Update plugins WIP

Author: constantinpape

run_correction.sh

@@ -5,10 +5,10 @@ categories: ["Image Processing", "Annotation"]
 contributions:
   commands:
     - id: synaptic_reconstruction.segment
-      python_name: synaptic_reconstruction.tools.synaptic_plugin.segmentation_widget:get_segmentation_widget
+      python_name: synaptic_reconstruction.tools.segmentation_widget:SegmentationWidget
       title: Segment
     - id: synaptic_reconstruction.distance_measure
-      python_name: synaptic_reconstruction.tools.synaptic_plugin.distance_measure_widget:get_distance_measure_widget
+      python_name: synaptic_reconstruction.tools.distance_measure_widget:DistanceMeasureWidget
       title: Distance Measurement
     - id: synaptic_reconstruction.file_reader
       title: Read volumetric data

synaptic_reconstruction/napari.yaml

@@ -1,9 +1,12 @@
 from pathlib import Path
+
 import napari
-from qtpy.QtWidgets import QWidget, QVBoxLayout, QHBoxLayout, QPushButton, QFileDialog, QLabel, QSpinBox, QLineEdit, QGroupBox, QFormLayout, QFrame, QComboBox, QCheckBox
 import qtpy.QtWidgets as QtWidgets
+
+from qtpy.QtWidgets import (
+    QWidget, QVBoxLayout, QHBoxLayout, QLabel, QSpinBox, QComboBox, QCheckBox
+)
 from superqt import QCollapsible
-from magicgui.widgets import create_widget
 
 
 class BaseWidget(QWidget):
@@ -15,7 +18,7 @@ def __init__(self):
     def _create_layer_selector(self, selector_name, layer_type="Image"):
         """
         Create a layer selector for an image or labels and store it in a dictionary.
-        
+
         Parameters:
         - selector_name (str): The name of the selector, used as a key in the dictionary.
         - layer_type (str): The type of layer to filter for ("Image" or "Labels").
@@ -34,24 +37,24 @@ def _create_layer_selector(self, selector_name, layer_type="Image"):
         selector_widget = QtWidgets.QWidget()
         image_selector = QtWidgets.QComboBox()
         layer_label = QtWidgets.QLabel(f"{selector_name} Layer:")
-        
+
         # Populate initial options
         self._update_selector(selector=image_selector, layer_filter=layer_filter)
-        
+
         # Update selector on layer events
         self.viewer.layers.events.inserted.connect(lambda event: self._update_selector(image_selector, layer_filter))
         self.viewer.layers.events.removed.connect(lambda event: self._update_selector(image_selector, layer_filter))
 
         # Store the selector in the dictionary
         self.layer_selectors[selector_name] = selector_widget
-        
+
         # Set up layout
         layout = QVBoxLayout()
         layout.addWidget(layer_label)
         layout.addWidget(image_selector)
         selector_widget.setLayout(layout)
         return selector_widget
-    
+
     def _update_selector(self, selector, layer_filter):
         """Update a single selector with the current image layers in the viewer."""
         selector.clear()
@@ -62,10 +65,10 @@ def _get_layer_selector_data(self, selector_name):
         """Return the data for the layer currently selected in a given selector."""
         if selector_name in self.layer_selectors:
             selector_widget = self.layer_selectors[selector_name]
-            
+
             # Retrieve the QComboBox from the QWidget's layout
             image_selector = selector_widget.layout().itemAt(1).widget()
-            
+
             if isinstance(image_selector, QComboBox):
                 selected_layer_name = image_selector.currentText()
                 if selected_layer_name in self.viewer.layers:
@@ -176,7 +179,7 @@ def _make_collapsible(self, widget, title):
         collapsible.addWidget(widget)
         parent_widget.layout().addWidget(collapsible)
         return parent_widget
-    
+
     def _add_boolean_param(self, name, value, title=None, tooltip=None):
         checkbox = QCheckBox(name if title is None else title)
         checkbox.setChecked(value)

synaptic_reconstruction/tools/synaptic_plugin/base_widget.py renamed to synaptic_reconstruction/tools/base_widget.py

@@ -1,13 +1,35 @@
+import os
+
 import napari
 import napari.layers
+import pandas as pd
+
 from napari.utils.notifications import show_info
-from qtpy.QtWidgets import QWidget, QVBoxLayout, QPushButton, QLabel, QComboBox
+from qtpy.QtWidgets import QWidget, QVBoxLayout, QPushButton
 
 from .base_widget import BaseWidget
-
-# Custom imports for model and prediction utilities
-from synaptic_reconstruction import distance_measurements
-from ..util import save_to_csv
+from .. import distance_measurements
+
+try:
+    from napari_skimage_regionprops import add_table
+except ImportError:
+    add_table = None
+
+
+def _save_distance_table(save_path, data):
+    ext = os.path.splitext(save_path)[1]
+    if ext == "":  # No file extension given, By default we save to CSV.
+        file_path = f"{save_path}.csv"
+        data.to_csv(file_path, index=False)
+    elif ext == ".csv":  # Extension was specified as csv
+        file_path = save_path
+        data.to_csv(file_path, index=False)
+    elif ext == ".xlsx":  # We also support excel.
+        file_path = save_path
+        data.to_excel(file_path, index=False)
+    else:
+        raise ValueError("Invalid extension for table: {ext}. We support .csv or .xlsx.")
+    return file_path
 
 
 class DistanceMeasureWidget(BaseWidget):
@@ -20,15 +42,16 @@ def __init__(self):
         self.image_selector_name1 = "Segmentation 1"
         self.image_selector_name2 = "Segmentation 2"
         # Create the image selection dropdown
+        # TODO: update the names to make it easier to distinguish what is what.
         self.segmentation1_selector_widget = self._create_layer_selector(self.image_selector_name1, layer_type="Labels")
         self.segmentation2_selector_widget = self._create_layer_selector(self.image_selector_name2, layer_type="Labels")
 
         # create save path
         self.settings = self._create_settings_widget()
 
         # create buttons
-        self.measure_pairwise_button = QPushButton('Measure Distance Pairwise')
-        self.measure_segmentation_to_object_button = QPushButton('Measure Distance Segmentation to Object')
+        self.measure_pairwise_button = QPushButton("Measure Distance Pairwise")
+        self.measure_segmentation_to_object_button = QPushButton("Measure Distance Segmentation to Object")
 
         # Connect buttons to functions
         self.measure_pairwise_button.clicked.connect(self.on_measure_pairwise)
@@ -50,7 +73,6 @@ def on_measure_segmentation_to_object(self):
         if segmentation1_data is None or segmentation2_data is None:
             show_info("Please choose both segmentation layers.")
             return
-        # get save_path
 
         (distances,
          endpoints1,
@@ -59,18 +81,16 @@ def on_measure_segmentation_to_object(self):
             segmentation=segmentation1_data,
             segmented_object=segmentation2_data,
             distance_type="boundary",
-            # save_path=self.save_path
         )
+
         if self.save_path.text() != "":
-            # save to csv
-            header = "distances endpoints1 endpoints2 seg_ids"
-            header_list = header.split(" ")
-            file_path = save_to_csv(
-                self.save_path.text(),
-                data=(distances, endpoints1, endpoints2, seg_ids),
-                header=header_list
-                )
-            show_info(f"Measurements saved to {file_path}")
+            data = {"label": seg_ids, "distance": distances}
+            axis_names = "zyx" if endpoints1.shape[1] == 3 else "yx"
+            data.update({f"begin-{ax}": endpoints1[:, i] for i, ax in enumerate(axis_names)})
+            data.update({f"end-{ax}": endpoints2[:, i] for i, ax in enumerate(axis_names)})
+            data = pd.DataFrame(data)
+            file_path = _save_distance_table(self.save_path.text(), data)
+
         lines, properties = distance_measurements.create_object_distance_lines(
             distances=distances,
             endpoints1=endpoints1,
@@ -79,19 +99,23 @@ def on_measure_segmentation_to_object(self):
         )
 
         # Add the lines layer
-        self.viewer.add_shapes(
+        line_layer = self.viewer.add_shapes(
             lines,
             name="Distance Lines",
             shape_type="line",  # Specify the shape type as 'line'
             edge_width=2,
             edge_color="red",
             blending="additive",  # Use 'additive' for blending if needed
         )
+
+        # FIXME: this doesn't work yet
+        if add_table is not None:
+            add_table(line_layer, self.viewer)
+
         if self.save_path.text() != "":
             show_info(f"Added distance lines and saved file to {file_path}.")
         else:
             show_info("Added distance lines.")
-        return
 
     def on_measure_pairwise(self):
         if self.image is None:
@@ -120,14 +144,8 @@ def _create_settings_widget(self):
         # setting_values.setToolTip(get_tooltip("embedding", "settings"))
         setting_values.setLayout(QVBoxLayout())
 
-        self.save_path, layout = self._add_path_param(
-            name="Save Directory", select_type="directory", value=""
-        )
+        self.save_path, layout = self._add_path_param(name="Save Table", select_type="file", value="")
         setting_values.layout().addLayout(layout)
 
         settings = self._make_collapsible(widget=setting_values, title="Advanced Settings")
         return settings
-
-
-def get_distance_measure_widget():
-    return DistanceMeasureWidget()

synaptic_reconstruction/tools/distance_measurement.py renamed to synaptic_reconstruction/tools/deprecated/distance_measurement.py

@@ -4,10 +4,7 @@
 from qtpy.QtWidgets import QWidget, QVBoxLayout, QPushButton, QLabel, QComboBox
 
 from .base_widget import BaseWidget
-from synaptic_reconstruction.training.supervised_training import get_2d_model
-
-# Custom imports for model and prediction utilities
-from ..util import run_segmentation, get_model_registry, _available_devices
+from .util import run_segmentation, get_model_registry, _available_devices
 
 
 class SegmentationWidget(BaseWidget):
@@ -23,7 +20,7 @@ def __init__(self):
         self.image_selector_widget = self._create_layer_selector(self.image_selector_name, layer_type="Image")
 
         # create buttons
-        self.predict_button = QPushButton('Run Segmentation')
+        self.predict_button = QPushButton("Run Segmentation")
 
         # Connect buttons to functions
         self.predict_button.clicked.connect(self.on_predict)
@@ -78,6 +75,7 @@ def on_predict(self):
             show_info("Please choose an image.")
             return
 
+        # FIXME: don't hard-code tiling here, but figure it out centrally in the prediction function.
         # get tile shape and halo from the viewer
         tiling = {
             "tile": {
@@ -111,9 +109,6 @@ def on_predict(self):
         # Add the segmentation layer
         self.viewer.add_labels(segmentation, name=f"{model_key}-segmentation")
         show_info(f"Segmentation of {model_key} added to layers.")
-        # alternatively return the segmentation and layer_kwargs
-        # layer_kwargs = {"colormap": "inferno", "blending": "additive"}
-        # return segmentation, layer_kwargs
 
     def _create_settings_widget(self):
         setting_values = QWidget()
@@ -142,15 +137,11 @@ def _create_settings_widget(self):
             # tooltip=get_tooltip("embedding", "halo")
         )
         setting_values.layout().addLayout(layout)
-        
+
         self.scale_param, layout = self._add_float_param(
             "scale", 0.5, min_val=0.0, max_val=8.0,
         )
         setting_values.layout().addLayout(layout)
 
         settings = self._make_collapsible(widget=setting_values, title="Advanced Settings")
         return settings
-
-
-def get_segmentation_widget():
-    return SegmentationWidget()