To give more options for object classification while maintaining the installability of apoc, it might make sense to setup a second ObjectClassfier, that uses internally the regionprops from SimpleITK.
We could then classify objects accorind to their
- maximum
- mean
- median
- minimum
- sigma
- sum
- variance
- bbox
- centroid_0
- elongation
- feret_diameter
- flatness
- roundness
- equivalent_ellipsoid_diameter_0
- equivalent_ellipsoid_diameter_1
- equivalent_spherical_perimeter
- equivalent_spherical_radius
- number_of_pixels
- number_of_pixels_on_border
- perimeter
- perimeter_on_border
- perimeter_on_border_ratio
- principal_axes0
- principal_axes1
- principal_axes2
- principal_axes3
- principal_moments0
- principal_moments1
We could alternatively build this in optionally in the existing object classifier. The user-interface in napari may need a major redesign for this.
See also:
https://github.com/haesleinhuepf/napari-simpleitk-image-processing/blob/main/src/napari_simpleitk_image_processing/_simpleitk_image_processing.py#L789
To give more options for object classification while maintaining the installability of apoc, it might make sense to setup a second ObjectClassfier, that uses internally the regionprops from SimpleITK.
We could then classify objects accorind to their
We could alternatively build this in optionally in the existing object classifier. The user-interface in napari may need a major redesign for this.
See also:
https://github.com/haesleinhuepf/napari-simpleitk-image-processing/blob/main/src/napari_simpleitk_image_processing/_simpleitk_image_processing.py#L789