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Additional Widgets

Widget: Add Custom Model

Screenshot

Screenshot

None
  • New model name: None
  • Model location: None
  • Voxel Size: Resolution of the dataset used to model in micrometers per pixel.
  • Description: None
  • Dimensionality: Dimensionality of the model (2D or 3D). Any 2D model can be used for 3D data.
  • Microscopy modality: Modality of the model (e.g. confocal, light-sheet ...).
  • Prediction type: Type of prediction (e.g. cell boundaries prediction or nuclei...).

Widget: Lifted Multi-Cut

As reported in our paper, if one has a nuclei signal imaged together with the boundary signal, we could leverage the fact that one cell contains only one nucleus and use the LiftedMultict segmentation strategy and obtain improved segmentation.

Traceback (most recent call last):
  File "/usr/share/miniconda/envs/plant-seg/lib/python3.12/site-packages/markdown_exec/_internal/formatters/python.py", line 71, in _run_python
    exec_python(code, code_block_id, exec_globals)
  File "/usr/share/miniconda/envs/plant-seg/lib/python3.12/site-packages/markdown_exec/_internal/formatters/_exec_python.py", line 8, in exec_python
    exec(compiled, exec_globals)  # noqa: S102
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "<code block: n2>", line 8, in <module>
    from plantseg.viewer_napari.widgets import widget_lifted_multicut
ImportError: cannot import name 'widget_lifted_multicut' from 'plantseg.viewer_napari.widgets' (/usr/share/miniconda/envs/plant-seg/lib/python3.12/site-packages/plantseg/viewer_napari/widgets/__init__.py)