Orthogonal views

finn/_tests/test_viewer.py

@@ -33,9 +33,16 @@ def _assert_shortcuts_exist_for_each_action(type_):
     actions = _get_provider_actions(type_)
     shortcuts = {name.partition(":")[-1] for name in get_settings().shortcuts.shortcuts}
     shortcuts.update(func.__name__ for func in type_.class_keymap.values())
+
+    actions_to_skip = {
+        "center_cross_on_mouse"
+    }  # skip this action as we only bind it if the cross widget is imported
+
     for action in actions:
+        if action.__name__ in actions_to_skip:
+            continue  # Skip this action
         assert action.__name__ in shortcuts, (
-            f"missing shortcut for action '{action.__name__}' on '{type_.__name__}' is missing"
+            f"missing shortcut for action '{action.__name__}' on '{type_.__name__}'"
         )
 
 

finn/track_application_menus/main_app.py

@@ -1,25 +1,69 @@
+from qtpy.QtCore import Qt
 from qtpy.QtWidgets import (
+    QPushButton,
+    QSplitter,
     QVBoxLayout,
     QWidget,
 )
 
 import finn
 from finn.track_application_menus.menu_widget import MenuWidget
 from finn.track_data_views.views.tree_view.tree_widget import TreeWidget
+from finn.track_data_views.views.view_3d.orthogonal_views import OrthogonalViews
 
 
 class MainApp(QWidget):
     """Combines the different tracker widgets for faster dock arrangement"""
 
     def __init__(self, viewer: finn.Viewer):
         super().__init__()
+        self.viewer = viewer
+
+        self.viewer.dims.events.ndim.connect(self.dims_changed)
 
         self.menu_widget = MenuWidget(viewer)
+        self.orth_views = OrthogonalViews(viewer)
         tree_widget = TreeWidget(viewer)
 
+        self.splitter = QSplitter(Qt.Horizontal)  # Set orientation to horizontal
+        self.splitter.addWidget(self.orth_views)  # Add the orthogonal views
+        self.splitter.addWidget(self.menu_widget)  # Add the menu widget
+        self.splitter.setSizes([0, 300])
         viewer.window.add_dock_widget(tree_widget, area="bottom", name="Tree View")
 
         layout = QVBoxLayout()
-        layout.addWidget(self.menu_widget)
+
+        self.collapse_btn = QPushButton("Show/hide orthogonal views")
+        self.collapse_btn.clicked.connect(self.toggle_orth_views)
+
+        if self.viewer.dims.ndim < 3:
+            self.collapse_btn.hide()
+        layout.addWidget(self.collapse_btn)
+        layout.addWidget(self.splitter)
 
         self.setLayout(layout)
+
+    def toggle_orth_views(self):
+        """Show/Hide the orthogonal views depending on their current state"""
+
+        if self.splitter.sizes()[0] > 0:
+            self.splitter.setSizes([0, 300])
+            self.orth_views.hide()
+        else:
+            self.splitter.setSizes([300, 300])
+            self.orth_views.show()
+            self.adjustSize()
+
+    def dims_changed(self):
+        """Show/Hide the orthogonal views depending on the amount of dimensions
+        of the viewer"""
+
+        if self.viewer.dims.ndim > 2:
+            self.collapse_btn.show()
+            self.splitter.setSizes([300, 300])
+            self.orth_views.show()
+            self.adjustSize()
+        else:
+            self.collapse_btn.hide()
+            self.splitter.setSizes([0, 300])
+            self.orth_views.hide()

finn/track_application_menus/menu_widget.py

@@ -31,3 +31,4 @@ def __init__(self, viewer: finn.Viewer):
         self.setWidgetResizable(True)
 
         self.setLayout(layout)
+        self.setMinimumWidth(300)

finn/track_data_views/views/layers/contour_labels.py

@@ -0,0 +1,125 @@
+from __future__ import annotations
+
+import numpy as np
+from scipy import ndimage as ndi
+
+import finn
+from finn.layers.labels._labels_utils import (
+    expand_slice,
+)
+from finn.utils import DirectLabelColormap
+
+
+def get_contours(
+    labels: np.ndarray,
+    thickness: int,
+    background_label: int,
+    group_labels: list[int] | None = None,
+):
+    """Computes the contours of a 2D label image.
+
+    Parameters
+    ----------
+    labels : array of integers
+        An input labels image.
+    thickness : int
+        Controls the thickness of the inner boundaries. The outside thickness is always 1.
+        The final thickness of the contours will be `thickness + 1`.
+    background_label : int
+        That label is used to fill everything outside the boundaries.
+
+    Returns
+    -------
+    A new label image in which only the boundaries of the input image are kept.
+    """
+    struct_elem = ndi.generate_binary_structure(labels.ndim, 1)
+
+    thick_struct_elem = ndi.iterate_structure(struct_elem, thickness).astype(bool)
+
+    dilated_labels = ndi.grey_dilation(labels, footprint=struct_elem)
+    eroded_labels = ndi.grey_erosion(labels, footprint=thick_struct_elem)
+    not_boundaries = dilated_labels == eroded_labels
+
+    contours = labels.copy()
+    contours[not_boundaries] = background_label
+
+    # instead of filling with background label,
+    # fill the group label with their normal color
+    if group_labels is not None and len(group_labels) > 0:
+        group_mask = np.isin(labels, group_labels)
+        combined_mask = not_boundaries & group_mask
+        contours = np.where(combined_mask, labels, contours)
+
+    return contours
+
+
+class ContourLabels(finn.layers.Labels):
+    """Extended labels layer that allows to show contours
+    and filled labels simultaneously"""
+
+    @property
+    def _type_string(self) -> str:
+        return (
+            "labels"  # to make sure that the layer is treated as labels layer for saving
+        )
+
+    def __init__(
+        self,
+        data: np.array,
+        name: str,
+        opacity: float,
+        scale: tuple,
+        colormap: DirectLabelColormap,
+    ):
+        super().__init__(
+            data=data,
+            name=name,
+            opacity=opacity,
+            scale=scale,
+            colormap=colormap,
+        )
+
+        self.group_labels = None
+
+    def _calculate_contour(
+        self, labels: np.ndarray, data_slice: tuple[slice, ...]
+    ) -> np.ndarray | None:
+        """Calculate the contour of a given label array within the specified data slice.
+
+        Parameters
+        ----------
+        labels : np.ndarray
+            The label array.
+        data_slice : Tuple[slice, ...]
+            The slice of the label array on which to calculate the contour.
+
+        Returns
+        -------
+        Optional[np.ndarray]
+            The calculated contour as a boolean mask array.
+            Returns None if the contour parameter is less than 1,
+            or if the label array has more than 2 dimensions.
+        """
+
+        if self.contour < 1:
+            return None
+        if labels.ndim > 2:
+            return None
+
+        expanded_slice = expand_slice(data_slice, labels.shape, 1)
+        sliced_labels = get_contours(
+            labels[expanded_slice],
+            self.contour,
+            self.colormap.background_value,
+            self.group_labels,
+        )
+
+        # Remove the latest one-pixel border from the result
+        delta_slice = tuple(
+            slice(s1.start - s2.start, s1.stop - s2.start)
+            for s1, s2 in zip(data_slice, expanded_slice, strict=False)
+        )
+        return sliced_labels[delta_slice]
+
+    def set_group_labels(self, labels: list[int] | None = None):
+        self.group_labels = labels