added support for running 2d inference in batch mode on a stack of images (optionally loaded from a folder).
- Converted to npe2 with napari.yaml manifest.

Stable napari plugin