moved instance seg + segres dims in infer + fixed popup in inference + rm test in helper

Author: C-Achard

napari_cellseg3d/interface.py

@@ -221,7 +221,7 @@ def add_to_group(title, widget, layout, L=7, T=20, R=7, B=11):
     layout.addWidget(group)
 
 
-def make_group(title, L=7, T=20, R=7, B=11):
+def make_group(title, L=7, T=20, R=7, B=11, parent=None):
     """Creates a group widget and layout, with a header (`title`) and content margins for top/left/right/bottom `L, T, R, B` (in pixels)
     Group widget and layout returned will have a Fixed size policy.
 
@@ -231,8 +231,12 @@ def make_group(title, L=7, T=20, R=7, B=11):
         T (int): top margin
         R (int): right margin
         B (int): bottom margin
+        parent (QWidget) : parent widget. If None, no parent is set
     """
-    group = QGroupBox(title)
+    if parent is None:
+        group = QGroupBox(title)
+    else:
+        group = QGroupBox(title, parent=parent)
     group.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed)
     layout = QVBoxLayout()
     layout.setContentsMargins(L, T, R, B)
@@ -241,10 +245,11 @@ def make_group(title, L=7, T=20, R=7, B=11):
     return group, layout
 
 
-def make_container(L=0, T=0, R=1, B=11, vertical=True):
+def make_container(L=0, T=0, R=1, B=11, vertical=True, parent=None):
     """Creates a QWidget and a layout for the purpose of containing other modules, with a Fixed layout.
 
     Args:
+        parent : parent widget. If None, no widget is set
         L (int): left margin of layout
         T (int): top margin of layout
         R (int): right margin of layout
@@ -255,7 +260,10 @@ def make_container(L=0, T=0, R=1, B=11, vertical=True):
         QWidget : widget that contains the other widgets. Fixed size.
         QBoxLayout :  H/V Box layout to add contained widgets in. Fixed size.
     """
-    container_widget = QWidget()
+    if parent is None:
+        container_widget = QWidget()
+    else:
+        container_widget = QWidget(parent)
 
     if vertical:
         container_layout = QVBoxLayout()

napari_cellseg3d/model_workers.py

@@ -40,6 +40,10 @@
 from tifffile import imwrite
 
 # local
+from napari_cellseg3d.model_instance_seg import (
+    binary_watershed,
+    binary_connected,
+)
 from napari_cellseg3d import utils
 
 """
@@ -64,6 +68,7 @@ class LogSignal(WorkerBaseSignals):
 
     log_signal = Signal(str)
     """qtpy.QtCore.Signal: signal to be sent when some text should be logged"""
+
     # Should not be an instance variable but a class variable, not defined in __init__, see
     # https://stackoverflow.com/questions/2970312/pyqt4-qtcore-pyqtsignal-object-has-no-attribute-connect
 
@@ -155,6 +160,9 @@ def log(self, text):
 
     def log_parameters(self):
 
+        self.log("-" * 20)
+        self.log("Parameters summary :")
+
         self.log(f"Model is : {self.model_dict['name']}")
         if self.transforms["thresh"][0]:
             self.log(
@@ -173,10 +181,19 @@ def log_parameters(self):
         else:
             self.log(f"Dataset loaded on {self.device}")
 
+        if self.transforms["zoom"][0]:
+            self.log(
+                f"Anisotropy parameters are : {self.transforms['zoom'][1]} microns in x,y,z"
+            )
+
         if self.instance_params["do_instance"]:
-            # TODO move instance seg
-            self.log(f"Instance segmentation enabled")
+            self.log(
+                f"Instance segmentation enabled, method : {self.instance_params['method']}\n"
+                f"Probability threshold is {self.instance_params['threshold']:.2f}\n"
+                f"Objects smaller than {self.instance_params['size_small']} pixels will be removed"
+            )
             # self.log(f"")
+        self.log("-" * 20)
 
     def inference(self):
         """
@@ -234,8 +251,7 @@ def inference(self):
         self.log("\nChecking dimensions...")
         pad = utils.get_padding_dim(check)
         # print(pad)
-        dims = 128
-        # dims = 64 # TODO
+        dims = self.model_dict["segres_size"]
 
         model = self.model_dict["class"].get_net()
         if self.model_dict["name"] == "SegResNet":
@@ -304,7 +320,7 @@ def inference(self):
             for i, inf_data in enumerate(inference_loader):
 
                 self.log("-" * 10)
-                self.log(f"Inference started on image n°{i+1}...")
+                self.log(f"Inference started on image n°{i + 1}...")
 
                 inputs = inf_data["image"]
                 # print(inputs.shape)
@@ -350,6 +366,7 @@ def inference(self):
                 out = post_process_transforms(out)
                 out = np.array(out).astype(np.float32)
                 out = np.squeeze(out)
+                to_instance = out  # avoid post processing since thresholding is done there anyway
 
                 # batch_len = out.shape[1]
                 # print("trying to check len")
@@ -391,8 +408,31 @@ def inference(self):
                     self.log(
                         f"\nRunning instance segmentation for image n°{image_id}"
                     )
-                    method = self.instance_params["method"]
-                    instance_labels = method(out)
+
+                    threshold = self.instance_params["threshold"]
+                    size_small = self.instance_params["size_small"]
+                    method_name = self.instance_params["method"]
+
+                    if method_name == "Watershed":
+
+                        def method(image):
+                            return binary_watershed(
+                                image, threshold, size_small
+                            )
+
+                    elif method_name == "Connected components":
+
+                        def method(image):
+                            return binary_connected(
+                                image, threshold, size_small
+                            )
+
+                    else:
+                        raise NotImplementedError(
+                            "Selected instance segmentation method is not defined"
+                        )
+
+                    instance_labels = method(to_instance)
 
                     instance_filepath = (
                         self.results_path
@@ -526,10 +566,11 @@ def log(self, text):
 
     def log_parameters(self):
 
-        self.log("\nParameters summary :\n")
+        self.log("-" * 20)
+        self.log("Parameters summary :\n")
 
         self.log(
-            f"Percentage of dataset used for validation : {self.validation_percent*100}%"
+            f"Percentage of dataset used for validation : {self.validation_percent * 100}%"
         )
         self.log("-" * 10)
         self.log("Training files :\n")
@@ -892,7 +933,7 @@ def train(self):
                     yield train_report
 
                     weights_filename = (
-                        f"{model_name}_best_metric" + f"_epoch_{epoch+1}.pth"
+                        f"{model_name}_best_metric" + f"_epoch_{epoch + 1}.pth"
                     )
 
                     if metric > best_metric:

napari_cellseg3d/plugin_convert.py

@@ -101,7 +101,7 @@ def build(self):
         ui.add_blank(layout=layout, widget=self)
         #############################################################
         folder_group_w, folder_group_l = ui.make_group(
-            "Convert folder", l, t, r, b
+            "Convert folder", l, t, r, b, parent=None
         )
 
         folder_group_l.addWidget(
@@ -127,7 +127,7 @@ def build(self):
         ui.add_blank(layout=layout, widget=self)
         #############################################################
         layer_group_w, layer_group_l = ui.make_group(
-            "Convert selected layer", l, t, r, b
+            "Convert selected layer", l, t, r, b, parent=None
         )
 
         ui.add_widgets(
@@ -142,7 +142,7 @@ def build(self):
         ui.add_blank(layout=layout, widget=self)
         #############################################################
         small_group_w, small_group_l = ui.make_group(
-            "Remove small objects", l, t, r, b
+            "Remove small objects", l, t, r, b,parent=None
         )
 
         ui.add_widgets(

napari_cellseg3d/plugin_helper.py

@@ -14,7 +14,9 @@ class Helper(QWidget):
     def __init__(self, viewer: "napari.viewer.Viewer"):
         super().__init__()
 
-        self.help_url = "https://adaptivemotorcontrollab.github.io/cellseg3d-docs/"
+        self.help_url = (
+            "https://adaptivemotorcontrollab.github.io/cellseg3d-docs/"
+        )
 
         self.about_url = "https://wysscenter.ch/advances/3d-computer-vision-for-brain-analysis"
         self._viewer = viewer
@@ -35,14 +37,11 @@ def build(self):
         vbox = QVBoxLayout()
 
         widgets = [
+            self.info_label,
             self.btn1,
             self.btn2,
             self.btnc,
         ]
-        #################
-        if self.test:
-            widgets.append(self.epoch)
-        #################
         ui.add_widgets(vbox, widgets)
         self.setLayout(vbox)
         # self.show()