Merge branch 'main' into fix_tests

haesleinhuepf · Dec 28, 2022 · 0c4edb7 · 0c4edb7
2 parents 8ccfe4e + 75771ba
commit 0c4edb7
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Showing 9 changed files with 437 additions and 20 deletions.
diff --git a/images/object_classifier_gui.png b/images/object_classifier_gui.png
diff --git a/napari_accelerated_pixel_and_object_classification/__init__.py b/napari_accelerated_pixel_and_object_classification/__init__.py
@@ -1,7 +1,7 @@
 try:
     from ._version import version as __version__
 except ImportError:
-    __version__ = "0.11.1"
+    __version__ = "0.12.0"
 
 
 

diff --git a/napari_accelerated_pixel_and_object_classification/_dock_widget.py b/napari_accelerated_pixel_and_object_classification/_dock_widget.py
@@ -294,22 +294,14 @@ def train(self,
         print("Applying / prediction done.")
 
         short_filename = filename.split("/")[-1]
-        self._add_to_viewer("Result of " + short_filename, result, scale)
+        _add_to_viewer(self.viewer, self.classifier_class == ProbabilityMapper, "Result of " + short_filename, result, scale)
 
         if show_classifier_statistics and self.viewer is not None:
             table = QTableWidget()
             update_model_analysis(table, classifier)
             self.viewer.window.add_dock_widget(table)
 
-    def _add_to_viewer(self, name, data, scale=None):
-        try:
-            self.viewer.layers[name].data = data.astype(int)
-            self.viewer.layers[name].visible = True
-        except KeyError:
-            if self.classifier_class == ProbabilityMapper:
-                self.viewer.add_image(data, name=name)
-            else:
-                self.viewer.add_labels(data.astype(int), name=name, scale=scale)
+
 
     def predict(self, images, filename, scale=None):
         print("predict")
@@ -332,7 +324,7 @@ def predict(self, images, filename, scale=None):
 
         short_filename = filename.split("/")[-1]
 
-        self._add_to_viewer("Result of " + short_filename, result, scale=scale)
+        _add_to_viewer(self.viewer, self.classifier_class == ProbabilityMapper, "Result of " + short_filename, result, scale)
 
     def update_memory_consumption(self):
         number_of_pixels = np.sum(tuple([np.prod(i.shape) for i in self.get_selected_images_data()]))
@@ -555,9 +547,10 @@ def getFeatures(self):
 def napari_experimental_provide_dock_widget():
     # you can return either a single widget, or a sequence of widgets
     from ._function import Train_object_classifier
+    from ._object_classification_widget import ObjectClassification
     from ._custom_table_row_classifier import CustomObjectClassifierWidget
     from ._object_merger import Train_object_merger
-    return [ObjectSegmentation, SemanticSegmentation, Train_object_classifier, CustomObjectClassifierWidget, Train_object_merger]
+    return [ObjectSegmentation, SemanticSegmentation, CustomObjectClassifierWidget, Train_object_merger, ObjectClassification]
 
 
 def set_border(widget:QWidget, spacing=2, margin=0):
@@ -566,3 +559,12 @@ def set_border(widget:QWidget, spacing=2, margin=0):
     if hasattr(widget.layout(), "setSpacing"):
         widget.layout().setSpacing(spacing)
 
+def _add_to_viewer(viewer, as_image, name, data, scale=None):
+    try:
+        viewer.layers[name].data = data.astype(int)
+        viewer.layers[name].visible = True
+    except KeyError:
+        if as_image:
+            viewer.add_image(data, name=name, scale=scale)
+        else:
+            viewer.add_labels(data.astype(int), name=name, scale=scale)
diff --git a/napari_accelerated_pixel_and_object_classification/_function.py b/napari_accelerated_pixel_and_object_classification/_function.py
@@ -1,4 +1,6 @@
-from apoc import PredefinedFeatureSet, PixelClassifier, ObjectSegmenter, ObjectClassifier, ProbabilityMapper
+import warnings
+
+from apoc import PredefinedFeatureSet, PixelClassifier, ObjectSegmenter, ObjectClassifier, ObjectSelector, ProbabilityMapper
 
 import numpy as np
 from napari_plugin_engine import napari_hook_implementation
@@ -191,7 +193,7 @@ def Connected_component_labeling(labels: "napari.types.LabelsData", object_class
         instances = cle.connected_components_labeling_box(binary)
     return instances
 
-@register_dock_widget(menu="Segmentation post-processing > Object classification (APOC)")
+@register_dock_widget(menu="Segmentation post-processing > Object classification (deprecated, APOC)")
 @magic_factory(
     model_filename=dict(widget_type='FileEdit', mode='w'),
     shape_extension_ratio=dict(label='shape (extension ratio)')
@@ -223,7 +225,7 @@ def Train_object_classifier(image: "napari.types.ImageData",
                             show_feature_correlation_matrix=False,
                             viewer : "napari.Viewer" = None
                             ) -> "napari.types.LabelsData":
-
+    warnings.warn("This function is deprecated. Use the classes in the APOC package instead.", DeprecationWarning)
     features = ","
     if pixel_count:
         features = features + "area,"
@@ -318,6 +320,17 @@ def Apply_object_classification(image: "napari.types.ImageData",
     result = clf.predict(labels, image)
     return result
 
+@register_function(menu="Segmentation post-processing > Object selection (apply pretrained, APOC)")
+@time_slicer
+def Apply_object_classification(image: "napari.types.ImageData",
+                             labels: "napari.types.LabelsData",
+                             model_filename : str = "ObjectSelector.cl",
+                             viewer: napari.Viewer = None) -> "napari.types.LabelsData":
+
+    clf = ObjectSelector(opencl_filename=model_filename)
+    result = clf.predict(labels, image)
+    return result
+
 @register_function(menu="Measurement > Annotation to cluster ID column (APOC)")
 def annotation_to_cluster_id(labels: "napari.types.LabelsData", annotation: "napari.types.LabelsData", name:str="ANNOTATION", viewer:napari.Viewer=None):
     import pyclesperanto_prototype as cle