return layers instead of LayerDataTuples

brainglobe_template_builder/napari/_widget.py

@@ -6,12 +6,11 @@
 
 Replace code below according to your needs.
 """
-from typing import Literal, Union
+from typing import Literal
 
 import numpy as np
 from magicgui import magic_factory
 from napari.layers import Image, Labels, Points
-from napari.types import LayerDataTuple
 from napari_plugin_engine import napari_hook_implementation
 
 from brainglobe_template_builder.utils import (
@@ -46,7 +45,7 @@ def mask_widget(
     gauss_sigma: float = 3,
     threshold_method: Literal["triangle", "otsu", "isodata"] = "triangle",
     erosion_size: int = 5,
-) -> Union[LayerDataTuple, None]:
+) -> Labels:
     """Threshold image and create a mask for the largest object.
 
     The mask is generated by applying a Gaussian filter to the image,
@@ -70,8 +69,8 @@ def mask_widget(
 
     Returns
     -------
-    napari.types.LayerDataTuple
-        A napari Labels layer containing the mask.
+    napari.layers.Labels
+        A napari labels layer containing the mask.
     """
 
     if image is not None:
@@ -99,17 +98,15 @@ def mask_widget(
         mask = morphology.binary_erosion(
             mask, footprint=np.ones((erosion_size,) * image.ndim)
         )
-
-    # return the mask as a napari Labels layer
-    return (mask, {"name": "mask", "opacity": 0.5}, "labels")
+    return Labels(mask, opacity=0.5, name="mask")
 
 
 @magic_factory(
     call_button="Estimate midline points",
 )
 def points_widget(
     mask: Labels,
-) -> LayerDataTuple:
+) -> Points:
     """Create a points layer with 9 midline points.
 
     Parameters
@@ -119,8 +116,8 @@ def points_widget(
 
     Returns
     -------
-    napari.types.LayerDataTuple
-        A napari Points layer containing the estimated midline points.
+    napari.layers.Points
+        A napari points layer containing the midline points.
     """
 
     # Estimate 9 midline points
@@ -143,7 +140,7 @@ def points_widget(
     # Make mask layer invisible
     mask.visible = False
 
-    return (points, point_attrs, "points")
+    return Points(points, **point_attrs)
 
 
 @magic_factory(
@@ -156,7 +153,7 @@ def transform_widget(
     image: Image,
     points: Points,
     axis: Literal["x", "y", "z"] = "x",
-) -> LayerDataTuple:
+) -> Image:
     """Transform image to align points with midline of the specified axis.
 
     It first fits a plane to the points, then rigidly transforms the image
@@ -174,8 +171,8 @@ def transform_widget(
 
     Returns
     -------
-    napari.types.LayerDataTuple
-        A napari Image layer containing the transformed image.
+    napari.layers.Image
+        A napari image layer containing the transformed image.
     """
 
     from scipy.ndimage import affine_transform
@@ -224,7 +221,7 @@ def transform_widget(
         transformation_matrix[:3, :3],
         offset=transformation_matrix[:3, 3],
     )
-    return (transformed_image, {"name": "transformed image"}, "image")
+    return Image(transformed_image, name="aligned image")
 
 
 @napari_hook_implementation